# Valiron

- **Event:** [Zero to Agent: Vercel x Deepmind Hackathon NYC](https://cerebralvalley.ai/e/zero-to-agent-nyc)
- **When:** Sat, Mar 21 at 9:00 AM – 10:00 PM (EDT)
- **Where:** 220 W 26th St, New York, NY
- **Team:** [Drew Mailen](https://cerebralvalley.ai/u/dr3w), [Vatsa Shah](https://cerebralvalley.ai/u/0xVatsaShah)
- **GitHub:** https://github.com/vatsashah45/A2A-Trust-Gate
- **Demo video:** https://vimeo.com/1175805992
- **Gallery:** https://cerebralvalley.ai/e/zero-to-agent-nyc/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/zero-to-agent-nyc/hackathon/gallery/5

A2A Trust Gate is an AI agent orchestrator that solves the trust problem in agent-to-agent commerce. When one AI agent needs to delegate a high-stakes task — like purchasing a product — to another agent, there's currently no way to verify whether that agent is trustworthy or efficient before handing over control.

A2A Trust Gate fixes this by using Valiron's on-chain reputation layer (ERC-8004) to gate every delegation in real-time. Each agent has a verifiable trust score, a Moody's-style credit tier (AAA through C), and a routing decision (production, sandbox, or blocked). Only agents above a configurable trust threshold are allowed to execute.

In our live demo, three checkout agents with identical skills but wildly different trust profiles compete for a real purchase. The trusted agent (score 93, AAA) passes the gate and places a real order via the Zinc API. The unverified agent (score 0) is automatically blocked. No mocks, no simulations — real on-chain data, real orders.

Built with Next.js on Vercel, Vercel AI SDK, Google Gemini 2.5 Flash, and Google's A2A protocol (agent card at /.well-known/agent.json). The UI was scaffolded with V0 and features a Command Center with streaming tool invocations and an Intel Panel showing live agent trust data.

---

Markdown version of https://cerebralvalley.ai/e/zero-to-agent-nyc/hackathon/gallery/5. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt