Interoperable, efficient memory layer for agentic AI
Every AI conversation contains knowledge worth keeping, but most of it gets trapped in separate chats and tools. Living Brain captures that knowledge, connects it to what you already know, and turns it into a persistent memory that keeps evolving. Share that intelligence across AI models, apps, and agents through API, SDK, or MCP, so every new interaction builds on the last instead of starting over. Reuse memory across ChatGPT, Claude, Gemini, OpenClaw, Hermes, Cursor, Codex and more
Hey Product Hunt 👋 I’m Christel, founder of ChatAndBuild, and I was part of Twitter's first international team.
We have built the Living Brain - a model independent, harness independent, efficient brain that travels with you across any AI platform.
Living Brain gives your AI tools a shared, persistent memory. It turns your notes, documents and conversations into connected knowledge that you can inspect, update and reuse across compatible assistants and agents.
For example, save a project brief, customer requirements and the decisions behind your roadmap in one brain.
Connect it to your AI tools, and they can retrieve that context when you ask them to work on the project.
With Living Brain, you can:
🧠 Build a memory around your work, projects and preferences. 🔗 Reuse that memory across ChatGPT, Claude, Gemini, OpenClaw, Hermes, Cursor, Codex and more 🛠️ Give your own apps and agents persistent context through our API. 📚 Review the organised knowledge and the sources behind it.
We’re measuring how accurately AI can use that memory, alongside how much context it needs.
Our latest internal evaluations show:
We're #1 on LoCoMo with 92.2% judged accuracy, answering 1,420/1,540 questions correctly with approximately 63.8% less context.
Those context reductions compare average retrieved memory with the displayed full-history references — approximately 9.4K versus 26K tokens on LoCoMo, and 5.1K versus 115K on LongMemEval-S.
We want you to choose each AI for what it does best, with your accumulated context coming along.
We’re building this for people who use several AI tools, teams whose context is scattered, and developers building agents that need continuity.
I’d love to hear from you. What’s the one thing you’re tired of explaining to AI over and over?
Tell us your workflow. I’d love to see where Living Brain could help, and where we still need to improve.
— Christel
About Living Brain on Product Hunt
“Interoperable, efficient memory layer for agentic AI”
Living Brain launched on Product Hunt on November 5th, 2026 and earned 248 upvotes and 37 comments, earning #2 Product of the Day. Every AI conversation contains knowledge worth keeping, but most of it gets trapped in separate chats and tools. Living Brain captures that knowledge, connects it to what you already know, and turns it into a persistent memory that keeps evolving. Share that intelligence across AI models, apps, and agents through API, SDK, or MCP, so every new interaction builds on the last instead of starting over. Reuse memory across ChatGPT, Claude, Gemini, OpenClaw, Hermes, Cursor, Codex and more
On the analytics side, Living Brain competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.7M followers on Product Hunt. The dashboard above tracks how Living Brain performed against the three products that launched closest to it on the same day.
Who hunted Living Brain?
Living Brain was hunted by Ben Lang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Ben Lang
Hey Product Hunt 👋 I’m Christel, founder of ChatAndBuild, and I was part of Twitter's first international team.
We have built the Living Brain - a model independent, harness independent, efficient brain that travels with you across any AI platform.
Living Brain gives your AI tools a shared, persistent memory. It turns your notes, documents and conversations into connected knowledge that you can inspect, update and reuse across compatible assistants and agents.
For example, save a project brief, customer requirements and the decisions behind your roadmap in one brain.
Connect it to your AI tools, and they can retrieve that context when you ask them to work on the project.
With Living Brain, you can:
🧠 Build a memory around your work, projects and preferences.
🔗 Reuse that memory across ChatGPT, Claude, Gemini, OpenClaw, Hermes, Cursor, Codex and more
🛠️ Give your own apps and agents persistent context through our API.
📚 Review the organised knowledge and the sources behind it.
We’re measuring how accurately AI can use that memory, alongside how much context it needs.
Our latest internal evaluations show:
We're #1 on LoCoMo with 92.2% judged accuracy, answering 1,420/1,540 questions correctly with approximately 63.8% less context.
Those context reductions compare average retrieved memory with the displayed full-history references — approximately 9.4K versus 26K tokens on LoCoMo, and 5.1K versus 115K on LongMemEval-S.
We want you to choose each AI for what it does best, with your accumulated context coming along.
We’re building this for people who use several AI tools, teams whose context is scattered, and developers building agents that need continuity.
I’d love to hear from you. What’s the one thing you’re tired of explaining to AI over and over?
Tell us your workflow. I’d love to see where Living Brain could help, and where we still need to improve.
— Christel