Othentic
  • Introduction
    • Introducing Othentic Stack
    • Use Cases
  • AVS Framework
    • Abstract
    • Quick Start
    • Othentic CLI
      • Key Management
      • Contracts Deployment
      • Operator Registration
      • AVS Logic Implementation
      • Operator Deposit
      • Node Operators
      • Rewards Distribution
      • P2P Config
        • Custom P2P Messaging
        • P2P Auth Layer
        • Metrics and Monitoring
        • Logging
        • Persistent storage
        • Latency
      • CLI Command Reference
    • Smart Contracts
      • AVS Governance
      • Attestation Center
      • Hooks
        • Task Logic
        • Operator Management
        • Rewards Fee Calculator
      • OBLS
      • Othentic Registry
      • Message Handlers
    • Othentic Consensus
      • Abstract
      • Task & Task Definitions
      • Leader Election
      • Proof of Task
      • Execution Service
      • Validation Service
      • Voting Power
      • Rewards and Penalties
      • Internal Tasks
    • FAQ
    • Supported Networks
    • Explainers
      • Networking
      • Multichain
      • Production Guidelines
      • Operator Allowlisting
      • Governance Multisig
  • External
    • AVS Examples
  • GitHub
  • Othentic Hub
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  1. Introduction

Use Cases

PreviousIntroducing Othentic StackNextAbstract

Last updated 3 months ago

One of the primary goals of Othentic is to support specialized node tasks to enable AVSโ€™s Operators to submit unique task specifications.

Node clients can retrieve information from API, run complex ML computations, analyze transactions to prevent exploits and initiate circuit breaks, run general computations for other applications, automate on-chain and off-chain workflows, relay encrypted messages, index and query databases, propagate decentralized RPC, or run verifiable computation provers.

Here's a list of potential use cases that you can build using the Othentic Stack (updating):

Agent Authorization Network ๐Ÿšฆ

Level: Medium Effort Category: AI Agents, Infrastructure Skillset: Backend Development, Cryptography What A decentralized AI agent authentication and action-verification system that ensures safe asset delegation to agents.

Why Centralized authentication systems lack flexible and agent friendly interfaces, additionally agents often hallucinate. Thus for secure high risk actions users need an environment that enables programmable delegation, self-enforcemeable & verifiable interactions and interoperable financial rails to function effectively.

How The network consists of three main components, MPC layer, which fragments user keys across nodes for secure delegation. The Policy Box, that ensures agent actions comply with predefined rules, and on-chain contracts that provide accountability by rewarding honest nodes and penalizing malicious behavior. AVS operators collaboratively compute and verify agent credentials and actions using MPC in a TEE environment. Outputs are attested using the AVS consensus mechanism, making sure only desired actions get executed. Teams can leverage this to get started with building their Agent Authorization AVS.

Verifiable Inference for Agents ๐Ÿ’พ

Level: Medium Effort Category: AI Agents, Infrastructure Skillset: Backend Development, Cryptography What Enable agents to produce outputs that are cryptographically verified to originate from a specified model and input prompt.

Why By default, agents rely on third-party inferences, existing methods that struggle to verify inference integrity, especially with protected APIs requiring credentials. This introduces risks of manipulated outputs or human intervention, which compromises trust. Verifiable inference guarantees reliability for high-stakes applications like finance and healthcare.

How AVS uses zkTLS within a multi-party computation (MPC) framework to verify API outputs without exposing sensitive credentials. MPC-TLS generates cryptographic proof that an agentโ€™s request to a protected API is valid, authenticated, and originates from a trusted source. This proof is passed to the user, ensuring the integrity of the agentโ€™s action while maintaining privacy. Teams can leverage this to get started with building their Verifiable Inference AVS.

Agent Task Validation โœ…

Level: Medium Effort Category: AI Agents, Infrastructure Skillset: Backend Development, Cryptography What Provide cryptographic proofs for tasks completed by agents, facilitating verifiable evidence of agent actions in real-world systems.

