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built right.made smarter.

We build AI systems for slow, manual, knowledge-heavy work — then hand your team the code, the tests, and the runbook.

what we build

01

one workflow, not an AI strategy

We take on a specific job your team does today. Not a platform, not a transformation programme.

02

built into the systems you already use

Your permissions, your data, your handoffs. The AI goes where the work already happens.

03

interface, model, and plumbing in one build

One team does the product design, the AI engineering, the integrations, and the cloud setup.

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most AI projects
die as demos.

We design the operating system around the model.

capabilities

discovery & AI audit

Work out which AI project is worth doing first, and why.

LLM applications

Products built on language models, tested against your real cases.

RAG & semantic search

Answers drawn from your own documents, with the source attached.

workflow automation

Multi-step work that runs without somebody remembering to start it.

platform & APIs

The web application and interfaces the whole thing runs on.

cloud & infrastructure

Hosting, deployment, and monitoring your own team can operate.

work we take on

ticket triage

Read what came in, gather the context around it, and draft the reply for a person to send.

document extraction

Pull the fields you need out of invoices, forms, contracts, and scanned files.

drafting and reporting

First drafts of proposals, summaries, and recurring reports, ready for someone to edit.

policy and precedent lookup

Answers from your own policies and past cases, with the source and its review date shown.

case and application review

Assemble the evidence, check it against the rule, and flag what a human must decide.

research and monitoring

Watch a source, notice what actually changed, and open the exceptions as work.

production-ready means

evaluated

Quality is tested against a task-specific benchmark before release.

observable

Teams can see cost, latency, failures, drift, and user outcomes.

controlled

Permissions, escalation, and human review live inside the workflow.

owned

Your team gets the code, infrastructure, documentation, and runbook.

A prototype only has to work once; production has to keep working after we leave.

is this you?

01

your first AI project, with real stakes

You need a clear opportunity, a justified architecture, and an honest path to production.

02

a pilot that stalled at the demo

You have evidence of value but not the controls, integrations, or operating model to release it.

03

a good team already at capacity

You need a senior product-engineering unit that can own a hard stream and leave the system stronger.

what we build with

language modelsretrievalagentsevaluationNext.jsAPIscloudobservability

Provider-flexible by design. The stack follows the operating constraint, not a preferred logo.

common questions

What does it cost?

Every engagement is scoped and priced after the free thirty-minute call. You see a written price for a defined stage before any work starts.

What do we get at the end?

The code, the infrastructure definitions, the tests, the documentation, and a runbook. Your team can deploy a change without asking us how.

Can we start before our data is perfect?

Usually. We define the minimum trustworthy data path, test it, and make the gaps explicit in the roadmap.

Will you use our current systems?

Where they are sound, yes. Replacing familiar tools without a clear operating reason creates risk instead of value.

How quickly do we see working software?

A useful vertical slice should appear in weeks. The exact sequence depends on access, risk, and the workflow being changed.

What happens after launch?

We can operate alongside your team, transition ownership, or continue into the next proven scope. The handover is designed from the start.

how we work

01

scope the real problem

Map the work, evidence, constraints, and the decision AI is meant to improve.

02

ship something usable

Put one end-to-end slice in front of real users and measure the hard assumption.

03

harden and hand over

Add tests, observability, governance, documentation, and a clear operating owner.

see the delivery model

Thirty minutes, no charge. Bring the workflow that is stuck.

book a free 30-minute call

Bring the workflow that is slow, fragile, or too dependent on a few people.

start withthe problem.