# Challenges in AI–dApp Integration Despite rapid progress in artificial intelligence and decentralized applications (dApps), the integration of these two domains remains highly fragmented, inefficient, and in many cases fundamentally incompatible. Without solving these bottlenecks, the vision of autonomous AI agents operating as transparent and trustworthy participants in Web3 cannot be realized. *** #### 1. Centralized AI Silos Most modern AI systems are controlled through **centralized APIs** provided by large corporations. Access to these APIs is permissioned, costs are high, and their internal mechanisms remain opaque. Developers cannot audit how inputs are processed, what datasets are used, or whether models introduce bias. This undermines the transparency and verifiability that Web3 ecosystems require. Furthermore, when AI outputs are consumed in decentralized contexts, they inherit the opacity of these black-box APIs. Similarly, privacy-preserving schemes like encryption or access control are not natively supported in these platforms, making them poorly suited for trustless environments ([arXiv, 2023](https://arxiv.org/abs/2305.03928?utm_source=chatgpt.com)). In short, AI remains locked in proprietary silos, preventing it from aligning with the principles of **decentralization, composability, and user ownership**. *** #### 2. Complexity of dApp Interactions On the Web3 side, accessing decentralized applications typically involves **low-level smart contract interactions**. Contracts expose ABIs, but every integration requires custom wrappers, gas fee handling, and chain-specific code. This results in a fragmented developer experience and creates steep technical barriers for non-expert users. An ACM Computing Surveys article on blockchain technology stresses that *interoperability, system complexity, and lack of standardization are primary obstacles in real deployments* ([ACM Computing Surveys, 2024](https://dl.acm.org/doi/10.1145/3700641?utm_source=chatgpt.com)). These difficulties mean that even simple user goals—such as querying balances or automating a DeFi position—require extensive manual coding and infrastructure management. Consequently, AI agents today cannot interact fluidly with dApps, because the integration burden is prohibitive. This results in a **two-sided deadlock**: dApps remain technically inaccessible to most users, and AI remains unable to act as a universal interface to them. *** #### 3. Lack of Composability Between AI and On-Chain Services Composability is a cornerstone of Web3, but current AI–blockchain integrations fail to achieve it. Existing solutions rely on **hard-coded connectors or centralized middleware** that map specific AI outputs to specific contract calls. This creates brittle, one-off pipelines that must be rebuilt whenever a new contract or service emerges. Peng et al. (2025) argue that *trustworthy AI integration requires standardized protocols and cryptographic verification mechanisms*—yet most current efforts neglect lifecycle aspects like discovery, invocation, and auditing ([arXiv, 2025](https://arxiv.org/abs/2505.20136?utm_source=chatgpt.com)). Similarly, Sun et al. show in zkLLM research that while *AI inference can be verified via zero-knowledge proofs*, the overhead makes such systems impractical without modular, reusable integration frameworks ([arXiv, 2024](https://arxiv.org/pdf/2404.16109?utm_source=chatgpt.com)). This lack of composability means AI agents cannot dynamically discover and use blockchain services in the same way they do Web2 APIs. As a result, **innovation is throttled** by the need for manual adaptation. *** #### 4. Security and Trust Deficits Even if AI could connect seamlessly to dApps, the **security model remains underdeveloped**. Allowing autonomous AI agents to trigger on-chain transactions creates risks of manipulation, bugs, or outright malicious exploitation. Most prototypes solve this by requiring human approvals for every step, which compromises both automation and decentralization. Gănescu and Passerat-Palmbach (2024) demonstrate how *zero-knowledge proofs (ZKPs) could enhance trust in generative AI*, but they also note that cost and scalability limit practical adoption ([arXiv, 2024](https://arxiv.org/pdf/2402.06414?utm_source=chatgpt.com)). Keršič et al. (2024) similarly highlight that *on-chain verification of ML models remains too resource-intensive for production use*, leaving a gap between theoretical trust and operational security ([ScienceDirect, 2024](https://www.sciencedirect.com/science/article/pii/S1319157824002969?utm_source=chatgpt.com)). Without standardized guardrails—such as multi-sig control, permission scopes, or verifiable computation—AI-driven blockchain actions remain **risky and difficult to audit**. *** #### 5. Limitations of Existing Attempts Several academic and industry efforts have explored AI–blockchain integration, often through oracles or middleware. However, most face critical limitations: * **Centralization**: reliance on off-chain servers or registries as single points of failure. * **Lack of standards**: each integration defines its own communication format, reducing reusability. * **No incentives**: developers contributing tools receive no ongoing economic benefit. * **Cryptographic immaturity**: while MPC and zkML research is advancing, real-world adoption is minimal. Li et al. classify privacy-preserving schemes and conclude that *scalability, latency, and deployment complexity remain largely unresolved* ([arXiv, 2023](https://arxiv.org/abs/2305.03928?utm_source=chatgpt.com)). Keršič et al. emphasize that while *zkML offers strong guarantees*, current proof sizes and circuit overheads are still prohibitive for autonomous agent workflows ([ScienceDirect, 2024](https://www.sciencedirect.com/science/article/pii/S1319157824002969?utm_source=chatgpt.com)). Thus, existing attempts remain **isolated experiments rather than sustainable ecosystems**. *** #### 6. The Resulting Gap The net effect of these challenges is a **fundamental gap** between AI’s potential and Web3’s infrastructure. AI remains locked in opaque, centralized silos, while decentralized applications remain inaccessible and fragmented. Without a unified framework that enables: * Dynamic discovery of blockchain tools, * Privacy-preserving and verifiable AI execution, * Developer incentives aligned with ecosystem growth, and * Security-first, auditable operations, the vision of **autonomous AI agents operating natively, transparently, and securely on-chain** will remain unrealized. # Why REVOX Exists At REVOX, our mission is to **unlock the full potential of artificial intelligence in decentralized environments** by enabling AI agents to become **native participants in the blockchain economy**. We envision a world where AI systems do not merely analyze blockchain data as external observers, but actively engage, transact, and coordinate as autonomous entities with verifiable trust and accountability.
#### From Centralized AI to Decentralized Intelligence Today, most AI applications are constrained by closed APIs and centralized platforms that limit transparency, composability, and ownership. Users must trust opaque infrastructures, while developers face integration challenges and limited monetization opportunities. REVOX aims to break this paradigm by introducing the **on-chain Model Context Protocol (oMCP)**, which transforms every smart contract into a universally accessible AI tool. In doing so, REVOX provides the missing bridge between **the intelligence layer of AI and the execution layer of Web3**. Through oMCP, AI agents can: * Dynamically discover and invoke blockchain services across multiple networks without custom integration. * Collaborate with each other through standardized protocols, creating a composable ecosystem of autonomous agents. * Execute actions transparently on-chain, ensuring every step is auditable and verifiable. #### Creating Value for Developers, Researchers, and Investors
* **For Developers**, REVOX provides low-code tooling and SDKs that dramatically reduce the complexity of building AI-powered decentralized applications. Every smart contract becomes a ready-to-use plugin, accelerating innovation and enabling faster go-to-market cycles. * **For Researchers**, REVOX is a living laboratory for multi-agent systems, secure computation, and cryptographic verification. It provides a unique testbed where ideas in AI safety, zero-knowledge proofs, or multi-party computation can be validated in real economic environments. * **For Investors and Ecosystem Partners**, REVOX offers a platform with real user traction, sustainable tokenomics, and a first-mover advantage in the emerging decentralized AI agent economy. The $REX token aligns incentives across all participants, powering payments, staking, and rewards in a transparent and scalable manner. #### Security, Trust, and Governance as First Principles REVOX is committed to ensuring that autonomous AI agents act within secure, auditable, and well-governed frameworks. By embedding multi-signature controls, DAO-based governance, and cryptographic verification such as zkML and MPC, the platform safeguards against abuse while maintaining agility. This trust-first approach is critical for enterprises, institutions, and users who depend on the reliability of AI agents handling valuable assets and decisions. #### Building the AI Agent Economy Our long-term mission is to foster a **self-sustaining ecosystem where intelligence itself becomes an on-chain commodity**. Developers who contribute tools and services are rewarded through protocol incentives; users can access personalized AI companions, financial automation, or data-driven insights with token-based payments; and the broader community benefits from an open, composable marketplace of intelligence. By combining **technical excellence, economic sustainability, and community-driven governance**, REVOX aspires to become the backbone of a new era: the **Decentralized AI Agent Economy**. # Solutions Powered by REVOX REVOX introduces the **on-chain Model Context Protocol (oMCP)** as the foundation for enabling AI agents to operate as native participants in Web3. By solving the limitations of current AI–dApp integration, oMCP establishes a standardized, extensible, and verifiable infrastructure that allows AI to become the execution layer of decentralized intelligence. Unlike existing middleware or centralized API gateways, REVOX does not rely on ad hoc connectors. Instead, it provides a **unified framework where every smart contract can be discovered and invoked by AI agents as if it were a tool**. This approach fundamentally lowers the barrier for developers, increases trust for researchers and regulators, and unlocks a wide range of real-world applications for users. *** #### Key Design Principles of REVOX Solutions 1. **Universal Composability**\ Any smart contract registered on oMCP can be transformed into an AI-accessible service. Developers no longer need to create wrappers or adapters; instead, the oMCP registry and code generator automatically expose functions as tools discoverable by AI agents. This design ensures that as new dApps emerge, they become immediately usable within the AI agent economy. 2. **Dynamic Discovery and Standardization**\ AI agents interact with oMCP servers via a lightweight protocol that standardizes capability discovery. This allows agents to learn in real time what tools and contracts are available across multiple chains. The result is **true dynamic composability**, where agents can adapt to evolving ecosystems without reprogramming. 3. **Security and Governance by Design**\ Autonomous execution requires trust. REVOX integrates multi-signature wallets, permission scopes, auditable logs, and DAO-style governance. Combined with cryptographic primitives such as zero-knowledge machine learning (zkML) and secure multi-party computation, this creates a secure environment for AI-driven transactions. 4. **Multi-Chain Interoperability**\ The oMCP framework abstracts away the differences between chains like Ethereum, BNB Chain, and Layer 2 networks. AI agents see a unified tool interface, while oMCP servers handle chain-specific execution. This ensures **scalability across heterogeneous ecosystems** and prepares the platform for integration with future blockchain protocols. 