Why This ensures accountability and transparency, mitigating the risks of errors or manipulation in AI Agent task execution and allowing users to verify tasks such as asset staking, cross-chain transfers, inference posts on Twitter, voting in a DAO proposal, and more.

How AI agent submits proof of task execution to the network operators. The operators individually verify the proof against pre-defined conditions and attest to its validity. The resultant attestations are aggregated, and results are subsequently logged on-chain for verifiable records. Teams can leverage this to get started with building their Agent Task Validation AVS.

Agent Oracle

Level: Medium Effort Category: AI Agents, Infrastructure Skillset: Backend Development, Cryptography

What An Agent Oracle AVS where AI agents fetch external data (e.g., price feeds) and submit it onchain with cryptographic verification of authenticity and origin.

Why Traditional oracles rely on trust assumptions and lack verifiable execution. For high-stakes DeFi protocols, trust-minimized data submission is critical to avoid manipulation or incorrect feeds impacting collateral, trades, or governance.

How AI agents fetch data from authenticated APIs (e.g., Binance), use zkTLS to generate verifiable proofs, and submit them to AVS attester nodes. The AVS network validates the agent's task and confirms the data was fetched from the intended source, ensuring trustless integrity. Teams can leverage this to get started with building their Agent Oracle AVS.

Keeper Network ๐Ÿ’‚โ€โ™€๏ธ

Level: Medium Effort Category: DeFi, Infrastructure Skillset: Backend Development, Smart Contract Development What Build Keeper Network to maintain the liveliness and healthiness of DeFi protocols. Why Keepers play a crucial role in maintaining the health of DeFi protocols by acting as incentivized parties who take advantage of arbitrage opportunities to boost the overall health of the protocol. How Nodes in the network track collateralized positions, detect the Loan-to-Value ratio of a lending position, and automatically trigger liquidations when thresholds are breached.

Intent Solver ๐Ÿ”

Level: High Effort Category: DeFi, Consumer Skillset: Backend Development,Smart Contract Development,Web Scraping,Optimization, AI/ML What Build Intent Solvers Network to execute workflows under pre-defined conditions and improve end-user experience. Why "Simple" txs are limited in functionalities. Intents are the next step to improving the user experience of blockchain applications. How This architecture can be built as an AVS using Othentic. End-users submit a policy of conditions to trigger on-chain actions based on pre-defined logic. Task Performers discover intents, analyze several routes to execute them, and propose the best one. Attestations verify whether that is the most optimal and correct route and approve the process. Solvers that are inactive or attest malicious routes can get slashed to provide economic security to the user.

Reputation System ๐Ÿชช

Level: Low Effort Category: Consumer Skillset: Backend Development Web Scraping What Decentralized reputation system for Twitter accounts and wallets. Why (1) Billion of dollars lost in the past years due to crypto frauds. (2) Crypto Twitter (CT) signal-to-noise ratio is terrible. From scam links and grifters, inauthentic followers count and bots, to spurious project support. How Build a network with Othentic Stack, where Performers fetch user data from Twitter and on-chain interactions to develop a decentralized credibility system. The credibility score can be used to rank accounts in specific fields, spotlight malicious users, and/or distribute rewards to active community members.

Training AI/ML Models ๐Ÿค–
User-faced Liquidation Detectors ๐Ÿšจ

Level: Medium Effort Category: DeFi, Consumer Skillset: Backend Development, Smart Contract Development What Decentralized safeguard network for end-users. Why DeFi has unlocked unprecedented financial innovation, allowing users to borrow, lend, and trade assets in a decentralized manner. However, the backbone of these services is the ability to manage and liquidate collateralized positions to maintain system stability. How Build a decentralized network of nodes to monitor individual wallet health factors, exit and rebalance the user's positions before liquidation events. Performers are authorized to execute certain on-chain actions when thresholds are breached to safeguard end-users capital.

