Alternatives
Products that do what Infinite Context Memory (ICM) does
10M-token BYOK memory. Cut your LLM API costs by 90%.
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Hey HN! We're Taranjeet and Deshraj, the founders of Mem0 (https://mem0.ai). Mem0 adds a stateful memory layer to AI applications, allowing them to remember user interactions, preferences, and context over time. This enables AI apps to deliver increasingly personalized and intelligent experiences that evolve with every interaction. There’s a demo video at https://youtu.be/VtRuBCTZL1o and a playground to try out at https://app.mem0.ai/playground. You'll need to sign up to use the playground – this helps ensure responses are more tailored to you by…
2024 · github.com
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I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video:…
2025 · github.com
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Built this for my LLM workflows - needed searchable, persistent memory that wouldn't blow up storage costs. I also wanted to use it locally for my research. It's a content-addressed storage system with block-level deduplication (saves 30-40% on typical codebases). I have integrated the CLI tool into most of my workflows in Zed, Claude Code, and Cursor, and I provide the prompt I'm currently using in the repo. The project is in C++ and the build system is rough around the edges but is tested on macOS and Ubuntu 24.04.
2025 · github.com
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Hi HN, There’s been a lot of discussion lately around context graphs, decision traces, and how AI systems reason. One thing we kept running into: when AI agents make real decisions, the why behind those decisions often disappears. The context is scattered across prompts, tools, policies, and approvals. Logs show what happened, but not why it was allowed. TraceMem is an attempt to make decision context durable. It records the reasoning, authority, and context behind AI actions as a system of record, not as monitoring data, but as memory. Happy to share more details or answer questions. - Tommi
Jan 2026 · tracemem.com
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Virtual Memory Manager for LLMs. Drop into your stack now!
May 2026 · dopove.com
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May 2026 · adola.app
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Hey HN! We're Deshraj and Taranjeet. We've been building working on a startup called Mem0, building an open-source memory layer for AI apps and agents (https://news.ycombinator.com/item?id=41447317). We also kept running into our own daily frustrations with AI assistants forgetting everything between conversations. Over a weekend, we decided to hack together a Chrome extension to solve this for ourselves. The problem was simple: we were constantly re-explaining our context across platforms when switching between ChatGPT, Claude, and Perplexity. Start a coding discussion in…
2024 · github.com
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Hi HN, Erik here. Today we launch Butter, an OpenAI-compatible API proxy that caches LLM generations and serves them deterministically on revisit. Since April, we’ve been working on this concept of “muscle memory,” or deterministic replay, for agent systems performing automations. You may recall our first post in May, launching a python package called Muscle Mem: https://news.ycombinator.com/item?id=43988381 Since then, the product has evolved entirely, now taking the form of an LLM Proxy. For a deep dive into this process, check out:…
Oct 2025 · docs.butter.dev
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Hi HN, I'm building Librarian (https://uselibrarian.dev/), an open-source (MIT) context management tool that stops AI agents from burning tokens by blindly re-reading their entire conversation history on every turn. The Problem: If you're building agentic loops in frameworks like LangGraph or OpenClaw, you hit two walls fast: Financial Cost: Token usage scales quadratically over long conversations. Passing the whole history every time gets incredibly expensive. Context Rot: As the context window fills up, the LLM suffers from the "Lost in the Middle" effect. Response latency…
Feb 2026 · uselibrarian.dev
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