Customer data
CRM
Most CRMs are a database with a form in front of it. The AI ones bolt a chat box onto the side of that form.
The problem
The expensive part of a CRM was never the storage. It is that keeping records true is manual work, so it does not get done — contacts go stale, deals sit in the wrong stage, and the person who knew the context left.
Adding a chat assistant to that does not fix it, because the assistant only runs when somebody remembers to ask it something.
What we built
The agent runs whether you are there or not
Research runs against its own work queue on its own schedule, deciding what to look at next and booking its own follow-ups. Closing the browser does not stop it.
Nothing about a person is guessed
The agent is constrained to write only what it can source. An enriched record is one it found evidence for, not one it inferred — which is what makes the data safe to act on.
A research budget with a floor
The agent spends against an explicit budget and stops when it runs out, so unattended research cannot quietly become an unattended invoice.
Connected to everything else
Deployed alongside the rest of the stack so lead flow, outreach and pipeline live in the same place rather than in three disconnected tools.
How it works
- Something happens — a thread is ingested, a company appears, an attendee is unknown.
- The API records that an event occurred, without interpreting it.
- The agent leases the event off the queue and decides what it means.
- It researches, writes what it can prove, and schedules its own next look.
At a glance
Built on the MIT-licensed open-source CRM from Comp AI. Tropika Labs runs, hosts and integrates the deployment rather than having authored the upstream project.
Want something like this?
We build production software for other people too — this is just what we build for ourselves.
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