How to choose a memory layer: MemoryFirst vs the alternatives
Mem0, Supermemory, Zep, MemoryFirst. They all promise 'memory for AI'. The differences that actually matter: where your data lives, whether you can audit answers, and whether you can self-host.
The "memory for AI" space filled up fast. Mem0, Supermemory, Zep and others have done good work putting the problem on the map. If you're evaluating options, the mistake is to compare on surface features. Compare on the decisions that are hard to reverse.
The four questions that actually matter
- Where does the data live? A memory layer sees *all* of your user's context. Data residency isn't a compliance footnote: it's the most expensive architectural decision to change later.
- Can you audit the answer? If memory returns "the client prefers quarterly billing" but can't show you where that came from, it isn't memory: it's a hallucination with a good reputation.
- Can you self-host? For many teams — healthcare, legal, public sector — a multi-tenant SaaS in another jurisdiction is a hard no, however elegant the API.
- How does it stay current? Facts change. A layer that returns both the old and the new rate hands the conflict-resolution problem back to you.
How MemoryFirst positions
We won't make up competitor numbers. What we can tell you is where we put the focus:
| Axis | MemoryFirst's approach |
|---|---|
| Data residency | Self-hostable, EU infrastructure (Hetzner). No single-cloud lock-in. |
| Auditability | Every answer includes citations to the original source (paragraph, minute, message). |
| Interface | OpenAI-compatible API + MCP server (stdio/HTTP/SSE). No SDK lock-in. |
| Retrieval | Dense + BM25 + graph, RRF fusion, cross-encoder reranking. |
| Currency | Resolves toward the most recent truth on contradicting facts. |
| Privacy | We never train on your data. GDPR by default, DPA available. |
When we are NOT the right choice
Honesty first: if you want a fully managed SaaS, zero infrastructure, and data residency doesn't matter to you, one of the cloud alternatives will give you a faster time-to-hello-world. That's their strength.
MemoryFirst wins when trust is part of the product: when your users operate in regulated sectors, when you need to show the source of every answer, or when self-hosting is non-negotiable.
Don't choose a memory layer by its demo. Choose it by the decisions you can't undo: where the data lives, and whether you can prove what the AI claims.
How to evaluate it seriously
- Load your *real* documents, not the toy dataset.
- Ask a question whose answer changes over time, then ingest the update. See if it returns the old, the new, or both.
- Ask for the source of three answers. If it can't give you one, you have your answer.
You can try all of this with the API or the MCP server.
Give your agents a memory.
The memory layer for AI: OpenAI-compatible API + MCP, with citations and EU data.
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