We built Oxynote because we got tired of documenting new features while their contextual information lived somewhere else. In most teams, feature requirements and acceptance criteria are in Notion or Confluence, metrics and alerts are in Grafana, and the "why we did it this way" is buried in GitHub pull requests and Slack threads.
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So engineers waste time hunting for basics like expected behavior, edge cases, rollout plans, service ownership, and what production looks like when things are healthy. And unlike code, docs often don’t have a solid review process, so they quietly drift until nobody trusts them.

Oxynote puts those pieces together in one place: feature requirements, API contracts, runbooks, incident notes, and deployment metrics that prove what’s actually happening. The goal is simple: less searching, fewer wrong assumptions, and faster implementation that matches reality. As a bonus, when that context is organized and up-to-date, AI tools stop guessing and become genuinely useful.