5. **Incentivized Ecosystem**\ The $REX token powers payments, staking, and developer rewards. By aligning economic incentives with protocol usage, REVOX ensures that contributors of tools, oracles, and data sources are sustainably rewarded. This transforms REVOX into not just a technical framework but a **marketplace of decentralized intelligence**. *** #### Current Problems ↔ REVOX oMCP Solutions | **Current Problems** | **REVOX oMCP Solutions** | | ------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------- | | **Centralized AI silos** – Proprietary APIs, opaque models, high costs, no transparency | **Decentralized AI access** – AI agents interact directly with on-chain contracts and oracles, with outputs verifiable on-chain. | | **Complex dApp integration** – Manual wrappers, chain-specific coding, gas handling | **Automatic tool registration** – Any smart contract ABI can be registered once and instantly exposed as a callable tool. | | **Lack of composability** – Hard-coded pipelines, no dynamic discovery | **Dynamic discovery & composability** – AI agents query oMCP servers for available tools at runtime, enabling adaptive and interoperable workflows. | | **Security & trust deficits** – Risky execution, no standardized auditing | **Secure execution framework** – Multi-sig, DAO governance, auditable logs, and zk-based verification ensure safe operations. | | **Isolated industry attempts** – Centralized middleware, no incentives, weak cryptographic integration | **Open ecosystem & incentives** – Decentralized registry, developer rewards via $REX, SDKs, and Launchpad enable sustainable growth. | *** #### Practical Implications * **For Developers:** Faster go-to-market with AI-powered dApps, thanks to low-code tools and multi-language SDKs. No more boilerplate contract wrappers—every chain interaction is standardized. * **For Researchers:** A living testbed for studying multi-agent collaboration, secure computation, and privacy-preserving AI in real economic environments. * **For Investors and Partners:** A sustainable, incentivized network powered by $REX, positioned as the backbone of the decentralized AI agent economy. *** #### Future Roadmap Integration The REVOX solutions are not static. The roadmap includes: * Expansion of **decentralized tool registries** into cross-chain standards. * Integration of **zkML verification pipelines** for auditable AI computation. * Enhanced developer experience with **REVOX Studio Launchpad**, enabling assetization and monetization of AI agents. * Strengthening of ecosystem alliances to push $REX adoption as the universal AI payment token. Together, these initiatives ensure REVOX evolves into a **comprehensive operating system for decentralized AI**, capable of supporting millions of users and billions of autonomous transactions. # oMCP Research ## oMCP Research: The On-Chain Model Context Protocol ### Abstract The **on-chain Model Context Protocol (oMCP)** is REVOX’s architecture for making *model context*—prompts, domain knowledge, on-/off-chain state, and tool interfaces—a first-class, verifiable resource for AI agents operating with smart contracts. Concretely, oMCP introduces contract/ABI registration, dynamic tool discovery, expanded Web3 data access (state, logs, storage, oracles), multi-language SDKs, and a roadmap toward cross-chain registries and one-click on-chain proxies. Combined with cryptographic or consensus verification (e.g., zkML, oracle attestations, or TEE-assisted modules), oMCP enables composable, auditable AI reasoning that dApps can invoke natively. *** ### 1. Introduction AI systems are context-driven, whereas dApps are verification-driven. Bridging these paradigms requires a way for agents to *discover* tools on chain, *compose* context with live state, and *return* results with verifiability. oMCP addresses this by standardizing how smart-contract tools are registered and exposed to agents; how agents query chain data and decentralized storage; and how off-chain inference or real-world data can be anchored back on chain with proofs or agreement. Relative to prior oracle-only designs, oMCP elevates the *context + invocation* surface itself into a protocol that agents can reason about and reuse. *** ### 2. Design Goals and Contributions **(G1) Dynamic discoverability.** Contracts are pre-registered with ABIs; an MCP server advertises a capability list so agents need not hard-code integrations. A server-side code generator emits service modules that map contract functions to invocable “tools.” **Contribution:** decouples agent logic from specific contracts while preserving typed interfaces. **(G2) Rich model context.** Beyond function calls, agents require chain state, historical logs, and documents (e.g., whitepapers, metadata) to condition inference. oMCP extends access to on-chain queries, decentralized storage (IPFS/Arweave), and oracle inputs to enrich the model context available at inference time. **(G3) Developer ergonomics.** SDKs (e.g., Python/TypeScript) abstract protocol details and data formatting for DeFi/NFT/dID scenarios, lowering time-to-integration. **(G4) Verifiability options.** oMCP is compatible with multiple verification routes—zk proof systems for ML inference, decentralized oracle attestations, or TEE-assisted execution—so applications can choose the right trust-performance point. ([arXiv](https://arxiv.org/abs/2502.18535?utm_source=chatgpt.com)) *** ### 3. Architecture and Implementation Phases The development of oMCP can be understood as an **iterative research program**, structured into four phases. Each phase expands the system’s functional surface while also surfacing new challenges in verifiability, scalability, and developer adoption. #### Phase 1 — Core Infrastructure and Registration Protocol The first phase establishes the minimal primitives necessary for agents to interact with smart contracts dynamically.
* **Contract & ABI Registration**: Smart contracts register themselves with an MCP server, publishing ABI interfaces and metadata. This allows automatic generation of service modules so agents can discover callable functions without preprogramming.
* **Capability Lists**: A standardized discovery protocol enumerates available tools, signatures, and access rules. Agents query this list to construct context windows dynamically. * **Dynamic Invocation**: Agents call functions through the MCP host↔server channel, which mediates parameter passing and type-checking. * **Research Insight**: This phase addresses the “rigid coupling” problem observed in early AI–Web3 integrations, where agents were forced to hard-code tools. oMCP introduces dynamic binding similar to service discovery in distributed systems. #### Phase 2 — Expanded Web3 Data Access and SDK Layer The second phase broadens the **contextual bandwidth** available to agents. * **State Queries**: Beyond function calls, oMCP supports queries for balances, storage slots, event logs, and historical transactions. * **Decentralized Storage**: Integration with IPFS and Arweave allows persistent content such as metadata or whitepapers to become part of the model context. * **Oracle Bridges**: Off-chain data (e.g., prices, external events) enters oMCP through standardized oracle interfaces. * **SDK v1.0**: Multi-language SDKs (Python/TypeScript) abstract discovery and invocation for developers, enabling integration in DeFi, NFT, or decentralized identity workflows. * **Research Insight**: This phase resonates with distributed database systems, where query languages abstract away underlying storage heterogeneity. By exposing richer data layers, oMCP allows agents to ground their reasoning in **domain-specific, high-value context**. #### Phase 3 — Operational Hardening and Security Extensions As oMCP is integrated into real-world applications, the need for trust and governance arises. * **Identity & Permissioning**: Introduction of authenticated tool invocation and permission scopes to prevent misuse. * **Multi-Signature Wallets**: Support for custodial workflows where multiple parties control sensitive agents. * **Auditing and Governance Hooks**: Tools for tracking provenance and ensuring accountable usage of context modules. * **TEE Integration**: Exploration of Trusted Execution Environments (e.g., Intel SGX, ARM TrustZone) for handling sensitive computations and confidential model inputs. * **Research Insight**: This phase maps closely to the literature on secure computation platforms (e.g., Ekiden, Town Crier), where enclave-backed execution adds confidentiality and integrity. It highlights the trade-offs between hardware trust assumptions and proof-based systems like zkML. #### Phase 4 — Multi-Chain Expansion and Ecosystem Integration The final phase focuses on scaling oMCP across ecosystems. * **Cross-Chain Registries**: Decentralized registries allow contracts on different blockchains to be uniformly discoverable. * **Universal Packaging**: Legacy contracts can be wrapped into standardized schemas, ensuring backward compatibility. * **On-Chain Proxies**: One-click proxy contracts enable frictionless registration for developers, minimizing integration cost. * **Marketplace Integration**: Agents, plugins, and context modules can be published and reused across ecosystems via Studio and Launchpads. * **Research Insight**: This phase reflects broader trends in **cross-chain interoperability research**, where universal schemas and registries attempt to unify fragmented ecosystems. For oMCP, the key contribution is to ensure that **contextual intelligence is portable and composable across chains**. *** ### 4. Verification Layer: Options and Trade-offs * **zkML proofs.** Zero-knowledge proof systems can attest that an ML model ran correctly on a given input—useful for sensitive or high-impact decisions. The literature details proof-system choices, prover/verifier costs, and emerging frameworks for verifiable inference. ([arXiv](https://arxiv.org/abs/2502.18535?utm_source=chatgpt.com)) * **Decentralized oracle attestations.** TLS-anchored proofs (e.g., DECO) attest to the authenticity of off-chain data without trusted servers, offering an alternative to TEE-only designs and enabling selective disclosure. ([ACM Digital Library](https://dl.acm.org/doi/10.1145/3372297.3417239?utm_source=chatgpt.com)) * **TEE-assisted execution.** Systems like Ekiden explore enclave-backed confidentiality and integrity for smart-contract computation; TEEs can also underpin authenticated data feeds (e.g., Town Crier), with known deployment considerations. ([arXiv](https://arxiv.org/abs/1804.05141?utm_source=chatgpt.com)) **Implication.** oMCP does not mandate a single trust primitive; instead it **parameterizes verification**, so developers pick per-use-case balances between latency, cost, and assurance. *** ### 5. Context Composition & Agent Orchestration oMCP’s discovery and context surface is orthogonal to any specific agent framework. Multi-agent patterns (task planners, tool-users, reviewers) can be layered atop oMCP so that agents first **retrieve context** (state/logs/docs) then **invoke tools** and **ground model outputs** back on chain. The literature on multi-agent LLM systems motivates these designs and suggests evaluation protocols for cooperative agents. ([arXiv](https://arxiv.org/abs/2308.08155?utm_source=chatgpt.com)) *** ### 6. Applications (Illustrative) * **DeFi risk & operations.** Score collateral health by combining vault state, market context, and oracle prices; trigger on-chain mitigations when thresholds are crossed. * **Governance intelligence.** Summarize proposals with historical participation logs and sentiment context retrieved via oMCP, then anchor results for auditability. * **Asset and identity services.** Compose NFT metadata/documents from decentralized storage with contract calls to deliver verifiable profile enrichment and content workflows. *** ### 7. Research Directions * **Context schemas & universal tooling.** Formalize schemas for reusable *context modules* and tool metadata (costs, side effects) across chains; extend the “universal packaging” line toward static analysis of legacy ABIs. * **Proof-efficiency for inference.** Reduce prover time and proof sizes for practical zkML in production agent loops. ([arXiv](https://arxiv.org/abs/2502.18535?utm_source=chatgpt.com)) * **Hybrid verification paths.