Show HN: MemoryOps AI – governed memory lifecycle for AI assistants

Category: infrastructure

Tags: ai-memory, memory-governance, rag

Score: 7.3/10 (Innovation: 7, Technical: 8, Documentation: 8, Utility: 6)

MemoryOps AI is a governed memory lifecycle system for AI assistants, implementing typed memory stores with policy evaluation, hybrid retrieval, auditability, and tenant isolation as first-class invariants. It distinguishes itself from simple vector-db demos by treating memory as governed state with enterprise features like Row-Level Security, append-only audit logs, and a policy-before-storage principle. The project is interesting for its comprehensive, production-oriented approach to AI memory management beyond typical retrieval-augmented generation patterns.

Target audience: backend devs, data engineers, ai-engineers

Repository: https://github.com/patibandlavenkatamanideep/memoryops-ai · Python · 10 stars

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