Hi Product Hunt community, We built InfinityDB to solve the primary bottlenecks facing production AI agents: high token costs, slow recall latency, and lack of deterministic memory auditability. Most current memory libraries dump conversation transcripts into vector databases. This requires constant auxiliary LLM calls for extraction, introduces vector hallucination on conflicting facts, and incurs 35ms to 140ms latency. InfinityDB introduces a tiered L0–L6 neurosymbolic architecture operating locally on SQLite WAL mode: - L0: Disk-backed raw interaction store that eliminates up to 81.4% of agent prompt token bloat. - L1: Deterministic fact extraction with zero LLM API calls ($0 extraction cost). - L2: Episodic causal graph tracking dependencies between memory events. - L3: Dynamic persona with automatic chronological conflict resolution. - L4: Enterprise policy engine injecting compliance guardrails directly into recall context. - L6: Immutable SHA-256 cryptographic proof chain linking every recalled fact back to its exact raw source transcript. Verified benchmarks from our 2,000-turn stress test: - Recall latency (p95): 4.2ms - Context token reduction: 81.4% - Fact extraction cost: $0 Ecosystem support available today: - Python: pip install infinitydb-ai - Node.js & TypeScript: npm install infinitydb - Native MCP Server: Out-of-the-box support for Claude Desktop and Cursor - Turnkey adapters: Drop-in memory support for LangChain and CrewAI Try the interactive browser demo without installing anything: https://huggingface.co/spaces/Di... Repository (100% open source under Apache 2.0): https://github.com/infinitydb-ai... We look forward to your feedback, questions, and feature requests.

InfinityDB

Sub-millisecond neurosymbolic memory engine for AI agents

Sub-millisecond neurosymbolic memory engine for AI agents