Mnemo API
Mnemo is Panaxon AI's core product: structured, indexed memory infrastructure for AI agents. Dorothy is one thing built with it — not the only thing it can do.
The problem
Imagine a travel agency. A customer books a trip in March, has a hotel issue in April, and calls back in July about a new booking. Today that usually means digging through email threads, CRM notes, and call logs — or asking the customer to repeat their whole history again.
With Mnemo
Every past booking, preference, and open issue is memory the agent can recall exactly — not a chatbot guessing from a similar-looking document, but a lookup that returns the actual stored facts: the itinerary, the seat preference, the refund that's still pending.
Why Mnemo
What you get
API access to the same memory engine Panaxon AI builds on.Ingest documents and structured data, then recall or query it through a REST API designed for long-lived, multi-session agent memory.
In practice
Your business doesn't have to be a travel agency for this to apply. Any team whose agent needs to remember a specific customer, case, or record exactly — a support ticket, a client account, a claim — runs into the same wall: memory built for a single conversation, not a real relationship. Mnemo is infrastructure for that pattern, not a finished vertical app. In practice, that looks like:
Any AI agent that needs to remember across sessions — not just within a single conversation window — can use Mnemo as its persistent memory layer.
Because retrieval is indexed and exact rather than approximate, questions over ingested spreadsheets or records can return precise values, not paraphrased summaries.
A support tool could ground every conversation in a customer's full history — past interactions, preferences, prior issues — without asking them to repeat it.
Per-tenant isolation and role-based access rules make it possible to keep sensitive data scoped to the right roles as memory is shared across a team.
Share model
You have knowledge - documents, notes, expertise - that people in your circle, or the public, would benefit from. Today that often means sending files, answering the same questions repeatedly, or hoping someone reads everything you wrote. With Mnemo, they just ask instead.
A person, team, or company can publish data to Mnemo once. People who subscribe can query it through Dorothy chat, or through their own app connected via the Mnemo API, like asking someone who already knows the answer.
Access is never automatic. Other Mnemo users explicitly subscribe first - similar to following someone on Instagram or Facebook. Circle-only data is shared with chosen people; public data can be subscribed to by anyone. In both cases, visibility starts only after explicit opt-in.
Mnemo is the subscription and access layer, not the publisher and not the source-of-truth authority. The person or company publishing the data owns and is responsible for it. Subscribers know whose data they are querying.
This model supports both peer sharing (your circle) and public sharing (anyone who explicitly subscribes). The same publish flow serves both, with access rules set by the publisher.
Publishing flow
Use a separate flow for publishing knowledge, distinct from API integration.Proof of concept
Dorothy is Panaxon AI's own reference application — a conversational interface that shows what persistent, structured memory feels like day to day. It is one example of what the API can power, not a limit on what you can build with it.
Try it live
See Mnemo's memory in action in a live chat app.
Next step
Talk with Panaxon AI about API access to Mnemo.If you are building agents, copilots, or memory-heavy context pipelines, Panaxon AI can discuss fit, architecture, and access.
