Memory Hybrid Stackv0.1.0

An AI assistant tracks user preferences (Postgres), current interest state (Redis), and retrieves semantically similar articles (Qdrant) to deliver a personalized news feed in real time.

The stack manages durable user profiles (Postgres), session state like cart contents (Redis), and retrieves past interaction context via vector search (Qdrant) to provide coherent, personalized support.

Patient vitals and alerts update Redis for low-latency access, structured medical records store in Postgres, while Qdrant indexes clinical notes for semantic search across symptoms and treatments.

Redis caches device status and locks for real-time coordination, Postgres stores durable device configurations and logs, and Qdrant enables semantic search over maintenance manuals and error patterns.

The assistant uses Redis for short-term task state, Postgres for persistent task and project data with tagging, and Qdrant for semantic recall of notes and documents to aid planning and research.

Users pay based on the volume of facts stored, state operations per month, and vector queries. Higher tiers offer faster embedding generation and longer TTL for Redis state.

Leverage hybrid memory to build detailed user preference profiles (Postgres) and session intent (Redis) to serve highly relevant ads, while Qdrant enables semantic ad matching to user's current context.

Expose anonymized, aggregated insights derived from the memory stack (e.g., trend analysis across users via Postgres queries, semantic patterns via Qdrant) as an API for third-party developers.