Diverse team in a bright boardroom reviewing work together

How we work

Diagnose honestly, build the foundation,
hand it over

Fixed scope, fixed price, and a system your team owns on the day we leave.

The method

Three stages, six steps, and the order matters

Most of the AI programmes we are called into have already been attempted once. This order exists because of what we found when we looked into why those attempts stalled — almost never the model.

Diagnose & specify

Nothing is proposed before the estate has been read.

Diagnose before proposing
Every engagement opens with an honest read on what you have already tried and why it did not scale. The AI-Ready Blueprint scores your data estate, technology, team capability and governance maturity against sector benchmarks.
Design the specification before any code
Task boundaries, tool permissions, escalation logic, output schema and failure modes are written down and signed off before a line is written. This is the step most agent projects skip.

Build & prove

Foundation first, then intelligence, then a measured result.

Build the foundation, then the intelligence
The governed data layer comes first, the agents second. Medallion architecture, automated quality tests and a semantic layer with agreed definitions — then retrieval, extraction and decision support on top of it.
Prove accuracy against a real benchmark
Accuracy thresholds, confidence scoring and a hold-out set of your real documents are defined at design time. Nothing goes live on a demo; it goes live on a measured result against a human benchmark.

Review & hand over

A person on every regulated decision, and no standing dependency on us.

Put a human on every regulated decision
Human review is designed to accelerate the decision, not gate it. Only outputs that genuinely require judgement route to a person, and every override is captured and fed back.
Hand over completely
Documentation, runbooks and hands-on training are part of the engagement. Your team owns and operates every system we build. We would rather be re-hired than depended upon.

Stage by stage

What each stage does, produces and costs you in time

	01Diagnose & specify	02Build & prove	03Review & hand over
What happens	Your data estate, technology, capability and governance maturity scored against regulated-sector benchmarks, then the specification written and signed off.	The governed data layer built first, the agents second, and accuracy measured against a hold-out set of your own documents.	Reviewer roles, escalation paths and override capture in the workflow, then documentation, runbooks and training.
What you get	A prioritised, costed initiative list with a named owner on each line — yours to execute with us, your own team, or another firm.	A running system inside your own cloud tenancy, with every output explained and traceable to its source.	Full in-house ownership at handover: the code, the architecture and the ability to extend it without us.
How long	Three weeks, fixed scope and fixed price.	Under six weeks from kick-off to running, on fixed commercial terms.	Inside the engagement — handover is not a later phase you pay for twice.

What makes us different

Four claims you can hold us to

Fixed scope, fixed price, time-boxed
Diagnostic engagements are three weeks. Product deployments are under six weeks. Both are priced up front, and the boundary is contractual rather than aspirational.
Platform choice follows the estate
We build daily on Databricks, Microsoft, Snowflake, Anthropic and OpenAI, and the recommendation follows what your estate can actually support.
Your tenancy, your data
Products deploy inside your own cloud tenancy. In NHS engagements, patient data never leaves the approved boundary. Documents are not sent anywhere to be processed.
You own what we build
Blueprints, architectures and code are yours to take anywhere, including to another firm. No lock-in is designed into the deliverable.

What it produces

Delivered results from the method

Point figures are attributable to a specific engagement. Nothing here is a projection.

3 wksto a board-ready roadmapFixed-scope diagnostic, prioritised actions

6 wkskick-off to runningOn fixed commercial terms, in your own tenancy

100%XAI trace coverageOn every automated output in production

100%in-house ownership at handoverNo standing dependency on us

Our work

The method, applied

All success stories

AI agents · Specialty insurance

Submission triage from 4.2 days to 18 minutes with twelve AI agents

A specialist MGA’s underwriting team was drowning in inbound submissions. Twelve co-operating agents rebuilt the intake workflow — without replacing a single underwriter.

Read the case study

Clinical AI · NHS