Integrations and AI builds
Agents running in production on live client accounts, and the connectors that let them reach your systems.
Our process
Versioned, documented, handed over. No lock-in, no unnecessary dependencies.
Requirements
Map what needs connecting and why.
Architecture
Design the connector.
Build
Write and test the integration.
AI layer
Add intelligence where volume justifies it.
Deploy and monitor
Go live with error reporting.
Document and handover
No lock-in.
What is included
Custom connectors
API work between CRM, website, telephony, WhatsApp, ERP and accounting systems, built for your actual data rather than a generic mapping.
Data sync
Two-way where needed, with deduplication and conflict rules agreed up front rather than discovered in production.
AI agents in production
Qualification on WhatsApp and web forms, reply classification on outbound, call scoring, and extraction from documents and threads. Built where the volume justifies it and where the accuracy can actually be checked, which rules out more use cases than it permits.
Cost discipline
Results cached and looked up locally before a model is called. A lookup resolved once is never paid for again, which is why our AI builds do not get more expensive as you use them more.
Where we say no
We will not put an agent in front of something a buyer would notice going wrong. Technical content, outbound copy and live deal judgement stay with people. The test is whether an error would be embarrassing or merely inefficient.
Internal tooling
Small tools that remove recurring manual work, where buying software would be disproportionate.
Documentation and handover
Everything documented so your team or another vendor can maintain it. No lock-in.
Want to know if this is the right starting point? Tell us what is not working and we will say whether this is where we would begin, or somewhere else.
Ask usProblems we have solved
Described by the problem rather than by the client.
A calling operation with no product behind it
What we found
The client wanted cold outreach run by callers rather than by email. The work needed a dialling priority list, call tracking, call analysis, quality reporting, meeting booking and prospect reminders. No single product covered it, and four stitched-together tools would have leaked data at every join.
What we built
One application. Priority lists generated daily, calls tracked and analysed, quality reports per caller, a team leaderboard, meetings booked from inside the app during the call, and automatic reminders to the prospect on WhatsApp and email.
What changed
The callers work in one screen instead of four. The manager coaches on what was said rather than on call duration. Reminders go where prospects actually read them, and the reports reconcile because everything writes to the same place.
An AI tool whose running cost was growing with use
What we found
A lookup process called a model on every single record, including for values it had already resolved many times before.
What we built
A local store checked first, with the model called only for genuinely new values. Everything resolved once is never paid for again.
What changed
Running cost dropped sharply and stopped scaling with volume.
Two systems kept in sync by hand
What we found
A person was re-entering records between two systems daily, with the usual consequences for accuracy.
What we built
A connector with agreed conflict rules and error reporting, so failures surface instead of silently diverging.
What changed
The manual step disappeared and the two systems stopped disagreeing.
Often runs with
Talk to us about integrations and AI builds
Thirty minutes, no deck. If this is not what you need we will say so.