** Combine zk attestations with TEE anchoring or oracle proofs to optimize for latency vs. assurance per workflow segment. ([ACM Digital Library](https://dl.acm.org/doi/10.1145/3372297.3417239?utm_source=chatgpt.com)) * **On-chain proxies & registries.** Finalize one-click registration and decentralized registries for cross-chain discoverability and lifecycle governance. *** ### 8. Conclusion oMCP reframes the AI-on-chain problem around **model context as an auditable, composable resource**. By coupling dynamic tool discovery and rich context access with configurable verification, it provides a pragmatic path from today’s siloed AI/dApp stacks to autonomous, verifiable agent workflows that dApps can *trust and act upon*. The phased roadmap—core infra → data/SDK → operational hardening → multi-chain/registries—maps cleanly to deployment realities and positions oMCP as a foundation for the next wave of intelligent Web3 systems. *** ### References * Ghodsi, A., Ruan, K., et al. (2023). *Zero-Knowledge Machine Learning: From Proof-of-Concept to Scalable Protocols.* arXiv:2303.01063. * Ruan, Y., et al. (2024). *zkML: Verifiable Machine Learning Inference via Zero-Knowledge Proofs.* IEEE Security & Privacy Workshops. * Juels, A., Kosba, A., & Shi, E. (2016). *The Ring of Gyges: Investigating the Future of Criminal Smart Contracts.* ACM CCS. * Cheng, R., et al. (2019). *Ekiden: A Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contracts.* EuroSys. * Zhang, F., Cecchetti, E., Juels, A., & Shi, E. (2016). *Town Crier: An Authenticated Data Feed for Smart Contracts.* ACM CCS. * Wooldridge, M. (2009). *An Introduction to MultiAgent Systems.* Wiley. * Russell, S., & Norvig, P. (2021). *Artificial Intelligence: A Modern Approach (4th Edition).* Pearson. # Onchain AI Oracle: DPrompt ## Overview DPrompt is an innovative AI inference oracle service that bridges the gap between computationally intensive AI inference tasks and blockchain’s on-chain operations. By leveraging an oracle-based design, DPrompt enables seamless integration of AI-powered functionalities within smart contracts, empowering decentralized applications (dApps) with advanced AI capabilities while maintaining the efficiency and security of blockchain operations. An **MVP demo** of DPrompt is deployed at: ## Why DPrompt? ### The Challenge of On-Chain AI Inference Performing AI inference directly on-chain is impractical due to its computational intensity and resource requirements. Blockchains, by design, are optimized for consensus and decentralized verification, not heavy computation. This limitation creates a significant gap for developers who want to incorporate AI insights into their decentralized applications. ### Oracles as a Solution Oracle frameworks are widely used in blockchain ecosystems to bring off-chain data, such as real-world events and market prices, to on-chain services. This well-established model can be extended to handle AI inference, providing a trusted, efficient way to deliver AI-driven results to smart contracts. ## DPrompt Design Principles **1. Decentralized Oracle Network** DPrompt operates within a decentralized oracle network, ensuring reliable delivery of AI inference results to the blockchain. This design reduces the risk of single points of failure and ensures trustless operations. **2. Off-Chain AI Inference** The heavy lifting of AI inference occurs off-chain within a secure, scalable infrastructure. These computations are performed by verified nodes, leveraging state-of-the-art AI models and hardware accelerators to deliver fast and accurate results. **3. Smart Contract Integration** DPrompt provides a seamless interface for smart contracts to request and receive AI inference results. Developers can write contracts that interact with the oracle to access AI-powered insights without leaving the blockchain environment. **4. Scalability and Cost Efficiency** By moving AI inference off-chain, DPrompt significantly reduces the computational burden on blockchain nodes, allowing for greater scalability and lower operational costs for dApps. **5. Verifiability** DPrompt ensures that all inference results are auditable and verifiable. It incorporates cryptographic proof mechanisms to guarantee the integrity and authenticity of the data delivered on-chain. ## Key Components of DPrompt
### AI Inference Layer **Model Repository** * **Role**: A library of pre-trained and fine-tuned AI models optimized for different use cases. * **Capabilities**: * Availability: A general DA for models * Customization: Allows developers to upload custom-trained models or request model fine-tuning for specific applications. * Versioning: Supports version control to ensure consistency in inference results and facilitate upgrades. **Inference Engine** * **Role**: Executes AI computations using high-performance hardware and algorithms. * **Capabilities:** * Resource Optimization: Dynamically allocates GPU, TPU, or other accelerators based on the complexity of the task. * Fault Tolerance: Ensures uninterrupted operation by rerouting tasks in case of node failures. * Latency Minimization: Optimizes response times to meet real-time application needs. ### Oracle Network **Dispatcher Nodes** * **Role**: The dispatcher node acts as the central coordinator for the oracle network. It collects inference requests from the blockchain and distributes them to appropriate nodes for processing. * **Capabilities:** * **Request Management**: Receives inference requests from smart contracts and validates them. * **Task Allocation**: Dispatches requests to a set of available and verified oracle nodes based on workload, specialization, or geographic proximity. * **Result Aggregation**: Collects the inference results from nodes and ensures they meet the required standards of quality and accuracy before relaying them back to the requesting smart contract. * **Incentive Calculation**: Calculates rewards for inference nodes **Inference Nodes** * **Role**: Decentralized containers responsible for performing inference tasks using Inference Engines. * **Capabilities**: * **Inference Execution**: Execute computationally heavy AI tasks using pre-trained models provided by DPrompt. * **Result Submission**: Send results back to the dispatcher node along with cryptographic proofs to ensure the authenticity and integrity of the results. **Consensus Protocol** * **Purpose**: A mechanism (e.g. Proof-of-Stake) to ensure the correctness of results provided by oracle nodes. ### Smart Contract Interface The Smart Contract Interface is the primary touchpoint for developers to interact with DPrompt’s AI inference capabilities. It provides an intuitive and secure way to request and receive AI-powered insights directly within blockchain applications. **API Design** * **Purpose**: Simplifies communication between smart contracts and the oracle network. * **Features:** * Request Submission: Smart contracts can invoke DPrompt by specifying the task type, input data, and any additional parameters required for the AI model. * Output Specification: Developers can define the expected format and type of the AI inference result (e.g., text, JSON, numerical values). * Error Handling: Built-in mechanisms to notify smart contracts of invalid requests, inference errors, or delays.Intuitive APIs that allow developers to request specific AI tasks and retrieve the results. **Event Notifications** * **Role**: Provides asynchronous updates to smart contracts once inference results are ready. * **Mechanism:** * Event Logs: Emits blockchain events to signal the completion of a request. * Callback Functions: Supports user-defined callback functions for handling the returned data. # Primitive Agents #### 1. Definition and Core Role Primitive Agents are the **atomic building blocks of REVOX’s decentralized AI agent ecosystem**. Each Primitive Agent is designed to perform a single, narrowly scoped task with high reliability and auditability. By following the *single responsibility principle*, they provide predictable, secure, and composable functionality. This design ensures that agents remain lightweight, reusable, and independently auditable, while still forming the foundation for advanced, compound workflows. In the REVOX ecosystem, Primitive Agents are comparable to the “Lego bricks” of decentralized intelligence. They are intentionally simple on their own, but when combined, they enable sophisticated workflows such as autonomous trading, compliance monitoring, data-driven governance, and prediction markets. *** #### 2. Architectural Principles 1. **Minimalism and Modularity** * Each agent focuses on one function only: signing transactions, fetching price data, analyzing charts, querying databases, or performing predictions. * Modularity allows agents to be upgraded, replaced, or reused independently without breaking higher-level workflows. 2. **Security by Design** * Local storage is encrypted, with support for hardware-based vaults for key management. * Agents operate within strict **permission scopes**, preventing unauthorized access to sensitive resources. * Role-based execution ensures that an agent designed for analytics cannot sign or broadcast transactions unless explicitly delegated. 3. **Performance and Reliability** * Primitive Agents follow strict performance benchmarks (latency <200ms for queries, >99.9% uptime for critical agents). * Built-in retry, fallback, and failover logic ensure reliability in real-world deployments. * Agents are load-tested to operate under high-concurrency scenarios, preparing them for millions of daily calls. 4. **Transparency and Auditability** * Every input, output, and execution path is logged in a verifiable format. * Logs can be persisted on-chain or in distributed storage, creating an immutable record for research, compliance, and forensic analysis. *** #### 3. Functional Categories of Primitive Agents * **Wallet Agents** * Handle address management, transaction signing, gas estimation, and secure broadcasting. * Provide APIs for both hot-wallet execution and cold-storage signing. * Equipped with customizable policies such as daily spending limits, multi-signature approval, or compliance filters. * **Ticker Agents** * Fetch real-time price feeds from decentralized exchanges and oracle networks. * Provide normalized, cached, and timestamped data streams to minimize latency. * Support anomaly detection, flagging price discrepancies across liquidity pools. * **Chart & Analytics Agents** * Aggregate and visualize historical market data. * Provide technical indicators (RSI, MACD, Bollinger Bands) directly callable by other agents. * Support predictive overlays, enabling trend-based decision-making. * **Database Agents** * Manage structured and unstructured storage for agents. * Enable efficient context retrieval (e.g., user history, KYC records, workflow states). * Designed for scalable querying across both on-chain and off-chain datasets. * **Prediction Agents (New)** * Lightweight ML-based forecasters that handle token price prediction, volatility estimation, or anomaly detection. * Integrated with proof-based validation (zkML) to provide verifiable inference. * Enable risk-sensitive applications like automated trading or fraud detection. *** #### 4. Security and Trust Framework * **Isolated Execution Environment**: Each agent runs in a sandbox, minimizing the blast radius of potential vulnerabilities. * **Permissioned Capabilities**: Developers declare agent capabilities explicitly, and permissions must be granted before deployment. * **Cryptographic Guarantees**: Integration with zkML ensures that outputs can be cryptographically verified. * **Community Governance**: Agents can be registered, rated, and reviewed in a decentralized registry, creating a reputation-based trust layer. *** #### 5. Application Scenarios * **DeFi Automation**: A combination of Wallet Agent + Ticker Agent + Prediction Agent enables a self-rebalancing portfolio strategy. * **Compliance Monitoring**: Database Agent + Analytics Agent can track suspicious transactions and feed alerts into governance workflows. * **Data-driven Governance**: Primitive Agents can monitor DAO proposals, analyze participation trends, and surface insights to stakeholders. * **NFT and Gaming**: Agents can fetch NFT metadata, validate ownership, and automate asset transfers during gameplay. *** #### 6. Interoperability with Other Building Blocks * **Plugins**: Primitive Agents call Plugins to access external APIs (e.g., off-chain market data, compliance services). * **Context Knowledge**: Primitive Agents query static or curated domain knowledge to enrich their decisions with historical or off-chain context. * **Compound Agents**: Multiple Primitive Agents are orchestrated into workflows, enabling multi-step autonomous behaviors. * **DPrompt Oracle**: Outputs from Primitive Agents can be verified on-chain, ensuring their correctness in mission-critical contracts. *** #### 7. Why Primitive Agents Are Foundational By design, Primitive Agents ensure that REVOX remains **secure, composable, and scalable**. They embody three unique advantages: 1. **Auditability**: Unlike centralized AI APIs, Primitive Agents expose verifiable execution logs. 2. **Flexibility**: Any agent can be recombined to build new services, accelerating innovation. 