RetainDB gives your AI agents persistent memory — so users feel understood from session one, never repeat themselves, and keep coming back. Most teams are live in under 30 minutes.
It doesn't remember their preferences. It doesn't know they've explained their setup twice already. It just starts over.
Your users notice — even if they never say it. There's a low-grade friction to re-explaining context that should already be there. And slowly, quietly, they use your product less.
Users stop re-explaining their plan, their history, what they've already tried. The agent picks up exactly where the last conversation ended.
It knows your constraints, your preferences, what you've already rejected. It compounds knowledge instead of losing it session to session.
What's been covered, what was useful, what was a dead end — all carried forward. Research compounds instead of resetting.
Every interaction, objection, and outcome is remembered. The agent knows what was discussed and what to say next.
Every agent type benefits differently. Pick your domain and see what becomes possible when your agent remembers.
They reach out once and your agent already knows their history, plan, and what they care about. No more "can you describe the issue again?" — just fast, warm resolutions.
See how it worksEvery resolved ticket makes the next one faster. Your agent learns from every customer it helps, compounding into a support experience your competitors can't replicate.
See how it worksWhen a human takes over, full context travels with them. Your customer never has to repeat themselves. The conversation just continues.
See how it worksPlug into your existing stack. No infra to manage, no RAG pipeline to build. Three steps — and your AI never forgets again.
Every conversation is stored automatically. Next session, your agent already knows who the user is, what they've shared, and what matters to them.
Before every response, RetainDB pulls exactly what's relevant from that user's history. Your agent gets the right context without the cost of replaying every conversation.
The right context flows into every response automatically. Your AI becomes the assistant that actually listened — users feel remembered, not just handled. One call wraps all three steps if you want it even simpler.
We ran the tests and published every result — no cherry-picking.
LongMemEval · hallucination test · March 2026 · methodology published
Highest preference recall on the academic memory benchmark — the category that matters most for personalised agents.
See full results & methodology16 real SDK questions. Temperature 0.0. Without RetainDB, GPT-5 hallucinated on 89% of them. With RetainDB grounded to your docs — zero.
Correct retrieval across all test cases. 12/12 successful source retrievals across 39 real files.
Every question in the matrix looks like this — not cherry-picked. Without grounding, the model confidently invents an API that doesn't exist. With Retaindb, it pulls from your actual docs.
Full benchmark methodologyHere's the honest comparison. No marketing spin.
Most teams who try to build persistent memory in-house underestimate what it actually takes. Deduplication across sessions. Semantic retrieval that doesn't degrade. Per-user isolation. Token-efficient injection under 40ms.
That's 4–8 weeks of engineering work for a first version — and months more to harden it. RetainDB is that layer, already built and tested at scale.
On the academic benchmark for AI memory, RetainDB scores highest on preference recall — the test that measures whether your AI remembers personal details and context across conversations. 88% vs. the field's 70%.
RetainDB does not use your data to train models. Your users' memory belongs to you. You control what gets stored, retrieved, and how long it's retained.
Your current agent starts every session from zero. Your users feel it — even if they haven't put it in words. Churn from agents that feel impersonal is harder to attribute than a broken feature. But it compounds just as fast.
RetainDB is built for teams where data ownership isn't negotiable. Every user's memory is stored in isolation — no cross-contamination, no shared retrieval, no way for one user's data to surface in another's session.
Enterprise enquiries →Three ways to add memory — pick the one that fits. SDK for full control. MCP for any agent tool, no code needed. Memory Router to drop in front of your existing LLM calls without changing a line.
Install, initialize, and your agent has persistent memory. JS, Python, and Go out of the box. Most teams are in production the same day.
Connect RetainDB as an MCP server. Claude, Cursor, or any MCP-compatible agent instantly gets persistent memory and recall — one config line, no SDK, no build step.
Swap one URL. RetainDB intercepts your LLM calls, injects the right memory automatically, and forwards to OpenAI or Anthropic. Your existing code stays exactly the same.
The questions teams ask before they ship with RetainDB. Honest answers, no marketing speak.
The difference between an agent people tolerate and one they love is often this simple: does it remember them? RetainDB is the fastest way to answer that question with yes — for every user, from the very first session.
Most teams go from zero to production memory in under 30 minutes. Free to start. No infrastructure to manage.
These are the pages at the center of the new memory, context, and comparison cluster.
The core landing page for persistent memory and user continuity.
The context-engineering page for retrieval, memory, and state assembly.
Proof for the memory claims and published March 2026 benchmark results.
A high-intent comparison page for buyers evaluating memory layers.
A buyer-facing comparison that connects product narrative to proof.
A direct comparison against another benchmark-heavy memory and context competitor.
Useful for buyers deciding between memory layers and context infrastructure.
The educational guide for teams implementing memory the first time.