Data Availability Sampling ๐Ÿงช

Level: High Effort Category: Skillset: Backend Development,Computer Networking What Build data availability sampling (DAS) network to allow light nodes to verify availability across multiple providers without downloading all block data.

Why Light nodes can validate data without resource-intensive requirements, ensuring efficient and scalable data availability infrastructure across providers.

How Light nodes conduct multiple rounds of random sampling for small portions of block data. Task performers sample the data, which is then verified by attesters, ensuring a network of light nodes consistently checks availability.

Prediction Markets ๐Ÿ”ฎ

Level: High Effort Category: Consumer,Infrastructure Skillset: Backend Development,Smart Contract Development,Frontend Development. What Build decentralized prediction market system that integrates off-chain and on-chain deterministic data, like the price of ETH at a certain point in time, a project FDV 24 hours after launch, and Amazon revenues forecast for Q4, while ensuring transparency and accuracy of data.

Why A credibly neutral network of nodes comes to a consensus on events

How Operators match and order user trades, submitting them to the underlying AVS network for execution. Simultaneously, they act as oracles, fetching and providing deterministic on-chain and off-chain data.

Access Gating Systems ๐Ÿšช

Level: Low Effort Category: Consumer,Dev Tooling Skillset: Backend Development

What Build a developer-first access control system.

Why To simplify the implementation of complex and nuanced access control for protocols, maintaining trustlessness and verifiability.

How Developers specify complex-attestation based conditions to gate features in their protocols. Users who have certain tokens, have made certain contributions, or are whitelisted on other protocols, can unlock special features and access. Performers monitor data sources, and once conditions are met, the user is authorized to act.

GPU Cluster ๐Ÿ›œ

Level: Medium Effort Category: AI, Infrastructure Skillset: Backend Development What Decentralize GPU clusters to enable anyone to contribute GPUs for computational tasks.

Why Training machine learning models demands high computational power, which centralized systems often monopolize, limiting accessibility and driving up costs. A decentralized setup allows for scalable, efficient, and accessible machine learning model training.

How Using AVS-based networks, contributors can share GPU power securely while task performers distribute workloads. Attestators ensure computation integrity, and participants are rewarded based on contributions.

Dynamic NFTs ๐ŸŽฎ

Level: Medium Effort Category: Gaming, Consumer Skillset: Smart Contract Development,Backend Development What Build a decentralized metadata infrastructure for digital assets. Why NFTs are not just an artform that you can collect, there can also be utility tokens for access to special features, reflect in-game player progress, and much more. The primitive extends the use cases and implementations of web3, ranging from gaming to art, reputation, and decentralized socials. How Create a network for changing metadata and graphics based on on-chain or off-chain conditions. Using Othentic, modify the assets and information in an NFTs based on certain triggers monitored by the task performers.

The network efficiently evaluates and validates complex data streams from off-chain and on-chain data sources, and updates the metadata state.

Bonus: Developers can utilize an application layer and developer-friendly tools to intuitively interact with the underlying infrastructure, manage metadata, and instruct the network to mutate the state of the metadata by applying a set of pre-defined conditions to data flows.

Decentralized Points System ๐Ÿ’ฏ

Level: Medium Effort Category: DeFi, Infrastructure Skillset: Backend Development, Smart Contract Development, Web Scraping What A decentralized points system for rewarding user contributions in an ecosystem.

Why To fairly distribute rewards based on diverse types of contributions that are often difficult to track in a decentralized manner.

How Using the Othentic Stack, task performers gather social media, GitHub, and on-chain DeFi data to calculate an inclusive and robust point system for users.

Composable Data ๐Ÿ’ฝ

Level: Medium Effort Category: Consumer, Infrastructure Skillset: Backend Development, Smart Contract Development, Web Scraping

What Build oracles that provide secure and composable data for blockchain applications.

Why To enable smart contracts to access real-time off-chain data and update the state of on-chain assets.

How Nodes gather data from diverse off-chain sources, which is then made available to smart contracts for seamless integration.

