Gave CrewAI real long-term memory with Mem0 and measured the savings head-to-head (memory crew vs cold crew)

Reddit r/AI_Agents 07/07/26, 07:17 PM Tools

crewai mem0 long-term-memory ai-agents token-savings cost-analysis open-source

Summary

A reproducible demo showing how adding long-term memory to CrewAI with Mem0 reduces token usage and latency via a fast/deep routing heuristic, with real measurements and a live dashboard.

Built a reproducible demo comparing a memory-backed CrewAI crew against a cold one on the same tasks: Shared Mem0 brain → fast path (1 call) vs deep path (2 calls) routing on memory hits Real measured tokens/latency/cost (not estimates) "It remembered" recall probe scored with embedding similarity Live dashboard with a mid-run "wipe memory" button to prove causality Local on Ollama, MIT-licensed. Would love feedback on the fast/deep routing heuristic and how you'd handle memory bloat over long runs.

Original Article

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