Autonomous agents suffer from amnesia due to expensive in-memory vector storage, which limits their long-term capabilities and drives up costs.
Memanto.ai is an open-source agentic memory built on serverless vector search that addresses six key failure modes including relevance, freshness, and conflict resolution.
The interactive dashboard provides tools for managing agents, exploring memories, viewing history, resolving conflicts, and migrating from other systems.
Memanto provides a powerful CLI for terminal-based management and integrates with popular AI assistants and frameworks like Claude, Cursor, and Gemini.
Performance benchmarks on Locomo and LongMemEval demonstrate that Memanto achieves state-of-the-art results compared to other agent memory solutions.
You can install Memanto with a single pip command, connect it to a backend, and contribute to the open-source project via GitHub or community channels.
Jobs that call for the skills explored in this talk.