Falconer
A self-updating knowledge platform that keeps engineering teams' docs, context, and codebase understanding accurate and always in sync.
Community:
Product Overview
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Technical Documentation Maintenance : Teams shipping new features can rely on Falconer to automatically flag and update outdated internal docs, eliminating documentation rot over time.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
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