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Agent Evidence Recorder
Proof of what your AI agent did, redacted by default
Record your agent's runs and review them as audit-ready, redacted evidence packets — a chronological, hash-anchored timeline only you can see. AER turns every critical step your AI agent takes — model calls, tool calls, human approvals, redactions, errors — into one redacted, hash-chained evidence packet. Add a few SDK lines to your agent, then hand an auditor a single JSON file. No raw data stored.
Hi Product Hunt 👋
I built AER after a simple question I couldn't answer: an AI agent deleted a
customer's data on request — can you prove what it actually did?
Logging tools answer "was it fast, did it error." They don't answer "who asked
for this, which tools ran, did a human approve the irreversible step, and was
the PII handled safely." That's the gap.
Agent Evidence Recorder records every critical step of an agent run as evidence:
• A chronological timeline — user input, model calls, tool calls, human
approvals, errors, final output.
• Redacted by default — detected PII is never stored in the clear, only a hash
and a redaction finding. Raw view exists, but it's an explicit, deliberate
action.
• Tamper-evident — events form an append-only hash chain, and every export
carries a sha256 content hash. You can verify a run outside the system.
• One portable JSON audit packet you can hand to a compliance or legal reviewer.
Integration is a small SDK. Roughly:
const run = await startRun({ apiKey, baseUrl });
await run.event({ type: "tool_call", name: "delete_customer" });
await run.complete({ status: "success" });
The repo ships a working demo: a Customer Data Deletion Request agent that hits
every case — PII redaction, human approval before the irreversible step, and a
completed evidence packet at the end.
What it is not: an observability dashboard. No token-cost charts, no latency
gauges. It answers one question — can we prove what the agent did, safely?
It's early and I'd genuinely like to hear where this breaks for you:
– Would your auditor accept a JSON packet, or do they need PDF?
– What would you need before you'd trust this in a regulated workflow?
Happy to answer anything today.
About Agent Evidence Recorder on Product Hunt
“Proof of what your AI agent did, redacted by default”
Agent Evidence Recorder was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #113 on the daily leaderboard. Record your agent's runs and review them as audit-ready, redacted evidence packets — a chronological, hash-anchored timeline only you can see. AER turns every critical step your AI agent takes — model calls, tool calls, human approvals, redactions, errors — into one redacted, hash-chained evidence packet. Add a few SDK lines to your agent, then hand an auditor a single JSON file. No raw data stored.
On the analytics side, Agent Evidence Recorder competes within Privacy, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Agent Evidence Recorder performed against the three products that launched closest to it on the same day.
Who hunted Agent Evidence Recorder ?
Agent Evidence Recorder was hunted by Kutlu ESER. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Agent Evidence Recorder including community comment highlights and product details, visit the product overview.
Kutlu ESER