3. **Resilience**: Modular design means failures in one agent do not compromise the entire system. Ultimately, Primitive Agents are not just technical components—they are the **bedrock of the decentralized AI agent economy**. Their simplicity and reliability make them the perfect foundation for a scalable, transparent, and trust-minimized infrastructure. # Plugins #### 1. Definition and Core Role In the anatomical analogy of the REVOX ecosystem, Primitive Agents form the **muscles and body**, while **Plugins act as the senses—the eyes, ears, and mouth**. They are the critical gateways through which REVOX agents perceive and interact with the external digital world. Plugins extend the boundaries of the ecosystem by enabling **direct API connections to external services**, spanning both traditional Web2 platforms and decentralized Web3 protocols. By serving as conduits for external intelligence and functionality, Plugins give Primitive Agents the ability to retrieve information, execute transactions, and leverage services beyond the native REVOX runtime. *** #### 2. Architectural Principles 1. **Clear Separation of Concerns** * Primitive Agents remain lightweight and focused. * Plugins handle specialized integrations—Web2 APIs, blockchain RPCs, third-party services. 2. **Standardized Interfaces** * Every Plugin implements a consistent API schema: request format, response schema, error codes, retry policies. * This ensures agents can interact seamlessly with any Plugin. 3. **Security and Permissions** * Plugins declare **capability scopes** (e.g., read-only query vs transaction execution). * Execution is sandboxed, with audit logs for every call. 4. **Versioning and Lifecycle Management** * Plugins are versioned; backward compatibility is maintained. * Deprecated or risky versions can be flagged in the Plugin Registry. 5. **Monitoring and Metrics** * Each Plugin tracks latency, error rates, and usage volume. * Poorly performing Plugins can be replaced or excluded by workflows. *** #### 3. Crypto-Related Plugin Use Cases * **Chain RPC Plugin** * Provides direct access to blockchain nodes for querying balances, transaction history, and broadcasting signed transactions. * Critical for enabling Wallet Agents or Compound Agents to execute DeFi strategies. * **Etherscan Plugin** * Integrates with the Etherscan API, letting agents retrieve verified contract metadata, historical transactions, and wallet analytics. * Used by compliance workflows or research agents. * **Token Price Plugin** * Fetches real-time token prices from multiple decentralized exchanges and oracle networks. * Includes safeguards such as median aggregation and anomaly detection for unreliable feeds. *** #### 4. Traditional Plugin Use Cases * **Google Search Plugin** * Empowers agents to perform knowledge retrieval tasks directly from the web. * Useful for research-oriented workflows or context enrichment. * **Twitter Plugin** * Connects agents to Twitter APIs, enabling social sentiment analysis, trending topic monitoring, and community engagement tasks. * **Location Service Plugin** * Supplies geolocation data to agents, enabling location-based logic for applications such as logistics or local compliance. * **Gmail Plugin** * Integrates email capabilities, allowing agents to parse, send, or organize communications. * Useful for productivity workflows and personal digital assistants. *** #### 5. Integration and Interfaces * **How Agents Interact**:\ Primitive Agents do not need to “understand” external protocols directly. Instead, they communicate with Plugins via standardized request/response schemas. * **API-Driven Design**:\ Plugins expose structured endpoints, not natural language. This ensures **deterministic, auditable, and reproducible behavior**. * **Seamless Workflows**:\ When building Compound Agents, Plugins are chained together with Primitive Agents, providing a smooth pipeline from intent → execution → verification. *** #### 6. Security and Governance * **Plugin Registry**: All Plugins are listed in the REVOX Plugin Registry, with metadata (capabilities, provider, version). * **Community Review**: Developers and users can audit, review, and rate Plugins, establishing a trust and reputation system. * **Permission Scopes**: For high-risk Plugins (e.g., transaction execution), stricter governance and multi-signature approval may be required. *** #### 7. Why Plugins Matter * **Extendibility**: They allow REVOX to rapidly integrate with new services and chains without modifying core agents. * **Specialization**: Plugin developers can focus on domain expertise (e.g., market data, social feeds), while agent developers focus on orchestration. * **Ecosystem Growth**: A Plugin marketplace incentivized by $REX ensures continuous evolution of capabilities and sustainable contribution. # Context Knowledge #### 1. Definition and Role In the diverse and expansive world of decentralized applications, agents must be capable of navigating **domain-specific tasks**—from interpreting intricate blockchain project details to engaging with specialized academic or financial datasets. General-purpose AI training is not sufficient; agents require **tailored access to curated, trustworthy, and up-to-date knowledge**. **Context Knowledge** within REVOX provides this capability. It equips agents with static and dynamic information sources that expand their situational awareness, improve decision accuracy, and enable adaptive responses in fast-evolving domains. By embedding domain-specific intelligence, REVOX ensures that agents are not generic assistants but **context-aware digital actors**. *** #### 2. Architectural Principles 1. **Layered Knowledge Model** * **Static Knowledge**: Immutable or rarely changing data (e.g., token metadata, project whitepapers). * **Dynamic Knowledge**: Continuously updated feeds (e.g., ticker lists, governance proposals, SKU lists). * **User-Customized Knowledge**: Privately curated inputs, enabling personal or enterprise-specific use cases. 2. **Verifiability and Provenance** * Each knowledge entry is associated with metadata: source, timestamp, and verification status. * This ensures traceability, accountability, and the ability to resolve conflicts when multiple sources disagree. 3. **Efficient Retrieval and Fusion** * Context Knowledge is indexed for **low-latency retrieval** (<100ms for common queries). * Agents use relevance scoring and weighting to merge static knowledge with real-time Plugin outputs. 4. **Adaptive Updating** * Knowledge entries are version-controlled, allowing rollback or comparison of historical vs current data. * Automated update pipelines ensure that rapidly changing domains (finance, governance) remain synchronized. 5. **Security and Privacy** * Sensitive user data (e.g., enterprise SKU lists, private research papers) are encrypted and access-controlled. * Compliance with global standards (GDPR, CCPA) ensures that Context Knowledge can be adopted by enterprises and institutions. *** #### 3. Use Cases for Context Knowledge * **Project Whitepapers and Technical Docs** * Agents can read and interpret project documentation, providing insights into tokenomics, roadmaps, and protocol mechanics. * Example: A Research Agent analyzing the consensus mechanism of a new L1 chain and summarizing its advantages for investors. * **Ticker Lists and Market Metadata** * Financial agents leverage real-time ticker lists to accurately map token symbols to underlying assets. * Example: A DeFi Agent distinguishing between wrapped and native tokens across multiple chains to execute safe swaps. * **SKU Lists for E-commerce** * E-commerce agents utilize structured SKU lists to guide product recommendations, price comparisons, and order automation. * Example: An AI shopping assistant comparing multiple vendors’ offers for the same product and optimizing purchase strategies. * **Regulatory & Compliance Knowledge** * Context Knowledge can store jurisdiction-specific compliance rules, enabling agents to enforce KYC/AML automatically. * Example: An Enterprise Agent that blocks transactions exceeding thresholds in restricted jurisdictions. * **Governance Archives** * DAO-related agents can query proposal histories, participation statistics, and treasury allocations. * Example: A Governance Agent summarizing community sentiment and highlighting deviations from past voting behavior. *** #### 4. Integration and Interfaces * **With Primitive Agents**: Primitive Agents query Context Knowledge for static information, reducing reliance on external calls. * **With Plugins**: Context Knowledge complements Plugins—while Plugins fetch fresh data, Context Knowledge provides authoritative baselines. * **With Compound Agents**: Complex workflows embed Context Knowledge nodes for decision-making checkpoints. * **With DPrompt Oracle**: Critical entries (e.g., compliance rules, price reference data) can be verified on-chain via proof mechanisms, ensuring trustworthy outcomes. *** #### 5. Governance and Ecosystem Value * **Knowledge Registry**: A decentralized registry allows knowledge modules to be published, updated, and rated. * **Community Curation**: Contributors earn rewards for curating or validating high-quality domain knowledge. * **Reputation Systems**: Sources are scored based on reliability and accuracy over time. * **Enterprise Adoption**: Enterprises can maintain private Context Knowledge repositories, integrated securely with REVOX agents. # Compound Agents and Workflows #### 1. Role in the REVOX Ecosystem REVOX is not just a collection of independent agents - it is an **orchestration system**. Compound Agents represent the next level of intelligence: they are **assembled from Primitive Agents, Plugins, and Context Knowledge** into workflows that can accomplish complex, multi-step objectives. Workflows provide the **blueprint** for how these components interact. This transforms the ecosystem from a set of isolated functions into a **flexible, composable network** capable of adapting to both developer-defined logic and user-driven prompts. *** #### 2. Architecture of Workflows * **Domain-Specific Language (DSL)** * A lightweight scripting framework that allows developers to define agent interactions with precision. * Supports branching logic, loops, conditional triggers, and parallel execution. * Example: A developer writes a workflow that *monitors ETH gas fees every 10 seconds and only triggers swaps when network cost is below a set threshold*. * **Prompt-Based Assembly** * For non-technical users, workflows can be created by simply describing goals in natural language. * The system interprets the prompt, maps it to relevant agents and plugins, and builds the workflow automatically. * Example: A user types *“Alert me when Uniswap liquidity for REX/USDT drops below $1M and recommend an alternative pool.”* * **Composability as a Core Principle** * Workflows allow simple blocks to be chained, nested, or reused. * A Compound Agent can itself be reused as a building block inside a larger workflow, creating hierarchical systems. * This composability ensures scalability: small, well-tested modules can be continuously recombined into novel solutions. *** #### 3. Practical Examples * **DeFi Liquidation Guard** * **Workflow**: Wallet Agent + Token Price Plugin + Prediction Agent. * **Function**: Continuously monitors loan collateral on Aave. If the health factor approaches 1.1, the workflow triggers an alert, calculates repayment options, and executes a partial repayment if approved by the user.
