Technology
AI Integration
AI added where it removes real work, wired into the systems you already run — not a chatbot bolted onto a homepage.
The useful question is which task currently costs a person hours and tolerates a machine getting it mostly right with a human check. Support triage, document extraction, search that understands a question instead of matching keywords, drafting that a person edits rather than writes. Those pay for themselves. A general-purpose assistant on a marketing page rarely does.
We build with evaluation from the start: a set of real examples with known-good answers, scored on every change, so a prompt or model swap is a measurement rather than a vibe. Cost is a design constraint too — caching, routing cheap requests to smaller models, and a hard ceiling so a runaway loop cannot produce a surprise invoice.
Anything that touches your data gets the boring safeguards: what leaves your infrastructure is decided explicitly, prompts are versioned, outputs are logged, and a person stays in the loop wherever a wrong answer would be expensive.
FAQ
AI Integration — questions we get asked
Where does AI actually pay off?
Repetitive reading and writing. Classifying and routing inbound messages, pulling structured fields out of invoices or forms, answering questions from a document set, and drafting text a person then edits. Anything requiring a guaranteed-correct answer with no human check is a poor fit.
Does our data get used for training?
Not on the business API tiers we build against, and we confirm the terms of whichever provider a project uses in writing before any data moves. Where the data cannot leave your infrastructure at all, that constraint shapes the architecture from day one.
How do you keep costs predictable?
Cache what repeats, send the cheap requests to a smaller model, cap tokens per request, and set a hard monthly ceiling with alerting well before it. You get a projected cost per thousand requests before we build, not after.
Ready when you are.
Tell us what you are trying to build. We will come back with scope, timeline and a number — not a discovery-call funnel.