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How we work

Most AI projects fail before anyone writes model code.

They fail because the wrong decision was targeted, or because the data never supported the claim. Both are discoverable in the first fortnight if you look, and expensive to discover in month five. So we look first, every time, and we tell you what we find even when it shrinks the project.

live
Six phases

What happens, when, and what you receive at the end of each.

Phases one to three are where a project should change shape. If they do not, we have probably not looked hard enough.

Frame

Week 1

Before a model, the decision. Who acts on the output, how often, on what information, and what a wrong call actually costs.

What you receive
  • Decision map and success measures
  • Stakeholder and approval chain
  • The explicit list of what we are not doing

Audit

Weeks 1–2

What data exists, what is missing, what is biased and what cannot lawfully be used. Most projects narrow here, and that is the point.

What you receive
  • Data inventory and quality report
  • Legal basis and retention assessment
  • Revised scope, usually smaller

Baseline

Weeks 2–3

A simple, cheap approach gets built and measured before anything sophisticated. If the baseline is good enough, we tell you and stop.

What you receive
  • Working baseline with measured performance
  • The number every later version must beat
  • Go or no-go recommendation

Build

Weeks 3+

Design and engineering in reviewable increments, with the explanation built alongside the model rather than bolted on at the end.

What you receive
  • Fortnightly demos of working software
  • Test suite and CI pipeline
  • Architecture and API documentation

Harden

Before launch

Access control, audit logging, monitoring, accessibility, security review of every endpoint, and a defined route for a person to challenge a decision.

What you receive
  • Security and penetration-style review
  • WCAG conformance pass
  • Runbook and incident procedure

Run

After launch

Into production with monitoring, drift checks and a support window. Handover means your team can operate it without calling us.

What you receive
  • Production deployment
  • Monitoring and alerting
  • Handover sessions and 30-day support
Engagement models

Three ways in, depending on how much certainty you already have.

If you are not sure which fits, describe the problem and we will propose one, including the smallest option.

Discovery sprint

Two to three weeks. We work through the data you hold, what a model could realistically add, and what it would cost to run. You end with a decision, an architecture and a cost model — including the option to stop.

2–3 weeksFixed feeWritten recommendation

Build partnership

We design and build the system, then hand it over with the documentation and tests to run it yourself. Delivered in reviewable increments, with production access and a support window at the end.

8+ weeksMilestone-basedHandover included

Embedded AI team

Our engineers work inside your team on your roadmap, for the period you need the capability rather than the headcount. Suited to organisations building a first AI function.

MonthlyNamed engineersYour tooling
What you can expect from us

Four commitments that hold on every project.

These are the things clients tell us made the difference, so we have written them down.

Fortnightly demos

Working software, not a status document. If there is nothing to show, we say why.

Direct access

You talk to the engineers. There is no account manager translating between you and the build.

Stoppable milestones

Every milestone is a point where a project can be paused or ended without losing what came before.

Real handover

Documentation, tests and sessions until your team can run it. Then a thirty-day support window.

Start with the frame, not the build.

A discovery sprint takes two to three weeks and ends with a written recommendation you can act on, whoever ends up building it.