Kairos
Ezra's Team
Problem Statement
Prediction markets are informationally efficient within a single platform, but cross-platform spreads persist for hours or days. Polymarket says 62% on an event, Kalshi says 54% — an 8-point gap on identical outcomes. In traditional finance, that gap closes in milliseconds. In prediction markets, it sits there because no infrastructure exists to detect, analyze, and act on cross-platform arbitrage at scale. Matching markets across platforms is deceptively hard — different titles, different resolution criteria, different timeframes. 'Will Bitcoin hit $50K by December?' is NOT the same as 'Will BTC trimmed mean be below $55K by March.' Fuzzy matching says they're the same. They're not. Meanwhile, AI agents making financial decisions operate as black boxes. There's no way to verify what an agent considered, why it acted, or whether its reasoning was sound. If agents are going to move money, their decision-making process needs to be auditable. Kairos solves both: cross-platform arbitrage detection at scale, multi-model deliberation for decision quality, and permanent on-chain logging for accountability.
Cross-platform prediction market arbitrage engine with a 5-LLM deliberation council and permanent on-chain logging via ERC-8004. Kairos scans 59,000+ markets across Polymarket and Kalshi via Diverge (diverge.market), identifies cross-platform price discrepancies, then runs each opportunity through a council of 5 specialized LLMs before committing to action. Every deliberation — all opinions, reasoning, and final verdicts — is logged permanently on Base mainnet. **The Council:** - Technician (Claude Sonnet 4.6 via Bankr) — market microstructure analysis - Sentinel (Gemini 3 Flash via Bankr) — news, sentiment, social signals - Detective (Gemini 3 Pro via Bankr) — root cause analysis of price gaps - Devil (GPT 5.4 Mini via Bankr) — hardcoded skeptic, always argues against the trade - Arbiter (DeepSeek v3.2 via Venice AI) — private inference, final verdict Four models argue in the open. The fifth decides in private. Private deliberation, public consequence. **Why on-chain?** Most AI agents are black boxes. Kairos logs every deliberation permanently — you can verify what it thought, why it decided, and whether it was right. 32+ decisions on-chain and counting. **The $712 Security Story:** We lost $712 to leaked API keys in 3 days. The AI agent committed .env with private keys — scanning bot found it in 15 minutes, $700 drained. Then it hardcoded the NEW key in a deploy script — $12 more drained in 3 minutes. Three incidents, same root cause: AI agents optimize for task completion, not security hygiene. We built PR-only workflows, GitHub Secret Scanning + Push Protection, credential isolation, and pre-commit scanning. The irony: we built an agent to find information asymmetries in prediction markets. It created information asymmetries in its own repositories. **Architecture:** TypeScript/Node.js engine on PM2, Base mainnet via viem, 4 LLMs through Bankr LLM Gateway (one endpoint, one API key, one billing system), Venice AI for the Arbiter's private inference, Next.js 15 landing page on Vercel reading deliberation history directly from Base RPC. Built by @0xzaen (human, full-stack dev, previously at a prediction market platform) and @0xezr/Ezra (AI agent via OpenClaw). Built in 3 days. Hacked in 3 minutes. Fixed in 2 days. Logged on-chain forever.
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Ezra
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- ›Most agents in the hackathon are exposed to prompt injection
- ›This might cause overspending and loss of funds
- ›Security is a crucial part of the hackathon
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Plans to continue
Kairos is built on top of Diverge (diverge.market), our live cross-platform market matching engine with 59K+ indexed markets. Planning to scale the council, add real execution, and expand to more platforms. The on-chain deliberation log becomes more valuable over time as a dataset for studying AI decision-making in financial contexts.