AI that does the work
and shows its sources.

Less than most agencies imply, because we don't start with a platform build. Every engagement opens with a scoped pilot (one workflow, your data, a working deliverable in 14 days), so you're pricing a small, defined piece of work rather than a vague transformation programme. The proposal you receive within 48 hours itemises exactly what ships, including the workflow covered, the integrations wired, the guardrails and evaluation included, and what handover looks like. Scaling beyond the pilot is priced only after the pilot has earned it.

The ones that fit your data, your budget and your residency requirements: decided in discovery, not before it. We're deliberately model-agnostic. Builds are structured so the underlying model can be swapped without rework as better or cheaper options ship, which happens every few months. That protects you from betting the project on whichever provider is fashionable this quarter. More important than the model name is everything around it: how answers are grounded in your documentation, how failures are caught, and how the system plugs into the tools your team already uses. And we build on your existing cloud and stack, not a platform you'd have to migrate to.

It stays yours. Work runs under NDA as standard; your documents and customer data are used to ground your system and for nothing else. Where you need it, we deploy inside your own cloud account or private environment so nothing leaves your infrastructure, and we use enterprise API terms under which providers don't train on your data. Retention, residency and access rules are agreed in the scope document, not discovered after launch. Access is logged. At handover you own the code, the prompts and every pipeline we built, so there's no dependency on us to keep it running.

Any language model can. Anyone who tells you otherwise is selling something. Our job is to make errors rare, visible and safe. Every assistant we ship answers from your own documentation and shows its sources; when confidence is low it says so and hands over to a human rather than guessing. Before launch it runs against an evaluation suite built from your real cases, and after launch the logs let you audit exactly what was said and why. The honest answer: not zero errors, but engineered, measured and contained ones.

Sometimes buy, and we'll tell you so in discovery, because a pilot that shouldn't exist wastes your money and our reputation. Off-the-shelf makes sense when the workflow is generic and the tool can already reach your data. Custom earns its keep when the workflow is core to how you make money, when answers must be grounded in your own documentation, or when the off-the-shelf option can't integrate with the systems your team actually uses. Discovery ends with a written recommendation either way. If the recommendation is a tool you subscribe to for a fraction of a build, that's what the document will say.

Whoever you choose: you're not locked to us. Every build hands over with documentation, admin training and a runbook your own team can operate; you own the code and the prompts outright. A light retainer is the usual shape after launch, for monitoring, evaluation re-runs as your documentation changes, and the changes the first month teaches. Or take the handover and run it in-house. Either way the retainer is scoped like everything else: itemised, in writing, cancellable.

A working pilot, not a slide deck. With us that means one workflow, your own data and a working deliverable in 14 days, built on the stack you already run. Guardrails, an evaluation suite from your real cases and a runbook for your team are included. You own the code, the prompts and the pipelines at handover.