What Pumaï does,
in practice.
One foundation — memory, action, autonomy, governance — shaped into very different roles. For developers, integrators, AI makers, automation consultants and small teams who want agents that actually run.
Answer, draft, send
A profile that answers, drafts, researches, and sends — with memory of files and the people it deals with.
Monitor and alert
An autonomous agent monitors sources and alerts by email as soon as a new fact appears. A workflow already proven in production.
Set a heading, let it advance
You set a goal (campaign, topic tracking, collection); the system advances alone and proposes actions to validate.
A living knowledge base
Ingest documents and logs into a partitioned knowledge base, queryable in natural language.
Qualify and create tickets
An agent that takes requests, qualifies them, creates tickets in your tracker and replies — sensitive cases go through approval.
Check services, read logs, propose
It checks service health, reads logs, correlates signals and proposes actions — never executing them without your go-ahead.
Answer the phone
Through the Twilio gateway, it answers calls, takes a message, qualifies the request or triggers a workflow — and can call back too.
Ship reliable tools fast
A team designs, tests and versions new agentic tools fast in a sandbox, then wires in internal MCP connectors.
Continuous learning — the "live logger". A daily feed of user data (activity, events, measurements) becomes a learning source: the AI queries it on demand, and the nightly dream automatically extracts what's durable. Pumaï doesn't just store — it infers.
search_memory)