* **Cross-Chain Arbitrage Agent** * **Workflow**: Ticker Agent + Chain RPC Plugin (BSC & Arbitrum) + Wallet Agent. * **Function**: Detects price gaps between DEXs on different chains. Executes a two-legged swap if price differential >2% and estimated gas fees <0.5% of trade size.
* **DAO Proposal Monitor** * **Workflow**: Context Knowledge (Governance Archive) + Etherscan Plugin + Sentiment Plugin. * **Function**: Tracks new DAO proposals, summarizes historical context, checks Twitter sentiment, and delivers a digest report to the user’s Web Extension dashboard.
* **E-Commerce Shopping Agent** * **Workflow**: SKU Knowledge Base + Location Plugin + Payment Plugin. * **Function**: Finds the cheapest vendor for a specified product, compares shipping times to the user’s location, and automates checkout with stored wallet credentials.
* **Research Automation** * **Workflow**: Google Search Plugin + Context Knowledge (whitepapers) + Chart Agent. * **Function**: Gathers latest AI+blockchain papers, extracts methodology sections, compares with known models in Context Knowledge, and visualizes innovation trends. *** #### 4. Advantages of Workflows * **For Developers** * Fine-grained control with DSL, enabling reproducible, testable, and scalable automation. * Modular design reduces duplication - tested building blocks can be reused in new workflows. * **For Users** * Natural language prompts lower the barrier: powerful workflows can be created without coding. * Intuitive UI integration via the REVOX Web Extension allows oversight, quick edits, and visualization of workflow execution. # REVOX Web Extension #### 1. Definition and Core Role The REVOX Web Extension serves as the **cornerstone of user interaction within the REVOX ecosystem**. It is both a **secure local runtime** for managing personal AI agent instances and the **primary interface layer** for human–agent communication. By bridging user devices with decentralized AI infrastructure, the Web Extension ensures that users maintain privacy, control, and seamless accessibility across their REVOX experience. *** #### 2. Core Functionalities 1. **User Storage for Personal Agent Instances** * Provides a **secure vault** for storing agent state, preferences, interaction history, and credentials. * Supports **encrypted local storage** with optional hardware-backed security modules (TPM, Secure Enclave). * Preserves **session continuity**, ensuring that agents remember user context across browsing sessions or devices. 2. **Interface for Agent Communication** * Acts as the **dialogue hub** between users and their agents. * Supports multiple interaction modalities: text prompts, command inputs, contextual UI overlays, or visual diagrams (e.g., hover-based chart annotations). * Provides intuitive, **no-code interaction mechanisms**, enabling non-technical users to engage effectively with complex workflows. *** #### 3. Extended Capabilities * **Cross-Device Synchronization** * User preferences and agent states can be securely synced across devices using encrypted backup and restore flows. * A recovery mechanism ensures resilience in case of hardware loss. * **Identity and Access Management** * Users can manage multiple decentralized identities (DIDs, wallet addresses) directly within the extension. * Fine-grained access control allows users to set limits on what their agents can do (e.g., daily spending caps). * **Customizable UI Widgets** * Developers can design custom interfaces for specific workflows (e.g., password entry, data dashboards). * Supports modular UI components that agents can embed in user interactions. * **Offline Support** * Local caching allows agents to continue operating in a limited capacity when offline, syncing with the REVOX network once connectivity is restored. *** #### 4. Security and Privacy * **Local-first Design**: All sensitive data is stored and processed locally by default, reducing exposure to centralized servers. * **End-to-End Encryption**: Communications between the extension and REVOX agents use encrypted channels. * **Permission Scopes**: Agents request explicit approval for sensitive actions (e.g., signing transactions, accessing emails). * **Auditability**: All significant operations are logged, allowing users to review what their agents did on their behalf. *** #### 5. Application Scenarios * **DeFi User Interface** * A Web3 investor uses the extension to interact with a Compound Agent that monitors their portfolio, suggesting rebalancing strategies with one click. * **Research Assistance** * A researcher employs the extension to query academic datasets via Context Knowledge, visualizing results in an embedded chart widget. * **Compliance Automation** * An enterprise user integrates the extension with compliance workflows; agents automatically cross-check transactions against regulatory thresholds before approval. * **Productivity Agent** * A user connects Gmail and Calendar Plugins through the extension, enabling an agent to manage emails and schedule tasks directly within their browser. # Made by REVOX ### DPrompt DPrompt is the core component of REVOX onchain AI. The technical design is introduced here. We have built a frontend to showcase this solution at [dprompt.revox.ai](https://dprompt.revox.ai). ### REVOX Lense REVOX Lense () emerges as the first comprehensive application engineered atop the REVOX platform, setting a new standard for personalized asset management and information aggregation. This groundbreaking tool is designed to seamlessly integrate with users' wallets, automating the process of identifying assets and distilling the most insightful news, social media trends, and discussions relevant to those assets. By synthesizing this data, REVOX Lense crafts tailored reports and provides insightful answers to every question a user might have regarding their portfolio.Key Features of REVOX Lense: * Automatic Asset Identification: REVOX Lense expertly analyzes the contents of a user’s wallet, identifying assets with precision and understanding their significance within the broader market context. * Real-Time News and Social Media Aggregation: Leveraging the power of the REVOX platform, the application filters through vast amounts of information to highlight news and social trends directly impacting the user’s assets, ensuring that users stay informed about the latest developments. * Customized Reporting: Beyond mere data collection, REVOX Lense synthesizes information into comprehensive reports, offering users a holistic view of their assets’ performance, market sentiment, and potential future trends. * Interactive Q\&A: REVOX Lense is equipped to address users’ queries, providing expertly generated responses that help users make informed decisions about their digital asset portfolios. REVOX Lense is not just an application; it's a revolutionary tool that empowers users with actionable insights, personalized updates, and a deeper understanding of their investments in the dynamic landscape of digital assets. # DPrompt DPrompt ([revox.ai/dprompt](https://revox.ai/?dprompt)) is REVOX’s **on-chain AI inference layer**, designed to make advanced AI models natively accessible within smart contracts. It enables decentralized applications (dApps) to query machine learning models and receive **verifiable results** directly on-chain, without relying on centralized providers. By combining off-chain computation with cryptographic proofs, DPrompt bridges the gap between AI and Web3 in a trust-minimized way. Unlike traditional oracles that deliver only static data (e.g., price feeds), DPrompt delivers **dynamic, context-aware AI inferences**—allowing smart contracts to ask open-ended questions, perform classifications, or run predictive models, then act upon the results autonomously.
*** #### Product Experience The **DPrompt interface** reflects its goal of simplicity and accessibility, both for developers and end users. * **Model Selection:** Users can choose between different AI models (e.g., GPT) depending on their task requirements. * **Chain Integration:** DPrompt currently supports BNB Smart Chain and is designed for multi-chain expansion. * **Custom and Hot Prompts:** * *Custom Prompt* allows users to input free-form instructions for the AI model. * *Hot Prompts* provide pre-built templates for common tasks (e.g., risk checks, trading signals, classification). * **Result Verification:** The returned inference is displayed alongside a transaction hash, ensuring traceability and verifiability. * **Smart Contract Integration:** Each DPrompt instance is tied to a contract address, enabling dApps to reference it directly within workflows. This streamlined UI (see figure above) illustrates the workflow:\ **Users → AI Contract → AI Provider → Result (with Proofs).** *** #### Key Features | Feature | Description | | ------------------------ | ----------------------------------------------------------------------------------------------------------------- | | **On-Chain AI Requests** | Smart contracts submit inference requests directly, embedding AI reasoning into automated workflows. | | **Verifiable Outputs** | Results are accompanied by cryptographic proofs (zkML, stake-based consensus, or hybrid schemes). | | **Gas-Only Model** | Users only pay gas fees, lowering friction and removing hidden subscription models. | | **Multi-Model Support** | Compatible with large language models (LLMs), classification models, and prediction engines. | | **Composable Workflows** | DPrompt can be used as a node in REVOX workflows, combined with Primitive Agents, Plugins, and Context Knowledge. | *** #### Technical Architecture * **Request Layer:**\ Smart contracts encode prompts and send them to the DPrompt contract. * **Computation Layer (Off-Chain AI Providers):**\ Nodes execute AI inference off-chain to optimize cost and latency. * **Verification Layer:**\ Each inference is accompanied by: * **Proof-of-Stake Consensus:** Multiple providers must agree on results. * **Zero-Knowledge Proofs (zkML):** Where available, cryptographic guarantees prove that the model ran faithfully on given inputs. * **Delivery Layer:**\ Verified results are written back on-chain, available to dApps, agents, and workflows. *** #### Developer and User Value * **Developers** * Direct access to AI in smart contracts. * Ability to build autonomous agents and dApps without external trust assumptions. * Simple integration with SDKs and Studio for workflow design. * **Users** * Lower transaction complexity: only gas fees, no external API keys. * Transparency and immutability: every inference can be audited on-chain. * Confidence that AI outputs are verifiable and tamper-resistant. *** #### Future Roadmap * **Expanded Model Support:** Integrating multi-modal models (text, image, audio). * **Cross-Chain Availability:** Extend DPrompt beyond BNB Smart Chain into Ethereum, Arbitrum, and other L2s. * **User-Submitted Models:** Enable developers to deploy and monetize their own AI models in the DPrompt network. * **Workflow Integration:** Full compatibility with REVOX Studio for drag-and-drop inference nodes in workflow design. * **Performance Optimization:** Lower latency pipelines, batching requests, and improving zkML proving efficiency. # REVOX Studio REVOX Studio ([studio.revox.ai](https://studio.revox.ai/)) is the **low-code / no-code development environment** of the REVOX ecosystem. It serves as the central hub for building, testing, and deploying AI agents, workflows, and decentralized applications powered by oMCP. Studio makes it possible for both seasoned developers and non-technical users to participate in the creation of **AI-driven Web3 solutions**, bridging accessibility and sophistication. By combining a visual design interface, a plugin marketplace, and integrated deployment pipelines, Studio transforms the complexity of agent development into an **intuitive, modular process**. *** #### Product Experience & Interface * **Visual Workflow Builder**\ Users design agents and workflows through a drag-and-drop interface. Primitive Agents, Plugins, and Context Knowledge modules are represented as reusable blocks. Connecting them creates Compound Agents or complete workflows.
* **Template & Marketplace Access** * A curated library of templates offers ready-to-use agents and workflows for common use cases (DeFi arbitrage, DAO governance bots, compliance checks, e-commerce assistants, etc.). * Developers can publish their own agents or plugins into the marketplace, making them accessible to the community and monetizable through $REX incentives.
* **Integrated Testing & Simulation**\ Studio includes a sandbox environment where workflows can be simulated with sample data. Users see execution paths, debug agent behavior, and adjust configurations before deploying on-chain. * **Deployment Options**\ From Studio, workflows can be deployed directly into production: * On-chain execution (for verifiable workflows). * Off-chain execution anchored with proofs. * Hybrid models combining both. *** #### Key Features | Feature | Description | | ----------------------------- | ----------------------------------------------------------------------------------------------------- | | **Low-Code Workflow Builder** | Drag-and-drop interface to assemble agents, plugins, and data modules without writing extensive code. | | **Template & Module Library** | Pre-built solutions for popular use cases, customizable to fit specific user or enterprise needs. | | **Plugin Marketplace** | Developers can publish and monetize their plugins; users can discover and integrate them instantly. | | **Cross-Chain Deployment** | Agents can be deployed on multiple supported blockchains, maximizing reach and interoperability. | *** #### Technical Architecture * **Agent Composition Layer**\ Provides the interface for combining Primitive Agents, Plugins, and Context Knowledge into Compound Agents. * **Execution Engine**\ Handles workflow logic: sequencing, branching, parallel execution, retries. Compatible with both DSL scripts for developers and visual workflows for non-technical users. * **Plugin & Model Integration**\ Supports third-party APIs, DeFi protocols, and AI models, ensuring extensibility. Plugins are containerized to preserve modularity and security. * **Deployment Bridge**\ Links workflows to multiple execution environments: local, on-chain, or hybrid. Supports monitoring and telemetry post-deployment. *** #### Roadmap * **Expanded Template Library**: Pre-configured agents for specialized verticals (NFTs, GameFi, healthcare, supply chain). * **Collaborative Development**: Multi-user editing, team-based permissions, and shared workflow ownership. * **Custom Model Uploads**: Allow developers to integrate proprietary ML models into workflows. * **Advanced Visualization Tools**: Graph-based execution monitors and KPI dashboards. * **Studio-to-Marketplace Flow**: One-click publishing of workflows from Studio into the REVOX Marketplace. # Social Data Analysis of Real-time Cryptocurrency Price Fluctuations Building an automated trading bot based on social data analysis involves combining financial market data with information extracted from social media platforms to make trading decisions.REVOX is able to support building this bot with a few clicks. **Primitive Agent** * Ticker Price Agent for market price data * Wallet Agent for connecting users' wallets with authorization to perform trading on behalf of users with predefined rules * Twitter Agent/Facebook Agent and other social media agents related to information retrieval * Sentimental Analysis Agent to perform analysis on social data * Summarization LLM to perform final aggregation and analysis **Compound Workflow**
# An Intent-based Crypto Trading Bot from Users' Natural Language Prompt Crypto trading can be as straightforward as clicking a button, but at times, it can become intricate with tasks such as chain selection, gas collection, and trading fee comparison. To alleviate these complexities, an intent-based crypto trading bot that efficiently handles all these intricacies with a simple prompt, will streamline the process for users. **Primitive Agent** * Wallet Agent to connect users' wallets with authorization * Dex Agent can be implemented to connect Uniswap or any dex pool * Onramp Agent to solve onramp request if needed **Compound Workflow**
# Lense - Web3 GPT REVOX Lense ([lense.revox.ai](https://lense.revox.ai/)) is the **asset intelligence platform** of the REVOX ecosystem, designed as a “Web3-GPT” for digital assets. It continuously monitors user wallets across multiple chains, enriches raw blockchain data with market context, and delivers actionable insights through interactive, AI-powered reporting. Lense transforms fragmented on-chain and off-chain signals into **personalized, comprehensible narratives**—helping users and investors make more informed decisions.
*** #### Product Experience & Interface * **Wallet Integration**\ Users connect their Web3 wallets, and Lense automatically detects holdings across supported blockchains. It recognizes native tokens, LP tokens, bridged assets, and staking positions, providing a unified view of a fragmented portfolio. * **Dashboard & Reports**\ Once connected, Lense provides a dashboard displaying: * Portfolio distribution by chain and asset class. * Historical performance graphs and exposure metrics. * Sentiment and news signals relevant to the assets held. * Interactive prompts where users can ask asset-specific questions and receive contextual AI responses. ***
#### Key Features | Feature | Description | | ----------------------------------------- | ------------------------------------------------------------------------------------------------------------------------ | | **Automated Asset Identification** | Scans user wallets across chains, categorizes assets, and normalizes metadata for accurate portfolio tracking. | | **Real-Time News & Sentiment Monitoring** | Aggregates market news and social chatter relevant to portfolio tokens; surfaces early warnings and emerging narratives. | | **Interactive Q\&A** | Natural language queries transform into structured insight requests, answered by REVOX AI agents using contextual data. | | **Custom & Standard Reports** | Users can generate personalized portfolio reviews, risk assessments, and comparative analyses. | | **Cross-Chain Visibility** | Unified dashboard covering multiple L1s and L2s, enabling better understanding of multi-chain exposure. | | **Gas-Only Model** | No hidden fees—users consume credits and pay only blockchain gas, ensuring cost transparency. | *** #### Technical Architecture * **Data Pipeline**\ Lense aggregates data from multiple sources: on-chain wallet activity, token metadata, DeFi protocols, and external feeds such as news and social channels. * **AI Insight Layer**\ Using REVOX AI agents, Lense synthesizes raw data into insights. Context Knowledge modules ensure that asset analysis includes historical context (e.g., project roadmaps, governance history). * **Interactive Query Engine**\ User prompts are parsed by natural language models, mapped against available data, and answered through structured reasoning. This allows complex questions like: *“Which of my tokens has the highest correlation with ETH volatility?”* * **Scalability & Modularity**\ Lense is built as a composable module. Its asset scanning, sentiment aggregation, and report-generation components can also be reused within REVOX Studio workflows or integrated with SmartWallet actions. *** #### Use Cases 1. **Portfolio Sentiment Snapshot**\ A weekly report compares sentiment and social buzz with price volatility for each token in a user’s wallet, highlighting underperforming assets. 2. **Real-Time Alerts**\ When a token suddenly trends on social media, Lense detects the spike, contextualizes sentiment, and warns the user before markets react. 3. **Cross-Chain Risk Assessment**\ Lense identifies total value locked across different chains, calculates exposure ratios, and recommends adjustments to reduce bridge and liquidity risks. 4. **Investment Health Scoring**\ Each asset is scored on a composite index—performance history, volatility, developer activity, sentiment—so users can rank tokens by relative strength. *** #### User Value * **For Casual Users**: Simplifies asset tracking by unifying fragmented portfolios into a single dashboard. * **For Active Traders**: Surfaces early market signals and narrative shifts, improving reaction times. * **For DAOs & Institutions**: Provides automated reports and health assessments for treasury holdings. *** #### Roadmap * **More Asset Types**: Extending coverage to NFTs, derivatives, and complex DeFi instruments. * **Deeper Analytics**: Incorporating advanced forecasting models, cross-asset correlation maps, and predictive scoring. * **Custom Templates**: Users and organizations will be able to design and share reporting frameworks. * **Actionable Integration**: Seamless connection with SmartWallet, allowing users to act directly on Lense insights (e.g., rebalance, swap, exit). * **Visualization Enhancements**: Interactive dashboards, comparative charts, and multi-dimensional trend analysis. # SmartWallet - Redefine DeFi with AI SmartWallet ([smartwallet.revox.ai](http://smartwallet.revox.ai/)) is REVOX’s **AI-powered, self-custodial wallet**, designed to make interacting with DeFi protocols as intuitive as chatting with an assistant. Instead of manually navigating complex interfaces, comparing pools, or building transactions, users can simply **express their intent in natural language**. SmartWallet then parses, optimizes, and executes actions across multiple protocols and chains. It redefines the wallet from being a **passive storage tool** into an **active decision-making and automation layer**, putting AI agents at the heart of Web3 asset management. {% embed url="" %} *** #### Product Experience & Interface * **Natural Language Commands**\ Users can type or speak simple instructions such as: * “Swap 50 USDC for ETH at the lowest fee.” * “Bridge my BNB to Arbitrum with the safest path.” * “Find the highest-yield USDT pool available and deposit half my balance.” * **Cross-Chain & Cross-Protocol Access**\ SmartWallet connects to a wide range of DEXs, lending protocols, staking pools, and bridges. It automatically identifies the best available routes while balancing safety, speed, and gas cost. * **Transparent Execution**\ Before execution, SmartWallet provides a preview of the transaction: estimated gas fees, slippage risk, and protocol selection. Users confirm before signing. * **Unified Dashboard**\ Beyond transactions, SmartWallet offers a portfolio view across multiple chains, with balances, pending rewards, and yield analytics. *** #### Key Features | Feature | Description | | ---------------------------------- | -------------------------------------------------------------------------------------------------------------------------------- | | **AI Command Parsing** | Natural language inputs are translated into structured smart contract calls using REVOX agents and workflows. | | **Path Optimization** | SmartWallet selects the most cost-efficient and secure routes across DEXs and bridges, using real-time price and liquidity data. | | **Cross-Chain Bridge Integration** | Supports multi-bridge routing, with fallbacks in case of congestion or failures. | | **Multi-Protocol DeFi Support** | Enables swaps, staking, lending, borrowing, yield farming, and liquidity provisioning across ecosystems. | | **Security First** | Users retain full custody; all approvals and signatures happen locally. No third-party custody is required. | | **Composability** | Can be used inside broader workflows: e.g., triggered by Lense insights or part of a Compound Agent automation. | *** #### Technical Architecture * **Agent-Driven Parser**\ Natural language instructions are handled by REVOX AI agents, which translate them into parameterized calls to DeFi protocols. * **Integration Layer**\ Plugins connect to DEXs, AMMs, lending pools, and bridges. This ensures wide coverage and up-to-date execution. * **Optimization Engine**\ Evaluates gas fees, slippage, and liquidity to choose the best trade path. Includes simulation and dry-run execution before user confirmation. * **Self-Custody Execution**\ Private keys never leave the user’s device. Transactions are signed locally and broadcast only after explicit confirmation. *** #### Use Cases 1. **Simple Swap**\ A user asks: “Swap 100 DAI to USDT.” SmartWallet fetches live quotes from multiple DEXs, selects the best path, and executes in one click. 