Side by side
Competitor claims last verified 1 November 2026| Dimension | NOAN | Mem0 |
|---|---|---|
| Purpose | Holds your company's own approved facts, like prices, policies and product details, so every agent reads the current version | A memory layer for AI agents and apps that keeps what users and agents said across sessions |
| Source of truth | One current fact per block, written and verified by your team. A new version supersedes the last | Facts, preferences and plans an LLM extracts from the messages you send. New memories are added without overwriting existing ones |
| Who verifies | A named person on your team. Facts an agent writes can wait for a person to verify them before anything reads them | Its docs describe no review step. Apps can send feedback ratings to improve memory and search quality |
| Versioning and history | Every version kept, with who verified it and when. Time Travel shows your facts as they stood on any past date | A History API records each add, update and delete for a memory, with timestamps |
| Permissions | Roles and fact permissions decide who sees and edits each area. Each API key is scoped further: read or write per resource, a list of allowed stacks, and fact changes held for approval | Memories scoped by user, agent, app and run. The hosted Platform adds organizations and projects with reader and owner roles |
| How agents access it | Remote MCP server (OAuth or an API key), REST API with an OpenAPI spec, and an open Agent Skill. Plain JSON from any language, no SDK needed | REST API, Python and JavaScript SDKs, a hosted MCP server, and integrations such as LangChain, CrewAI and LlamaIndex. Open source under Apache 2.0 |
| Where it fits | Under the conversation: the approved answer about your business that every agent gives | In the conversation: what this user prefers and what this agent learned last time |
When to choose Mem0
- Your agent should remember each user: preferences, history and what they asked last time
- You want memory to build itself from conversations, with no one curating it
- You want an open-source memory library you can self-host, with Python and JavaScript SDKs
- Memory should plug into a framework you already use, like LangChain, CrewAI or LlamaIndex
When to choose NOAN
- Agents quote your prices, policies or product details to customers, and the answer has to be the approved one
- You need to show who verified a fact, when, and what it said before
- Many agents, apps and your website should read the same facts, and one change should reach all of them
- Facts an agent writes should wait for a person to verify them
The deeper comparison
Memory recalls what was said. NOAN holds what was decided.
Mem0's docs describe an LLM that pulls facts, preferences and plans out of the messages you send, and stores them so an agent remembers next time. New memories are added without overwriting old ones. For memory, that is exactly right: a preference a user mentioned last month is still useful context today.
It is a different shape from your price list. When the Team plan changes, you don't want the old price kept beside the new one for a model to weigh. In NOAN, a new version supersedes the last. The old version is kept for history, and only the current one is served as true.
Who stands behind the answer
Mem0's History API records each change to a memory and the input that caused it, which is useful for debugging what an agent remembered. NOAN records something else: which person on your team verified each version of a fact, and when.
That matters when an agent tells a customer something. If someone asks where a number came from, the answer is a fact, a version and a name, not a conversation an LLM summarized.
Using Mem0 and NOAN together
Memory for the conversation, NOAN for the approved facts. The agent reads Mem0 for who the user is and what they discussed, and reads NOAN for what your company says is true about its products, prices and policies.
Add one rule to the system prompt: when memory and NOAN disagree about the business, NOAN wins. Both offer MCP servers, so an agent in Claude, Cursor or Codex can connect to both.
Common questions
Is NOAN an alternative to Mem0?
Not really. Mem0 gives agents memory of users and past sessions. NOAN gives them your company's own verified facts. They solve different problems, and many teams run both: Mem0 for the conversation, NOAN for the approved answers.
Can I use Mem0 as the source of truth for my company's facts?
Mem0 stores what an LLM extracts from conversations, and its docs describe adding memories without overwriting old ones and no human review step. That suits memory. For approved facts like prices and policies, where one current version should win and a person should stand behind it, a fact layer such as NOAN fits better.
How do I give my AI agent verified facts about my company?
Put your company's own facts in NOAN, where your team verifies each one and every version is kept. Connect the agent over the remote MCP server at https://mcp.getnoan.com/mcp or the REST API at https://api.getnoan.com/v1.
Does NOAN remember conversations?
No. NOAN holds facts your team has verified, not chat history. Pair it with a memory layer such as Mem0 if your agent needs to remember users.
Sources: Mem0: how it works · Mem0: adding memories · Mem0: memory history · Mem0: scoped memory · Mem0: MCP · Mem0 on GitHub · This page as Markdown · All comparisons
Next step
Connect your agent to verified facts
A remote MCP server for your company's own facts. Sign in over OAuth or send a NOAN API key. Install steps for Claude, ChatGPT, Cursor and Codex.
Plain REST with a bearer key, JSON in and out, from any language. Every endpoint is in the OpenAPI spec.
Or tell any agent: Read https://www.getnoan.com/setup.md and follow it.
See the fact layer with your facts in it
Every plan includes the API and MCP, and paid plans add unlimited keys. Start with one verified fact and build from there.