Product · AI chatbot
Upload what you know, then ask questions the way you would ask a colleague who has read everything. The answer is the value you stored, with the record it came from.
Available on every plan; Free has a limited monthly allowance.
Choose your chat app
The memory is the same whichever way you reach it. Pick the interface that fits how you work, and switch or combine them later without moving any data.
1 · Dorothy
Dorothy is Panaxon AI's own chat app, built for this memory. Sign in, upload your documents and spreadsheets, and start asking. Use it in your browser or install the desktop app.
Plans: every plan.
Download Dorothy →2 · A third-party chat app
Connect M.N.E.M.O. to a chat app you already use through MCP, the open standard for giving an AI app tools. The app can then remember things in a conversation and recall them in any later one. It works with Claude (Claude Desktop and Claude Code) and ChatGPT, and with other apps that support MCP (ChatGPT needs a plan that allows custom MCP servers).
Plans: Standard and above. You sign in once to connect; no API key needed.
MCP setup steps →3 · Your own chat app
Put the memory behind your own chat interface, support bot or internal assistant. Call the REST API for ingest, chat and recall, or connect your own agent over MCP, and keep full control of the experience.
Plans: Standard and above (needs an API token).
API details →AI chatbot
Dorothy, Panaxon AI's chat app, is the chatbot built on M.N.E.M.O. You upload what you know, then ask questions the way you would ask a colleague who has read everything. Because retrieval is exact rather than a similarity guess, the answer is the value you stored, with the record it came from, and a number such as a total or an average is computed by the memory itself, never added up by the language model.
In real life
Illustrative scenarios, not customer stories.
They upload the quarterly sales export and ask, "What was the total revenue for Asia Pacific in Q1?" The memory sums the matching rows and returns one exact figure, with no spreadsheet filters and no rounded estimate. Next week they ask for the average deal size on the Partner channel in the same conversation.
After loading the ticket history, they ask, "Which agent resolved Harborview Logistics' ticket about the Zenith product, and what did they do?" They get the agent, the fix and the ticket it came from, instead of paging through the helpdesk.
Meeting notes, scope changes and approvals go into one subject per client. Months later: "What did we agree about the data migration deadline?" The answer is the stored decision, not a summary that drifts.
With the employee roster loaded, "Who works in Engineering and what are their roles?" lists every matching record, not just the five closest matches. On Pro and above, role-based access rules can keep a salary subject out of reach for everyone who shouldn't see it.
Same memory, other doors
Whatever this feature can see, the other two can see too, so you can add them later without re-uploading anything.
Publish a subject; others subscribe and ask.
Learn more →One stateless call from your own pipeline.
Learn more →Next step
Choose a plan, or talk with Panaxon AI about your use case.