PR Activity
System monitors GitHub activity and pulls intent from commit messages and code changes.
Turn every PR and AI conversation into reusable knowledge. Tracewoven connects your stack to an intelligent context layer that humans and agents can query instantly.
# Implementation Details
The recent migration to Redis-backed sessions was completed to resolve the latency spike observed in the EU-West-1 cluster.
Tracewoven doesn't just feed data to LLMs. It generates a high-end, searchable internal documentation portal for your engineers. No more "where is the architecture diagram?" or "why did we build it this way?"
Witness the transformation of raw development activity into structured engineering intelligence.
System monitors GitHub activity and pulls intent from commit messages and code changes.
Extracts architectural decisions and "why" from Claude Code or Cursor sessions.
Tracewoven structures the data, resolves contradictions, and builds a knowledge graph.
Context is served back to AI agents AND rendered as a high-fidelity documentation site for your team.
Stop writing outdated documentation. Tracewoven silently listens to your development lifecycle, capturing tribal knowledge that usually evaporates after a sprint.
Identifies when new PRs contradict previous memory, prompting resolution to keep your knowledge graph 100% accurate.
Automatically renders a beautiful, browsable technical wiki that serves as the single source of truth for your entire organization.
Every piece of memory is tied to a specific line of code or a specific conversation. Fully auditable, explainable, and reliable.

Deploy our integration in minutes. Tracewoven authenticates via secure OAuth with your GitHub repositories and monitors your favorite AI development tools.
We back-index your existing repository history, extracting key design decisions and architectural patterns from past PRs and team discussions.
Our synthesis engine categorizes knowledge into a searchable, relational context layer. If code evolves, the memory evolves with it.
Agents query the API for precision, while engineers browse the auto-generated documentation for high-level understanding. One source of truth for all actors.