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I built a cryptographic audit trail for AI agent decisions — now a verified n8n node

Leader ●1 ●9 ●24
calendar_today ago • schedule1 min read

AI agents are making real decisions: approving loans, releasing payments, flagging insurance claims, modifying customer records. When something goes wrong, there's usually no tamper-evident record of what the agent decided, why, and under which policy.

I built Signatrust to fix that.

How it works:
Every agent decision → sealed into a Decision Receipt → Ed25519 signature + SHA-256 hash chain → append-only ledger. Any third party can verify the receipt independently without touching your systems or seeing your raw data.

What's available now:

  • ✅ Verified n8n node: n8n-nodes-signatrust (install from Community Nodes)
  • 📦 PyPI: pip install langchain-signatrust / crewai-signatrust
  • 📚 24 ready-to-import n8n workflows (finance, insurance, HR, healthcare, GDPR)
  • 📜 Open spec (ADR v1.0): signatrust.net/adr
  • 🆓 Free tier, no account needed to verify receipts

Links:
→ github.com/abokenan444/n8n-signatrust-workflows
→ signatrust.net
→ npmjs.com/package/n8n-nodes-signatrust

Would be curious to hear: are you building AI agents that touch regulated or high-stakes decisions? How are you handling the audit trail today?

4 Comments

•

Great idea, bringing cryptographic verification to AI agent decisions is a smart step toward better transparency and trust. Looking forward to seeing how this evolves in real-world workflows!

1 vote
•

@[Mehadi Hasan] Thanks Mehadi! The best way to see it in action is to try it directly — you can paste any receipt JSON at signatrust.net/verify and see the Ed25519 signature check, body hash match, and chain linkage in real time. No account needed.

If you're using n8n, the 24 workflow templates at github.com/abokenan444/n8n-signatrust-workflows show exactly how it fits into real automation pipelines — loan decisions, fraud flags, GDPR data changes, etc.

Would love to hear your thoughts after you try it.

1
•

This is a great step toward making AI workflows more transparent and trustworthy. Verifiable audit trails will become increasingly important as AI agents handle more critical tasks.

2 votes
•

@[VGR] Exactly, VGR — and the stakes are already real. Here's a concrete example of why this matters today:

Scenario: AI agent rejects a loan application

  1. Applicant submits: €50,000 loan, 60 months, credit score 612, DTI 47%
  2. The AI agent evaluates and decides: REJECTED — insufficient credit history, debt-to-income above threshold
  3. Without Signatrust: the decision exists only as a database entry. If the applicant disputes it, or a regulator asks “what model version made this decision, under which policy, at exactly what time?” — there’s no tamper-evident answer.

With Signatrust, the agent seals a Decision Receipt at the moment of rejection:

  • Model: anthropic · claude-3.7 — locked
  • Policy applied: eu-ai-act-high-risk, internal-credit-v3 — locked
  • Input hash (applicant data fingerprint) — locked
  • Output hash (rejection reason codes) — locked
  • Ed25519 signature — independently verifiable by anyone
  • Hash-chained to receipt #243 before it and #245 after it — insertion or alteration breaks the chain

You can verify this exact receipt live right now:
👉 signatrust.net/verify — paste Receipt ID: STR-6AF0B4CD75

If the applicant disputes 6 months later, the bank produces the receipt. The regulator verifies it in seconds — no access to internal systems needed. The signature either holds or it doesn’t. That’s the audit trail AI agents have been missing.

1
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Yasser Ab
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Netherlands • webagentbridge.com
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Active developer and follower of AI Agents technologies. I focus on open-source solutions that solve... Show more

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