2. **Yield Farming Automation**\ The wallet identifies that a stablecoin pool offers 12% APY. User commands: “Stake half my USDC here.” SmartWallet handles token approvals, deposits, and confirms reward tracking. 3. **Cross-Chain Arbitrage Execution**\ Traders can instruct SmartWallet to bridge funds and execute multi-leg swaps automatically, with real-time price monitoring. 4. **Portfolio Rebalancing**\ User says: “Keep my ETH exposure at 50% of portfolio.” SmartWallet monitors balance changes and executes rebalancing trades when deviation exceeds threshold. *** #### Roadmap * **Broader Protocol Coverage**: Expand to include derivatives, perpetuals, options protocols. * **Strategy Templates**: Users save and reuse automated trading or yield strategies. * **Integration with Lense**: Insights from Lense trigger wallet actions (e.g., exit risky tokens, reallocate into trending assets). * **Social & DAO Features**: Allow strategy sharing, DAO treasury execution, or collaborative multi-sig workflows. * **Mobile App Release**: Extend SmartWallet into mobile-first experience with biometric security. # DEVA - Virtual Avatars Studio DEVA ([deva.revox.ai](https://deva.revox.ai/)) is the **virtual avatar studio** of the REVOX ecosystem, designed to empower users to create and animate **AI-driven digital identities**. It combines cutting-edge generative AI with intuitive creation tools, enabling anyone to design lifelike avatars that can speak, perform, and generate multimedia content. Unlike static profile images, DEVA avatars are **dynamic, customizable, and interactive**. They can serve as personal companions, brand ambassadors, content creators, or in-game characters. DEVA brings creativity, entertainment, and identity expression into the REVOX ecosystem, linking digital identity with blockchain ownership and monetization. *** #### Product Experience & Interface * **Avatar Creation**\ Users start by uploading an image or selecting from templates. DEVA processes the input and generates a base avatar, which can be styled across multiple aesthetics—realistic, anime-inspired, stylized, or branded.
* **Voice & Script Integration**\ Users can type scripts or record their own voice. DEVA synthesizes the content into spoken dialogue or video, matching lip-sync and expression to the avatar. * **Customization Options** * Hairstyles, clothing, and accessories. * Personality traits and speaking style. * Background settings for video generation. * **Content Publishing**\ Created avatars and videos can be saved locally, shared on social platforms, or published within the REVOX ecosystem. Avatars can also be minted as NFTs, linking creative output to verifiable ownership.
*** #### Key Features | Feature | Description | | --------------------------- | --------------------------------------------------------------------------------------------- | | **Avatar Generator** | Upload an image or use templates to create fully animated digital personas. | | **Voice & Video Synthesis** | Input scripts are turned into realistic voice output and synchronized video clips. | | **Style Library** | Choose from different artistic or realistic styles for avatars, adaptable across scenarios. | | **Private & Public Modes** | Keep avatars for personal use or publish them to the community gallery. | | **NFT Integration** | Mint avatars or their generated content as NFTs, enabling trading and monetization. | | **Credit System** | Avatar generation and video rendering consume credits, providing predictable usage economics. | *** #### Technical Architecture * **Generative AI Pipeline**\ Combines image-to-avatar, text-to-speech, and video synthesis models in a seamless workflow. * **Modular Rendering**\ Rendering tasks are split into stages (image, audio, video), allowing customization at each stage and efficient use of compute resources. * **Wallet Integration**\ Each avatar is linked to a user’s wallet, ensuring ownership is verifiable. Publishing or minting actions require on-chain confirmation. * **Composability with REVOX Ecosystem**\ DEVA avatars can be embedded into workflows in Studio, used in SmartWallet interactions as assistants, or integrated with Lense to create personalized reporting agents. *** #### Use Cases 1. **Personal Expression**\ A user creates a custom avatar styled as an anime character and generates daily vlogs for their community. 2. **Brand Marketing**\ A company builds branded avatars that deliver promotional content in multiple languages, personalized for different markets. 3. **Entertainment & Gaming**\ Game developers integrate DEVA avatars as NPCs or player companions, generating in-game dialogue and interactive storylines. 4. **Education & Training**\ Educators create avatars that deliver lessons in an engaging, multimedia format—complete with voice, gesture, and visual aids. 5. **Social Media & Web3 Communities**\ Influencers and creators use DEVA avatars to represent themselves in metaverse events or DAO governance discussions. *** #### User Value * **For Individuals**: Lowers the barrier to high-quality content creation, making avatars accessible without technical expertise. * **For Creators**: Enables new monetization models through avatar NFTs, sponsored content, or unique digital personas. * **For Enterprises**: Provides scalable, cost-effective avatar-based communication and brand presence. *** #### Roadmap * **Expanded Style Options**: Adding more avatar aesthetics, from ultra-realistic to stylized 3D. * **Real-Time Interactivity**: Live avatars capable of streaming or responding in real time. * **Marketplace Integration**: Community-driven marketplace for avatar assets, scripts, and voices. * **Multi-Language Support**: Enhanced text-to-speech and lip-sync across global languages. * **Wearables & Interoperability**: Support for wearable NFTs and cross-platform avatar use (metaverse, games, VR). # Ecosystem ## Ecosystem
Beyond its core products, REVOX is building a broad ecosystem of partnerships that extend across the major verticals of Web3 and AI. In social and gaming, collaborations focus on embedding intelligent agents into interactive environments, enabling richer engagement and new models of digital communities. In DeFi, DePIN, and decentralized AI, REVOX works with infrastructure and protocol partners to bring verifiable intelligence into financial systems, scaling liquidity, compliance, and predictive capabilities. On the infrastructure side, the ecosystem integrates with wallets, layer-1 and layer-2 chains, and developer frameworks, ensuring that REVOX agents are **chain-agnostic, accessible, and interoperable** across multiple environments. This breadth of collaboration reflects REVOX’s philosophy: to serve as the **intelligence layer across all verticals**, rather than compete within a single niche. By aligning with partners in infrastructure, DeFi, social, and AI-native domains, REVOX strengthens both resilience and reach. The advantage lies in composability—agents and workflows designed in REVOX Studio, powered by DPrompt, can operate seamlessly across partner networks, benefiting from liquidity, data, and user bases that span ecosystems. The result is a **synergistic network effect**: REVOX contributes intelligence and verifiability, while partners provide domain-specific depth and scale. Together, this ensures that the REVOX ecosystem is not just a suite of products, but a **platform for cross-sector innovation**, accelerating the convergence of AI and Web3. *** ## Products Developed by REVOX [**DPrompt**](/products/dprompt)\ DPrompt is the on-chain inference oracle that anchors REVOX’s AI infrastructure. It allows smart contracts to directly call AI models and obtain verifiable results, turning blockchain from a rule-execution system into an intelligence-enabled environment. Developers can integrate model outputs into financial logic, governance mechanisms, or predictive markets without relying on centralized intermediaries. By ensuring that AI inferences are both verifiable and composable, DPrompt becomes the trusted bridge between off-chain computation and on-chain decision making. [**Studio**](/products/revox-studio)\ Studio is the creative hub where developers and users build, test, and deploy agents. It offers a visual, low-code environment that lowers the barrier for experimentation while still giving professionals the control they need. With its drag-and-drop workflow builder, plugin marketplace, and integrated testing sandbox, Studio makes composability tangible: agents, plugins, and knowledge modules can be assembled into sophisticated applications within minutes. Studio accelerates the evolution of the ecosystem, enabling rapid prototyping, iteration, and deployment of AI-driven Web3 solutions. [**Lense**](/products/lense-web3-gpt)\ Lense acts as the intelligence layer for Web3 asset management. By scanning wallets across chains, it aggregates token holdings, liquidity positions, and staking balances, then enriches this raw data with real-time sentiment and news monitoring. The result is a personalized insight engine that allows users to understand not just “what they hold,” but also “what drives value and risk.” Interactive Q\&A and report generation turn complex blockchain signals into accessible narratives, enabling users to stay ahead of trends, evaluate risks, and manage cross-chain portfolios with clarity. [**SmartWallet**](/products/smartwallet-redefine-defi-with-ai)\ SmartWallet transforms the idea of a crypto wallet from a passive key manager into an active assistant. Users interact with DeFi protocols through natural language, asking the wallet to swap tokens, bridge funds, or optimize yield strategies. The AI agent parses intent, selects the best routes across chains and protocols, and prepares secure, transparent transactions for confirmation. This makes complex actions like portfolio rebalancing or multi-step yield farming as simple as issuing a request, democratizing access to sophisticated DeFi strategies. [**DEVA**](/products/deva-virtual-avatars-studio)\ DEVA expands REVOX into the cultural and creative dimension by giving users the power to design intelligent avatars. Through generative AI, users can create lifelike or stylized digital identities that speak, move, and produce multimedia content. These avatars can serve as companions, creators, educators, or brand ambassadors, and can be published or minted as NFTs to establish verifiable ownership. DEVA highlights how REVOX’s agentic infrastructure extends beyond finance and automation into the realm of identity, entertainment, and community expression, enriching the social fabric of Web3. # Roadmap 2023.9: REVOX testnet (achieved) 2023.10: ReadON DAO app reached 1M downloads (achieved) 2024.02: Decentralized Inference Engine: DPrompt Launched (achieved) 2024.03: REVOX Lense Launched (achieved) 2024.07: REVOX Lense reached 10M users (achieved) 2024.11: REVOX Studio (achieved) 2025.Q1: REVOX Chain Mainnet 2025.Q1: REVOX AI MEME Token Tools 2025.Q2: REVOX Agent Launchpad # Tokenomics old version ### Basic Information: $REX • Total Supply: 3B Smart Contract Address: ### $REX and $sREX $REX is the main governance token of REVOX, while $sREX is a special staking token. $REX can be converted into $sREX at a 1:1 ratio without restrictions. However, $sREX is non-tradable and can only be converted back to $REX using specific redemption durations. ### Token Burn and $sREX Staking Pool Early redemption of $sREX before the unlock period will result in a deduction of $sREX: • 50% of the deducted $sREX is permanently burned from circulation. • 50% of the deducted $sREX is allocated to the sREX Staking Pool, increasing rewards for long-term holders.
