Proof Owl
BuildingAI-powered proof-of-work tracker. Proof Owl builds structured, timestamped records that clients can verify and AI models can cite — every deliverable logged as it happens.
Clients don't trust deliverables they can't verify, and agencies waste hours building manual reports just to prove the work happened. Proof Owl logs every action as it happens — with a timestamp and a link back to the artifact — so the record is built as the work is done, not reconstructed after the fact.
A piece of work as it happens — a commit, a doc, a shipped page, a completed task.
Claude Code turns it into a timestamped, evidence-linked record — entity, action, date, proof.
A verifiable proof record a client can check and an AI model can cite.
Claude Code
Structures raw activity into timestamped, evidence-linked records. The whole system runs on it — deliberately, no extra moving parts.
AI / structuringThe actual Notion workspace running Proof Owl — the proof records being logged, their evidence links, and what's shipping next, updated as the work moves.
It builds structured, verifiable, citable records of work. Each entry is stored as structured data — entity, action, date, evidence link — rather than prose, which is what makes it machine-readable and citable in the first place.
When records are built this way, AI models surface them. That structured-data foundation is the first thing I build for clients, proven here as a standalone tool instead of an internal process.
As of July 1, 2026
— proof records published · — evidence links · — records surfaced in AI answers
Real numbers land here on the first Monday of each month. Small is fine. Zero is fine.
- An automated citation-tracking database — structured, timestamped, and queryable.
- A weekly scan that outputs structured data, not a hand-written status report.
- Citable proof pages, schema-marked and indexed by AI search.
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This runs on the same system I install for B2B SaaS founders. The entry point is a paid AI Visibility Audit.