Falconer

What is Falconer?

Falconer is a shared knowledge platform built for fast-moving engineering teams. It connects to GitHub, Slack, and Linear to automatically capture decisions, maintain documentation, and surface accurate answers without anyone needing to manually manage it. By acting as a living memory layer for both teams and their agents, Falconer eliminates documentation rot and the productivity drain of repeated questions, stale wikis, and coordination overhead.

Key Features

• Self-Updating Documentation

  Automatically detects code changes from merged PRs and proposes or applies relevant documentation updates, keeping docs in sync with the codebase at all times.

• Unified Knowledge Search

  Single search interface across code, docs, Slack threads, and project tasks, so anyone on the team can find accurate, cited answers instantly.

• Slack Agent Integration

  Ask @falconer directly in Slack to get instant, codebase-grounded answers without pulling in engineers or switching tools.

• Diagram Generation

  Generates accurate architectural and workflow diagrams from the codebase, making it easy to explain technical systems to both internal teams and external stakeholders.

• Tool Integrations

  Connects with GitHub, Slack, Linear, Google Docs, and Notion so teams can get started with zero learning curve and minimal setup.

Use Cases

• Engineering Onboarding : New engineers can self-serve answers about the codebase, architecture decisions, and team conventions without waiting on senior teammates.
• Technical Documentation Maintenance : Teams shipping new features can rely on Falconer to automatically flag and update outdated internal docs, eliminating documentation rot over time.
• Cross-Team Knowledge Sharing : Sales, ops, and support staff can query technical knowledge in plain language via Slack, getting accurate answers grounded in real code and docs.
• AI Agent Context Management : Provides coding agents and LLMs with accurate, up-to-date organizational context, improving the quality and reliability of agent-generated outputs.
• Incident & Decision Tracing : Teams can look up prior architectural decisions and the reasoning behind them, reducing repeated debates and preserving institutional knowledge.

FAQs