### Design Principles 1\. Delayed Staking Inflation Inflation from staking rewards is limited to $sREX and dynamically delayed before reflecting in tradable $REX. 2\. Mitigating Paper Hands’ Impact on Inflation Paper hands opting for shorter durations incur higher deduction rates, significantly alleviating inflation pressure on $REX. This design rewards long-term holders with higher yields. 3\. Dynamic Balance Between Paper Hands and Diamond Hands The staking pool benefits from high deductions in short-duration redemptions, rewarding diamond hands with higher staking interest and incentivizing long-term holding. 4\. Long-Term Deflation With 50% of deducted tokens burned, $REX is designed to be deflationary, enhancing long-term holder returns. ### $REX Utility and Purpose 1\. Payment for AI Credits REX can be used to pay for AI credits in REVOX’s proprietary products (e.g., Lense, SmartWallet, Studio, Agent Marketplace) and third-party AI products supporting REVOX AI Payment. Users paying with REX will enjoy lower rates based on its dynamic price. 2\. Conversion to $sREX for Ecosystem Rewards REX can be converted into sREX to participate in REVOX ecosystem benefits. ### $sREX Utility and Purpose 1\. Stake-to-AI $sREX holders receive daily AI credits proportional to their holdings, usable in REVOX’s AI products and partner ecosystems. 2\. Participation in Staking Pools sREX holders can join staking pools for additional rewards. During the first 180 days after the TGE, staking pools are funded by REVOX Foundation directly. After 180 days, staking pools will consist of Foundation rewards and deducted tokens from short-cycle redemptions. 3\. Claim Future Tokens built on REVOX platform For all projects built on REVOX Studio or distributed on REVOX marketplace, sREX holders will have the chance to claim airdrop tokens from them based on their participation and sREX amount. ### Token Global Allocation
CategoryDistributionVesting
Community - Airdrop10%Unlock at TGE
Community - Staking & Future Incentives50%6-month cliff with 48-month vesting*
Liquidity + Marketing5%Unlock at TGE
Team & Advisor15%6-month cliff with linear 48-month vesting
Investor20%6-month cliff with linear 24-month vesting
\*The unlock schedule for Community is an estimated value. In practice, a large portion of tokens distributed to the community will be in $sREX and tradable converted REX will be smaller. The deflationary aspect of $REX is not reflected in the chart above. # Tokenomics Basic Information: $REX • Total Supply: 3B Smart Contract Address: ### $REX and $sREX $REX is the main governance token of REVOX, while $sREX is a special staking token. $REX can be converted into $sREX at a 1:1 ratio without restrictions. However, $sREX is non-tradable and can only be converted back to $REX using specific redemption durations. ### Token Burn and $sREX Staking Pool Early redemption of $sREX before the unlock period will result in a deduction of $sREX: • 50% of the deducted $sREX is permanently burned from circulation. • 50% of the deducted $sREX is allocated to the sREX Staking Pool, increasing rewards for long-term holders.
### Design Principles 1\. Delayed Staking Inflation Inflation from staking rewards is limited to $sREX and dynamically delayed before reflecting in tradable $REX. 2\. Mitigating Short-term traders’ Impact on Inflation Short-term traders opting for shorter durations incur higher deduction rates, significantly alleviating inflation pressure on $REX. This design rewards long-term holders with higher yields. 3\. Dynamic Balance Between Short-term traders and Diamond Hands The staking pool benefits from high deductions in short-duration redemptions, rewarding diamond hands with higher staking interest and incentivizing long-term holding. 4\. Long-Term Deflation With 50% of deducted tokens burned, $REX is designed to be deflationary, enhancing long-term holder returns. ### $REX Utility and Purpose 1\. Payment for AI Credits REX can be used to pay for AI credits in REVOX’s proprietary products (e.g., Lense, SmartWallet, Studio, Agent Marketplace) and third-party AI products supporting REVOX AI Payment. Users paying with REX will enjoy lower rates based on its dynamic price. 2\. Conversion to $sREX for Ecosystem Rewards REX can be converted into sREX to participate in REVOX ecosystem benefits. ### $sREX Utility and Purpose 1\. Stake-to-AI $sREX holders receive daily AI credits proportional to their holdings, usable in REVOX’s AI products and partner ecosystems. 2\. Participation in Staking Pools sREX holders can join staking pools for additional rewards. During the first 180 days after the TGE, staking pools are funded by REVOX Foundation directly. After 180 days, staking pools will consist of Foundation rewards and deducted tokens from short-cycle redemptions. 3\. Claim Future Tokens built on REVOX platform For all projects built on REVOX Studio or distributed on REVOX marketplace, sREX holders will have the chance to claim airdrop tokens from them based on their participation and sREX amount. ### Token Global Allocation
CategoryDistributionVesting
Community - Airdrop10%Unlock at TGE
Community - Ecosystem Incentives35%The Incentive Pool will be formed using sREX at TGE*
Community - sREX Staking Pool15%The Staking Pool will be formed using sREX at TGE*
Liquidity + Marketing5%Unlock at TGE
Team & Advisor15%6-month cliff with linear 48-month vesting
Investor20%6-month cliff with linear 24-month vesting

REVOX Circulation Supply

\*The unlock schedule for Community is an estimated value. In practice, a large portion of tokens distributed to the community will be in $sREX and tradable converted REX will be smaller. The deflationary aspect of $REX is not reflected in the chart above. # Tokenomics V2 V2 ### Basic Information: $REX • Total Supply: 3B Smart Contract Address: ### $REX and $sREX $REX is the main governance token of REVOX, while $sREX is a special staking token. $REX can be converted into $sREX at a 1:1 ratio without restrictions. However, $sREX is non-tradable and can only be converted back to $REX using specific redemption durations. ### Token Burn and $sREX Staking Pool Early redemption of $sREX before the unlock period will result in a deduction of $sREX: • 50% of the deducted $sREX is permanently burned from circulation. • 50% of the deducted $sREX is allocated to the sREX Staking Pool, increasing rewards for long-term holders.
### Design Principles 1\. Delayed Staking Inflation Inflation from staking rewards is limited to $sREX and dynamically delayed before reflecting in tradable $REX. 2\. Mitigating Short-term traders’ Impact on Inflation Short-term traders opting for shorter durations incur higher deduction rates, significantly alleviating inflation pressure on $REX. This design rewards long-term holders with higher yields. 3\. Dynamic Balance Between Short-term traders and Diamond Hands The staking pool benefits from high deductions in short-duration redemptions, rewarding diamond hands with higher staking interest and incentivizing long-term holding. 4\. Long-Term Deflation With 50% of deducted tokens burned, $REX is designed to be deflationary, enhancing long-term holder returns. ### $REX Utility and Purpose 1\. Payment for AI Credits REX can be used to pay for AI credits in REVOX’s proprietary products (e.g., Lense, SmartWallet, Studio, Agent Marketplace) and third-party AI products supporting REVOX AI Payment. Users paying with REX will enjoy lower rates based on its dynamic price. 2\. Conversion to $sREX for Ecosystem Rewards REX can be converted into sREX to participate in REVOX ecosystem benefits. ### $sREX Utility and Purpose 1\. Stake-to-AI $sREX holders receive daily AI credits proportional to their holdings, usable in REVOX’s AI products and partner ecosystems. 2\. Participation in Staking Pools sREX holders can join staking pools for additional rewards. During the first 180 days after the TGE, staking pools are funded by REVOX Foundation directly. After 180 days, staking pools will consist of Foundation rewards and deducted tokens from short-cycle redemptions. 3\. Claim Future Tokens built on REVOX platform For all projects built on REVOX Studio or distributed on REVOX marketplace, sREX holders will have the chance to claim airdrop tokens from them based on their participation and sREX amount. ### Token Global Allocation
CategoryDistributionVesting
Community - Airdrop10%Unlock at TGE
Community - Future Incentives35%6-month cliff with 48-month vesting*
Community - sREX Staking Pool15%The Staking Pool will be formed using sREX at TGE*
Liquidity + Marketing5%Unlock at TGE
Team & Advisor15%6-month cliff with linear 48-month vesting
Investor20%6-month cliff with linear 24-month vesting
\*The unlock schedule for Community is an estimated value. In practice, a large portion of tokens distributed to the community will be in $sREX and tradable converted REX will be smaller. The deflationary aspect of $REX is not reflected in the chart above.