AI integration for operating companies
We integrate AI into the workflows, data and tools your company already depends on. No rebuild, no rip-and-replace, no science project. Production systems with measured results.
Scroll the diagram sideways
4-8 weeks
to first system in production
Your cloud
or ours, your data never trains a model
Model-agnostic
swap providers without a rewrite
What we build
Most AI projects stall between the demo and production. These are the four we take all the way there.
Document processing, intake, triage, reconciliation, reporting. The repetitive back-office work that consumes hours and rewards nobody. We automate the judgement-light parts and route the rest to a human with the context already assembled.
Internal assistants that answer from your documentation, contracts, tickets and databases, with citations back to the source. Staff stop asking the one person who knows, and the answer is checkable.
Connecting models to the systems that hold your reality: your ERP, CRM, data warehouse, internal APIs. This is where most projects fail, and it is mostly engineering rather than prompting.
Evaluation harnesses, cost ceilings, latency budgets, audit logs, fallback chains and dashboards. The difference between a demo that impressed a room and a system your team can rely on at 3am.
How we work
A first engagement targets one workflow with a number attached to it. If that number does not move, nothing else was going to.
Week 1
We sit with the people doing the work, map one workflow end to end, and find where the time actually goes. You get a written plan with a fixed price and an honest estimate of the return, including the case where the answer is that AI is the wrong tool here.
Weeks 2-6
Two-week increments, something usable at the end of each. You see working software throughout rather than a status report. We build the evaluation harness before the feature, so improvement is measured rather than asserted.
Weeks 6-8
Deployment into your environment with monitoring, cost controls and runbooks. Your team is trained on it. The system is documented well enough that we are not a dependency.
Ongoing
You own the code and the infrastructure. Some clients take it from there; others move on to the next workflow. Both are fine, and we say so before you sign anything.
What we believe
We do not train on client data. Where the requirement calls for it, we deploy inside your own cloud account or on-premise so records never leave your perimeter.
Every system ships with an evaluation suite. If we cannot measure whether a change made it better, we do not claim that it did.
You own the code. Models are swappable by design. We would rather be re-hired than depended on.
Plenty of problems are better solved with a database query, a form or a fixed process. We say so early, when it is still cheap.
Tell us what is consuming your team's hours. We will tell you whether it is worth automating, and roughly what it would take.
Book a call