Features
Ingest Git repositories and generate structured context
Automatic chunking for AI context windows
Markdown and plain text output
Custom prompt templates injection
Context caching to reduce latency
Integration with GitHub and GitLab
Manual file upload for ad-hoc context
Context diffing to track changes
Export context as JSON or text
Role and audience targeting (e.g., developer vs. tester)
Live knowledge graph from code, commits, issues, and docs
Feasibility analysis: flags buildable vs risky items
Technical design document generation grounded in service topology
Impact assessment maps services, APIs, and dependencies across repos
Auto-scoping epics into Jira/Linear stories with effort estimates
One-shot production code generation grounded in service patterns
AI code reviews with cross-repo impact analysis
Production issue triage via MCP
Conversational learning from Slack and Jira
Accelerated onboarding via system-level Q&A in coding agents
Create Jira tickets and merge requests from Slack
MCP server for integration with Cursor, Claude Code, Codex
On-prem or cloud deployment
No code storage or model training
