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Agent Evidence Recorder

Proof of what your AI agent did, redacted by default

Privacy
Developer Tools
Artificial Intelligence
GitHub
Visit WebsiteSee on Product Hunt

Hunted byKutlu ESERKutlu ESER

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.

Top comment

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.

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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.

Agent Evidence Recorder was featured in Privacy (11.3k followers), Developer Tools (517.6k followers), Artificial Intelligence (476.1k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 229.3k products, making this a competitive space to launch in.

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.

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