We live in extraordinary times. AI can now write complex software from natural language prompts, solve IMO problems, analyze thousand-page contracts in minutes, and guide you through learning practically anything. We’ve blown past the Turing test and built intelligence that matches or beats human capability across many domains.
Yet these same systems suffer from a fundamental flaw: they can’t truly remember anything. Sure, individual chat sessions can recall earlier messages. But real memory—the kind that builds deep understanding over time, transfers seamlessly between contexts, and enables genuine personalization—remains elusive.
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Most interactions still start largely from scratch. Users paste the same context into ChatGPT over and over. They watch coding assistants suggest the same rejected patterns dozens of times. They re-explain their preferences to customer support bots that helped them yesterday. Our most sophisticated intelligence is trapped in digital amnesia.
The agentic future depends on solving memory. But when developers try to build it themselves, they discover it’s far harder than expected.
That’s where Mem0 comes in. With just three lines of code, developers can transform stateless agents into systems with powerful personalization. Since launch, thousands of developers, startups, and enterprises have trusted us with their memory needs in production.
Today, we’re announcing our $24M raise across Seed and Series A. Our Seed round was led by Kindred Ventures, and our Series A was led by Basis Set Ventures, with participation from Peak XV Partners, GitHub Fund, and Y Combinator. We’re also backed by an incredible group of angel investors including Scott Belsky, Dharmesh Shah, and the CEOs of companies that have built core infrastructure at scale—Olivier Pomel (Datadog), Paul Copplestone (Supabase), James Hawkins (PostHog), Thomas Dohmke (ex-GitHub), and Lukas Biewald (Weights & Biases).
Memory is deceptively hard
When developers realize their AI applications need memory, their first instinct is to build it themselves. It seems straightforward: store interactions, retrieve relevant context. A weekend project at most.
Then reality sets in. Simple semantic search fails to preserve nuanced context. New preferences clash with old ones. Recent information gets buried under stale data. Duplicates multiply. What starts as a simple project becomes months of engineering work tackling problems that only surface at scale.
Every hour spent wrestling with memory infrastructure is an hour not spent on what actually matters: building exceptional experiences for users in your domain.
Behind this simple API, we handle the complexity of memory at scale. We extract memories from interactions, categorize them, layer in metrics like decay and confidence, and update them intelligently when conflicting facts emerge. During retrieval, we use sophisticated algorithms that make sense of these factors and surface only the relevant memories in the context of the interaction. Put simply, we take care of all the messy details you don’t want to.
Since launching, we’ve crossed 41,000 GitHub stars and 14 million Python package downloads. Our API calls are growing exponentially—from 35 million in Q1 to 186 million in Q3 this year.
Beyond the numbers, Mem0 has gained wide adoption. Thousands of teams, from the fastest-growing startups to Fortune 500 companies, use us in production. Major agentic products like CrewAI, Flowise, and Langflow integrate Mem0 natively. AWS selected us as the exclusive memory provider for their new Agent SDK.
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