Tokenized Assets ๐Ÿ’น

Level:Low Effort Category: Consumer, DeFi Skillset: Backend Development What Build a system for tokenizing traditional assets like stocks and bonds.

Why To enable users to diversify their portfolios and invest in traditional assets without barriers, ensuring a decentralized and trustless process.

How Nodes fetch price information for stocks and bonds, allowing the AVS to create tokens pegged to these assets. Users can purchase these tokens and earn profits as the underlying assets perform well.

AVS Slashing Insuarance ๐Ÿ’ผ

Level: Low Effort Category: DeFi, Infrastructure Skillset: Backend Development What Create a decentralized slashing insurance system for operators in the shared security era.

Why To avoid error-prone disputes and punish dishonest actors only.

How Operators can get insurance from an AVS built with the Othentic Stack where performers can conclude whether a slashing insurance claim must be distributed or not.

Random Number Generator ๐ŸŽฒ

Level: Low Effort Category: Dev Tooling Skillset: Backend Development What Build a cryptographically secure random number generator.

Why Provide a trustworthy source of randomness for applications and ZK projects, ensuring fairness and security.

How Task performers generate a random number. Attestators add a random salt and sign the task to obtain a random aggregated BLS signature, which can be destroyed after use to provide cryptographic guarantees for the protocol.

Blockchain Data Indexing ๐Ÿ“‘

Level: Medium Effort Category: Data Analysis, Infrastructure Skillset: Backend Development What Custom data indexers for accessing blockchain data easily.

Why To simplify fetching specific on-chain data and improve the developer experience by providing indexed data.

How With the Othentic Stack, task performers extract blockchain data and store it in IPFS using a custom format. Users can then query the indexed data via GraphQL.

Watcher Networks ๐Ÿ•ต๏ธ

Level: Medium Effort Category: Skillset: Backend Development What A watcher network to validate Layer 2 transactions and submit fraud proofs.

Why To ensure transaction validity in optimistic rollups and modular networks where submitting fraud proofs may not be guaranteed.

How Watcher networks can be built with Othentic Stack as an AVS where task performers validate L2 transactions and submit fraud proofs whenever necessary.

AI Inference ๐Ÿ“ก

Level: High Effort Category: Consumer, AI/ML Skillset: Backend Development,Cryptography,AI/ML What A secure network for AI inference that ensures data privacy.

Why To provide a decentralized solution for running AI models without compromising user data privacy.

How Using the Othentic Stack, a network of operators can perform data inference in an encrypted manner with techniques like FHE or zkML to maintain privacy.

Threat Detection Network ๐Ÿšจ

Level: High Effort Category: AI/ML, ,Security Skillset: Backend Development,Computer Networking,AI/ML What A hack detection system for monitoring blockchain transactions.

Why To swiftly identify potential hacks in web3, reducing damage through early detection.

How Using the Othentic Stack, task performers scan block data and run AI models to detect potential hacks, notifying users for immediate action.

Validity Markets ๐Ÿ“

Level: High Effort Category: Infrastructure,ZK Skillset: Backend Development,ZK Circuits, Cryptography

What A market for requesting ZK proof generation.

Why To simplify the creation of ZK proofs, which are computationally intensive, while ensuring the integrity of the proofs.

How Using the Othentic Stack, users submit requests for ZK proofs. Performers generate proofs with generic circuits, and attestators verify the proofs, slashing any performer who submits invalid ones.

Arbitrage Bots ๐Ÿค‘

Level: Medium Effort Category: DeFi, MEV Skillset: Backend Development,Optimization,Networking

What A network of arbitrage bots that capitalize on price discrepancies across exchanges.

Why To enable users to profit from short term price differences before they are corrected across various exchanges and DeFi platforms.

How Using the Othentic Stack, task performers and attesters monitor price changes and execute trades to seize arbitrage opportunities quickly.

Dark Pool (Uniswap V4 Hook)

Level: High Effort Category: UniV4 Hook,DeFi, Infra Skillset: Backend Development,Cryptography

What Build an on-chain order matching network with end-to-end trade privacy.

