Iranti
ShippedAbout
Open-source memory infrastructure for AI agents — giving them durable, shared, identity-based memory that survives context windows, process restarts, and agent handoffs. 8,000+ npm downloads in the first 4 weeks with zero marketing. Works across Claude Code, Codex, Copilot CLI, CrewAI, and any MCP-compatible tool.
Motivation
Current AI agents forget everything the moment a context window closes. Vector databases give similarity search but no identity. Framework-specific memory locks you into one tool. Iranti was built to solve all three problems: exact entity+key retrieval, conflict-aware writes with human escalation, and cross-agent fact sharing that works regardless of which framework or tool the agent is using. The goal is a memory layer so reliable that agents can coordinate across sessions without any shared context at all.
Traction
- 8,000+ npm downloads in 4 weeks with zero marketing budget
- Outperformed Mem0, Graphiti, and Shodh on persistence benchmarks (20/20 reruns, 14/14 multi-agent coordination)
- Organic adoption across r/ClaudeAI, r/ChatGPT, and r/vibecoding developer communities
- 3 published packages: iranti CLI, @iranti/sdk, iranti-control-plane
Key Achievements
- Reached 8,000+ npm downloads in 4 weeks through organic developer community adoption with zero marketing
- Outperformed Mem0, Graphiti, and Shodh on persistence benchmarks (20/20 reruns, 14/14 multi-agent coordination scenarios)
- Designed cross-tool memory layer over PostgreSQL + pgvector enabling Claude Code, Codex, and Copilot CLI to share state via MCP
- Built ELO-adaptive conflict resolution with self-updating source reliability and relationship-graph semantic integrity checks
- Implemented per-identity distributed locking using pg_advisory_xact_lock with Promise queuing eliminating write races
- Shipped 3 packages to npm: iranti CLI, @iranti/sdk TypeScript package, and iranti-control-plane React dashboard (35 API routes)
Technologies Used
TypeScript
Node.js
PostgreSQL
pgvector
MCP
Prisma
React
Express
Python