AI should work inside the software your team already uses
Aima started with a practical problem. Businesses were ready to use AI, but their records lived in local, regional, or in-house systems with no public API.
The problem we work on
AI is useful when it can see the current record and leave the result where the team works.
A clinic may keep appointments in a local booking system. A property team may work from an internal database. An accounting team may rely on software with no public API. Those systems still hold the information that determines what happens next.
Aima connects the conversation to that record. Agents can check context and take the actions an organization approves, then write the outcome back into the existing workflow.
What we build around
Local systems
Booking, clinic, property, accounting, and in-house systems often sit outside global integration catalogs. They still run the business.
Approved actions
A connector gives an agent a defined way to read context and take the actions an organization allows.
Real conversations
WhatsApp and phone agents handle the conversation, then return the result to the system the team already trusts.
How the product took shape
Software without a public API
Teams wanted to use AI, but the software holding their appointments, records, and operations could not connect to a standard integration.
Turn the system into a usable tool
Aima maps the system into a connector with the reads and actions an agent needs. The source of truth stays where it is.
Put the conversation in front of it
WhatsApp and phone agents can now use that context during a conversation and return the result to the team's existing system.
"AI should be able to use the system that holds the work."