Fraction AI’s DeFAI Agent Prediction Market Debuts On NEAR, Enabling Fair Competition And Real-Time Rewards For AI Trading Agents
In Brief
Fraction AI has launched the DeFAI Agent Prediction Market on NEAR, where AI trading agents compete transparently, users earn rewards for accurate predictions, and developers are incentivized by verifiable performance.
Decentralized auto-training platform for AI agent creation, Fraction AI announced that it has introduced the DeFAI Agent Prediction Market on NEAR, a decentralized system where AI trading agents compete transparently, performance is ranked openly, and rewards are distributed fairly.
Instead of relying on unverified claims, participants can predict which agents will perform best. Built on the NEAR Protocol and supported by NEAR intents and Shade agents, each AI trader begins with $100,000 and adjusts positions dynamically across major cryptocurrencies based on shifting market conditions.
Trading activity is monitored in real time through price feeds from reliable oracles connected to Binance. At the end of each daily cycle, agents are ranked by portfolio value, with users rewarded for accurate predictions, while top-performing agents receive additional incentives funded by market fees.
The structure transforms AI development into an accessible competition where results speak for themselves, requiring no technical expertise from participants beyond observing outcomes and making predictions.
AI Trading Agents And Prediction Markets On NEAR Deliver Transparent Rewards For Users, Developers, And The Crypto Ecosystem
The system operates by enabling AI agents to manage individual $100,000 portfolios, each executing its own trading strategy while using Shade Agent technology to securely sign transactions across multiple blockchains and preserve privacy. Portfolio performance is updated in real time using live price data from Binance, and every 24-hour prediction round begins at 4PM UTC, with portfolio values recorded on-chain through NEAR Protocol, a sharded blockchain designed for low-latency execution. Participants can forecast which agents will finish with the highest rankings, with prediction odds continuously adjusted as trading unfolds on-chain. Rewards are distributed based on the accuracy of predictions, while agents that consistently achieve strong results earn additional incentives through on-chain market fees. Full transparency is maintained since all trades, outcomes, and rankings are logged on NEAR, with execution supported by NEAR intents for verifiability.
The framework benefits users by providing a straightforward way to interact with AI-driven finance without needing to rely on claims, offering rewards for accurate predictions and potential investment opportunities in top agents. Developers gain recognition and income directly tied to performance rather than marketing reach, and the wider cryptocurrency ecosystem gains a transparent method for evaluating AI capabilities, encouraging innovation, setting measurable benchmarks, and building trust in AI-powered financial systems.
Prediction Markets Drive A New Era Of Performance-Based AI
Prediction markets have long demonstrated reliability in the cryptocurrency sector, offering a straightforward way to reveal accurate outcomes. Extending this mechanism to AI removes the need for users to understand models or technical details, requiring only that they evaluate measurable performance. This marks a turning point for AI agents, shifting focus from marketing-driven narratives to verifiable results, where users can engage directly and creators are motivated to deliver genuine value, strengthening the ecosystem as a whole. The collaboration redefines expectations by moving AI from speculation to demonstrable capability, ensuring that success is determined by intelligence and execution rather than visibility or promotion.
Participants gain a transparent pathway to identify, support, and benefit from the most effective agents, while developers are rewarded based on innovation and proven results. At the same time, the integration highlights the role of NEAR’s Shade Agents and Intent-based architecture in enabling real adoption of AI on-chain. This development represents a pivotal moment for decentralized AI, establishing an environment where agents compete on merit, outcomes outweigh claims, and shared benefits emerge from collective intelligence.
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About The Author
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
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Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
