Enterprise AI needs a memory, not another chatbot
Most companies now run more than one AI tool. A support assistant. A coding agent. An internal helpdesk bot. A few scripts someone built on a Friday.
Each one starts with an empty head. Each one is told the same things again: who owns what, what the policy is, what the customer said. And none of them learns from the others.
That is the gap Eunomia fills.
One memory layer for every internal AI tool
Eunomia is shared, long-term memory for a company's AI.
- What you know goes in once. Staff, documents, email, calendars, tickets and code flow in through connectors, or agents write facts as they work.
- Every tool reads the same thing. Agents connect over MCP. Your own apps use the REST API or the Python and TypeScript SDKs.
- Memory gets better over time. Raw facts about a person, project or customer are folded into one up-to-date belief, so answers stay current.
Use cases
Internal staff and context
A new hire's assistant already knows the team, the tools and the past decisions. Nobody writes the same onboarding doc twice.
Internal tooling
The helpdesk bot, the ops agent and the reporting script all recall from the same vaults. When one learns that a vendor changed terms, the others know too.
Internal memory for software teams
Coding agents keep a small memory in each repo and share the big picture through Eunomia Cloud. See Projects.
The whole business, mapped
For large operations, we model the business end to end so agents and managers can see where work gets stuck. See Ontologies.
Your own AI product
Building an app with AI inside? Use the SDK to give it memory per customer, per team or per user, without building a memory system yourself.
Built for how enterprises work
| Need | How Eunomia handles it |
|---|---|
| Keep teams' knowledge apart | A vault per team, project or client, with owner and member roles |
| Limit what each tool can touch | Tokens scoped to one vault or to read only, with an expiry |
| Know who changed what | Every write is in the audit log |
| Keep data in-house | Self-hosted, and each org gets its own database |
| Use any model | Works with the agent's own model; an OpenAI-compatible endpoint is optional |
Memory is the layer, not the app
End-to-end AI platforms try to be the whole stack: the agents, the chat, the workflows and the data. That locks your company's knowledge inside one vendor's product.
Eunomia does one job: memory. It sits under whichever agents, tools and models you choose, today and next year. Swap the chatbot. Keep what it learned.
Want one memory for your company's AI? Get in touch with the Eunomia team.