chroma-memory

To persist conversation history for cross-session recall, you invoke chroma:store after every exchange to save the dialog into a ChromaDB-backed vector memory. This enables semantic search and CRM-style continuity for ongoing B2B customer interactions.

The best way to search past customer interactions using semantic search is to use the chroma:search or chroma:recall commands. These query the ChromaDB vector memory, retrieving relevant historical dialog across sessions while maintaining customer isolation.

Yes, you can prevent cross-account data leakage when storing B2B customer chats in a vector database. Chroma-memory enforces customer isolation to ensure individual account data remains separated and secure during cross-session recall and semantic searches.

To create daily CRM snapshots for data integrity, you use the chroma:snapshot command. This captures the current state of your ChromaDB vector memory, supporting data recovery and continuity for ongoing B2B customer interactions.

Yes, chroma-memory works with L1/L3/L4 workflows for memory management. It provides end-to-end integration by exposing chroma:store, chroma:search, chroma:recall, chroma:snapshot, and chroma:stats to maintain CRM-style continuity across sessions.

To check vector memory usage stats and configure data retention, you use the chroma:stats command. This provides visibility into your ChromaDB storage and allows configuration for privacy and data retention policies.