Blog·News

Supermemory raises $3 million with the best memory engine for LLMs

By Dhravya Shah·3 min read

Supermemory funding banner showing "PRE-SEED $3M" led by Susa Ventures, with Browder Capital and SF1

Today, I am excited to announce our first funding round to accelerate our mission of building an interoperable, scalable and reliable memory for LLMs and agents.

Memory is one of the hardest challenges in AI right now. We have really intelligent models (Claude, GPT-5, etc) and tools (Cursor, and many others), and I genuinely believe that the next hard frontier will be personalization. And that's the problem we're solving at supermemory - self-learning context about your users that is interoperable any model.

It all started as a consumer app built over the summer last year - to help humans organize the knowledge they collect on various apps. At the time, Supermemory was not trying to be a business. It was an open-source "second brain" app that users loved. We quickly reached 50k+ users, millions of items saved by these users, and 10,000 stars on Github, and it was one of the fastest growing OSS projects in 2024. Very quickly, this side-project turned into a real business.


At scale, the consumer app ran into many issues - and to our surprise the infrastructure for "Memory" for LLMs like this simply didn't exist. I had some experience in infrastructure and started sharing more details on how we were building the infrastructure behind the consumer app ourselves.


At the time, I was working on AI infrastructure at Cloudflare, where we filed a patent to make agents faster. I worked at startups working on memory, made multiple consumer-led apps, and much more. Doing this, I realized the real problems with memory - it's not just a search problem, it's about really understanding the users and making their experience magical by contextualizing the LLMs they talk to.

While many loved the consumer app, and the project won the buildspace grant, among many others, a lot of interest came from companies wanting this infrastructure for their products. Many were ready to pay right away, and many offered contractual or consultancy work for help with setting up the open-source project, and that's when we decided to open up the infrastructure for everyone to use.

We built our own vector database, content parser and extractor, and a lot of infrastructure components were built from scratch, purpose-driven for being a flexible, scalable memory layer that works like the human brain.
After all this work, Supermemory managed to top every benchmark and extremely scalable while providing some of the best latencies in the market.

Today, we have the best, scalable and fastest memory engine.

Ever since then, our customers have been loving supermemory in every way. Today, some send us many billions of tokens every week, and our product is loved by enterprise customers like Cluely, Composio etc. as well as open source projects like Scira AI.

Today, I am excited to announce the next chapter of supermemory - We have raised $3 million dollars led by Susa Ventures (Shaheer), Browder Capital, SF1.vc, with participation from top angels like Dane Knecht (CTO Cloudflare), Theo Browne, David Cramer, Julian Weisser at Solo founders program, and others leading in the space of infrastructure and AI.

We are hiring across engineering, research and product roles. Join us in the journey of creating the best memory engine on 🌎

