SurrealDB is a Rust multi-model database and context layer for AI agents: documents, graphs, vectors, time-series, and relations are native in one ACID engine, no stitched stores. Query with SurrealQL, connect via MCP, WebSocket, and SDKs, with GraphQL generated from your schema. Built-in auth, permissions, HTTP APIs, and live queries reduce separate backend glue. Runs embedded, at the edge, or as a highly-scalable cluster in the cloud. Same engine, everywhere.
This is the 2nd launch from SurrealDB. View more
Spectron
Launched this week
Spectron is agent memory built on one ACID substrate. Graph, vectors, documents, and structured rows commit in one transaction. Every fact carries provenance. Corrections supersede, never overwrite. Hybrid retrieval fuses vectors, graph, BM25, and keywords. Traces feed back into ranking. Tri-temporal facts, multi-tenant scopes, and MCP support. No stitched stores. No sync pipelines.
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Launch Team
Sounds amazing, I was already in the process of designing a similar memory layer on top of SurrealDB for my project where I need agents to remember same as humans do but then saw this was getting out soon. I am eagerly awaiting access so I can start testing implementation with Spectron.
Watching the promo video and reading through the docs I see that's exactly I was trying to achieve, structured memory data, all timestamped so agents do reason through time which is highly important for my product.
SurrealDB has already been my go-to database for all my projects for quite some time, love the experience using it and been making lots of projects on top of it, amazing work what this team has accomplished.
SurrealDB
This is one of my favourite kinds of comment to get, @msanchezdev, thank you. The fact that you were already building this on SurrealDB yourself tells me we were thinking about it the same way: agents should remember the way humans do, and that means structured, timestamped memory you can actually reason through over time rather than a flat log.
That "reason through time" point is exactly the part we obsessed over, so it's great to hear it's landing with someone who needs it for a real product. Hopefully Spectron saves you building the layer yourself, and you can spend that effort elsewhere.
And genuinely, thank you for being a long-time SurrealDB user; that loyalty means a lot to the whole team 💜. Get yourself on the waitlist and we'll make sure you're in early. Would love to hear how it holds up against what you had in mind 🎉.
Lancepilot
SurrealDB
Spectron is our memory and knowledge layer for AI agents, built on top of SurrealDB. The idea is to give agents reliable, shared memory that can work across your stack, tools, and applications, rather than having context scattered across separate systems.
It comes with integrations and SDKs for TypeScript, JavaScript, Python, Swift, Kotlin, LangChain, LangGraph, n8n, and a growing set of MCP server integrations that work with tools like Claude, Codex, Cursor, and more out of the box.
What makes Spectron especially powerful is its focus on authoritative knowledge. It is designed to help agents understand what they know, where that knowledge came from, how it has changed over time, and whether an answer is grounded in the underlying data.
So whether you are building internal agents, customer-facing AI apps, or developer tooling, Spectron gives you a trusted memory layer that can grow with your ecosystem.
SurrealDB
Well put, @at_chiru 🙌
The line I'd underline for anyone skimming is "whether an answer is grounded in the underlying data". That's the part most memory layers quietly skip; they'll happily hand an agent a fact with no notion of where it came from or how confident to be in it.
Spectron treats provenance and grounding as first-class: every fact carries its source down to the byte span it came from, knows when it was true and when we learned it, and is honest when the answer is uncertain rather than confidently wrong. For anything customer-facing or high-stakes, that difference between "the model said so" and "here is the data this is grounded in, and here is how sure we are" is the whole ballgame.
A trusted memory layer that grows with your ecosystem is exactly the right way to put it; trust is the feature, and everything else is in service of it 🎉.