Why Current DEXes are completely transparent: anyone can see user balances and trade history. This has resulted into many traders losing billions to MEV, copy trading, statistical arbitrage, and quote fading.

How Traders can send their orders and ZK proofs for their wallet state to the AVS Performer nodes who will validate userโ€™s order request. Once validated, a network of Attesters would then share and match market orders amongst themselves via MPC to ensure trade privacy.

Dynamic Swap Fees (Uniswap V4 Hook)

Level: Medium Effort Category: UniV4 Hook,DeFi Skillset: Backend Development What Dynamic swap fees on Uniswap for periods of high volatility using Uniswap v4 hooks.

Why Uniswap LPs fare worse during times of high volatility due to impermanent loss and increased arbitrage trades.

How AVS operators monitor volatility using trusted external data sources or internal calculations. As volatility spikes, operators increase pool fees proportionally to offset risks and stabilize LP returns. Shared security helps ensure liveness of the nodes and an unbiased pricing at all times.

P2P Orderbook (Uniswap V4 Hook)

Level: Medium Effort Category: UniV4 Hook,DeFi, Infra Skillset: Backend Development What Enable direct matching of trades with opposing interests on Uniswap (e.g., USDC for ETH and vice versa) using v4 hooks.

Why To reduce trading fees and optimize liquidity usage by allowing users to swap assets directly in case of coincident of wants, rather than relying on the liquidity pool.

How Orders will be sent to the AVS to record them on IPFS or a DA layer. These buy or sell orders are then matched against each other, and validated by the attester network. Once matched they are sent on-chain for execution.

Automated LP Management for LSTs (Uniswap V4 Hook)

Level: Medium Effort Category: UniV4 Hook,DeFi Skillset: Backend Development What Automate liquidity management for pools containing yield-bearing tokens (e.g., stETH/ETH, rETH/USDC) by adjusting Uniswap LP positions in response to yield changes, via UniV4 Hooks.

Why To minimize slippage and optimize yield by automatically moving LP positions up the curve based on the yield.

How AVS operators fetch the yield from liquid staking positions and adjust LP positions by a constant amount. The economic security and decentralized nature of pool management ensure that the assets in the pool are secure.

Auctions for Loss Versus Rebalancing (Uniswap V4 Hook)

Level: Medium Effort Category: UniV4 Hook,DeFi, Infra Skillset: Backend Development What Run an auction to prioritize transactions in a block, addressing LVR by reducing the price discrepancies between off-chain and on-chain exchanges.

Why To minimize LVR, which results from the time lag between on-chain and off-chain price updates, thus encouraging more on-chain trading.

How AVS operators conduct an auction within each block to allocate the first transaction, with auction proceeds directed to liquidity providers (LPs) or swappers, instead of validators. Helps incentivize on-chain liquidity and improve price alignment.

Cross-Chain Price Aggregation (Uniswap V4 Hook)

Level: Medium Effort Category: UniV4 Hook,DeFi, Interoperability Skillset: Backend Development What Maintain a shared, aggregated state of capital across all AMM pools on different chains to enable more efficient price discovery.

Why To reduce price discrepancies and inefficiencies in arbitrage across chains, minimizing slippage and improving overall liquidity.

How Operators maintain an aggregated state of capital, allowing traders to trade against a multichain aggregated pool. Ensuring less slippage and more stable prices. All the while, shared security helps keep the asset pool secure.

Level: High Effort Category: AI/ML, Skillset: Backend Development,AI/ML What Build a privacy-preserving AI/ML training network. Why Training accurate AI/ML models requires a huge amount of data. Often this data is not available because the owners want to ensure privacy. For example, a new technique of training models was introduced by Google called . How Nodes in the network can train models locally without sharing their data which can then be aggregated to form a global model. This can be built on Othentic, where a network of Performers train models. Attestators validate the model accuracy increases in each epoch to ensure no malicious activity has occurred.

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