Gitmem

What it does

Stop bleeding tokens on redundant context. Our persistent memory layer gives agents a reliable "brain," ensuring models never lose the thread. By optimizing how agents retrieve information, we eliminate hallucinations and slash monthly API spend by 37%. Build smarter, leaner, and production-ready agentic workflows that actually remember.

One memory across every app and agent you use. Captured automatically, synthesized continuously, shared on your terms. Everything your coding agents need to deliver accurate, context-aware responses without token waste. Keep your coding agents grounded with real-time repos, up-to-date API schemas, and robust document boundaries. Save token costs. Prune unnecessary files dynamically and feed agents only the hyper-relevant snippets. Live codebase listener. Your local modifications are compiled and indexed immediately for your connected tools. The Manhattan Project is onboarding users in batches. We'll prioritize users who filled out all answers. We'll be in touch soon! Hi there! 👋 Have any…from themanhattanproject.ai

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  This is a project that I have been building for a while now, YourMemory is a solution to agentic memory which focuses on pruning of noise rather than hoarding of data. In the current state of agentic memory most of the context is stored in the form of a MD file or is derived through a RAG model where you store each and everything. Both of the solution leads to bloated context which does not optimize the usage of any tokens. In this system we only keep relevant data in our memory and prune all the unnecessary data. The relevance of a data is derived through multiple factors such as recall…

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