Features
Outcome-based memory scoring (wilson score)
Two-lane retrieval: 4 summaries + 4 facts per turn
TagCascade retrieval pipeline
Automatic summarization of conversations
Noun tagging at store time
Memory lifecycle: working (24h), history (30d), patterns (∞)
Demotion of low-scoring memories
Poison-resilient against semantic match + spoofed trust
Works with Claude Code and OpenCode
Local-first, no cloud dependency
Desktop GUI with Ollama/LM Studio support
MCP (Model Context Protocol) tools
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