  1. An update to supermemoryWe've discontinued the supermemory company brain and Nova. Everyone who was charged has been refunded, our MCP and plugins continue to run, and we're going all in on the memory engine.
  2. SMFS: making agentic retrieval 55% cheaper AND more accurateWe launched SMFS.ai (Supermemory Filesystem) a few weeks ago, with a simple bet: We can redesign the filesystem specifically for agents, with special files, structures, and commands that it can use for it's tasks. Today, SMFS is used by hundreds of companies to power their agents.
  3. Introducing Dynamic Dreaming: supermemory now connects the dots, for you.Dreaming is magical. TLDR: We're launching Dynamic Dreaming in supermemory today, which automatically works if you're using supermemory in any way - API, OpenClaw, Hermes agent, etc.
  4. Dear reader, we just made supermemory insanely cheap... the Context CloudWhen I first started building supermemory, I had one goal: To build the best memory system for AI. I would talk to customers, and find out that memory was not the only thing they needed - They were all setting up 7-8 different vendors at the same time.
  5. Introducing @supermemory/tools v2.0.0Today we're releasing v2.0.0. This release unifies the API across all agents sdk integrations from AI SDK to Mastra, makes conversation identity a first-class concept, and ships with memory saving on by default.
  6. supermemory will make your Hermes-agent crazy powerfulToday, we are launching supermemory support to your Hermes agent TLDR: you can use supermemory now in your Hermes agent, it totally free to get started - https://supermemory.ai/docs/integrations/hermes In case you missed it: Hermes Agent is a self-improving AI agent from Nous Research.
  7. Solving the Precision-Recall Tradeoff: Search Result AggregationWhen you're building memory for AI, search is your foundational layer. The way search generally works is straightforward: the user defines a query, and then sets a limit (top-K) on how many search results they want returned. Usually, this is set to 10 or 20.
  8. Infinitely running stateful coding agentsWe built a plugin for Claude Code and OpenCode that gives your coding agent persistent memory. It remembers your preferences, learns your codebase, and never loses context mid-conversation. The result is an agent you can run for months without starting over.
  9. Why everyone is complaining about OpenClaw's memory (it sucks) - and why supermemory fixes it.TLDR: Today, we are releasing a new version of our openclaw plugin - https://github.com/supermemoryai/openclaw-supermemory. This post is going to be a bit technical, so bear with me (or bookmark for later!) In this post, I will talk about what we do about OpenClaw memory, and how we fix it.
  10. We added supermemory to Claude Code. It's INSANELY powerful now...Today, we are launching the Supermemory plugin for Claude Code! TLDR: You can use supermemory in claude code now. - https://github.com/supermemoryai/claude-supermemory Claude code has genuinely changed how I work. But there's this one thing that drives me crazy...
  11. Clawd / Molt bot's memory SUCKS. We gave it supermemory.I'm the founder of supermemory. Clawd/Molt bot is blowing up right now, with many, many use cases. I set it up, too, and have been using it through telegram. TLDR: just go to https://supermemory.ai/docs/integrations/clawdbot to set up supermemory for your clawd bot.
  12. Catch up with our UNFORGETTABLE Launch WeekOver the last year, one belief has guided almost everything we’ve built at Supermemory AI becomes meaningfully useful only when it remembers. Memory shouldn’t be something developers rebuild from scratch. It shouldn’t be fragile, expensive, or trapped inside a single tool.
  13. Empowering the Next Generation of Founders: Supermemory Startup ProgramIf there’s one thing we’ve learned while building Supermemory, it’s that most startups don’t fail because they didn't build features; they fail when infrastructure slows them down, or they built too slow.
  14. Building code-chunk: AST Aware Code ChunkingAt Supermemory, we're building context engineering infrastructure for AI. A huge part of that is dealing with code: ingesting repos, understanding structure, and making it searchable. The problem is that most code chunking solutions are terrible. We built code-chunk to fix this.
  15. Unified Memory That Works Where You Work: Your Second Brain With SupermemoryHi everyone, I’m Dhravya, the founder of Supermemory. I want to start with a little story behind why this product means so much to me. You can also skip straight to what it is and how it works below.
  16. Supermemory just got faster on PlanetScaleWhat is Supermemory? Supermemory completes the missing part of the LLM puzzle: memory. Just as memory is crucial for human intelligence, it's essential for truly intelligent AI systems.
  17. Faster, smarter, reliable infinite chat: Supermemory IS context engineering.People are obsessed with prompts and prompt engineering. Sure, what you say is important, but what the model knows when you say it is the difference between a stateless text generator and an intelligent AI system. In short, context is the most crucial component.
  18. We solved AI API interoperabilityOne API to rule them all, One spec to find them, One library to bring them all and in the TypeScript, bind them. When we were building the the Infinite Chat API, initially, we only supported the OpenAI format. This was fine, until a lot of our customers started asking, asking for more.
  19. The UX and technicalities of awesome MCPsLast month, we launched the Supermemory MCP, mostly to test our own infrastructure and get some initial traction. It blew up. To my absolute surprise, the initial launch itself got half a million impressions (!!!). Then, we launched and got #2 on ProductHunt too.
  20. Architecting a memory engine inspired by the human brainLanguage is at the heart of intelligence, but what truly powers meaningful interaction is memory — the ability to accumulate, recall, and contextualize information over time. Large Language Models (LLMs) have mastered language, but memory remains their Achilles’ heel.