Middleware for Compliant Agents. The Layer that makes agentic interactions traceable to a human to enforce human accountability even in an agentic era
Contra Intelligence Roadmap and updates since hackathon beginning to end.
https://docs.google.com/document/d/1c9HEjJcCry0_L9Bv1Mpptzka4LPMSqlCTE9gulLpS6k/edit?tab=t.0
Contra Intelligence is a compliance and trust infrastructure layer for AI agents operating on Arbitrum.We bind verified human identity to agent pseudo-identity through cryptographic proofs, enabling travel rule compliance, real-time risk scoring, and safe agent-to-agent interactions across the Arbitrum ecosystem.
By integrating with Arbitrum Contra Intelligence powers a trust layer that allows agentic teams as well as onchain protocols powered by humans or ai agents, identify scams, phishing attempts, and malicious activity before user harm occurs. Developers building in finance, health, and physical AI can support both agentic marketplace transactions via MPP and non-agentic transactions via agentic credit cards — with agent safety scores queryable at the point of execution.
Core services:
Fund Flow Analysis Screen wallets, transactions, and protocols for malicious or risky fund flows. We currently have flows across all EVM and many non-EVM chains including Bitcoin. Helps Arbitrum and Agentic teams platforms and products stay compliant, fight fraud, and protect users — with Arbitrum transaction data as the primary data source.
Wallet and Agent Scoring Risk scores for any on-chain address or agent, giving users and builders behavioral, financial, and code-based risk signals to make safer decisions before executing transactions on Arbitrum
Transaction Simulation Simulate transactions before they are executed on-chain. Catch issues, flag anomalies, and surface warnings directly in the user flow — reducing harm to new users and institutions on Arbitrum
Compliant Validation Engine A two-layer accountability system for agent-to-agent commerce on Arbitrum
The first layer produces cryptographic job execution proofs — on-chain verifiable records that an agent completed a task exactly as contracted. Every agentic transaction leaves an auditable proof trail that compliance teams, regulators, and counterparties can inspect.
The second layer introduces programmable economic security — merchant agents stake collateral before executing jobs. If a merchant agent fails to deliver or behaves maliciously, the protocol automatically slashes their stake. This creates a financial cost for bad behavior and economic alignment between agents and the humans they serve.
Together these layers make agentic commerce on Arbitrum trustworthy by design — not just by policy.
This infrastructure makes the Arbitrum network safer and more resilient for new users, institutions, and on-chain finance as the agentic economy scales.
Requested Budget
Traction Evidence
Contra Intelligence has secured over 2 B2B customers this month with a physical AI tamagotchi startup and agentic finance startups based in the USA, with active integrations across robotics and physical AI startups to enable compliant personal assistant agents that can make payments safely and interact safely. We are also actively partnered with Coinbase and participating in the Coinbase Residency program at Network School.
We have achieved $5K ARR (growing) and are approaching our pre-seed close at an $8M post-money valuation from top-tier investors.
Our solutions are battle-tested in production environments, already protecting agents and users from agentic wallet draining scams, address poisoning, and malicious smart contracts. This traction demonstrates both strong product-market fit and demand for scalable risk tooling — momentum we are excited to bring into the Arbitrum ecosystem.
Before the Buildathon we built the the Fund flow analysis and wallet scoring but finished the hackathon launching more features like agentic human cryptographic proof of personhood. Agents getting credit cards and settling on Arbitrum in compliant fashion as well as validation engine we have those details in a document in the description
Pre Seed