Four ways teams end up working with us.
Most engineering problems do not arrive neatly labelled. Start with the symptom closest to yours; we will identify the underlying problem and the right way forward.
Build it
A product, platform or internal system that has to go from nothing to running, with a date attached and no team standing by to do it.
- You have a signed customer, a board commitment or a market window, and nothing is running yet.
- Hiring the team you need takes longer than the deadline you have.
- A previous attempt produced a prototype nobody can operate or extend.
- You know roughly what it must do, and not at all how it should be built.
- Cut the idea down to the smallest thing that can be real, then argue with you about what got cut.
- Architecture decided against your actual constraints — data residency, budget, team size after we leave.
- Build the product: web, mobile, services, data model, integrations, admin tooling.
- Ship it into an environment your team can run, with the deployment path and observability already in place.
- Hand it over properly, or keep running it — both are fine, but we decide which at the start, not the end.
A small senior team, a fixed first milestone measured in weeks, and a working deployment before anyone writes a status report.
We will tell you in the first conversation if what you are describing cannot be built for what you want to spend. That answer is free and it is usually the useful one.
Scale it
Something real is already in production and the way it was built is now the constraint on the business rather than the support for it.
- Releases that used to take days take weeks, and nobody can say precisely why.
- The same class of incident keeps coming back with a different name.
- There is a service everyone routes around because the person who wrote it left.
- Onboarding a new customer requires an engineer, and it should not.
- You are being asked for enterprise things — SSO, audit trails, tenant isolation — the system was never shaped for.
- Read the system as it actually is, including the parts the documentation is wrong about.
- Separate what is genuinely load-bearing from what is simply old, so you do not pay to rewrite working code.
- Re-architect the parts that need it: tenancy and identity, transaction boundaries, background work, data access.
- Put delivery back in order — environment parity, artifact promotion, tests that actually gate a release.
- Make the operational picture legible: what is slow, what is failing, what it costs to serve a customer.
A short assessment first — usually two to three weeks — that ends in a written, prioritised plan you own whether or not you continue with us.
We would rather fix four things that matter than propose a rewrite. Rewrites are occasionally correct and almost always oversold.
Run it for less
The infrastructure bill has stopped tracking the value the system produces, and the estate has grown into something nobody has a full picture of.
- Cloud spend is growing faster than usage and the line item breakdown explains nothing.
- Steady, predictable workloads — CI, dev environments, batch, inference — are being billed by the hour.
- Data residency or sovereignty rules are pushing you towards infrastructure you control, and nobody wants to run it.
- You have hardware already, and it sits underused because using it means a different developer workflow.
- Systems that should talk to each other are joined by scripts one person understands.
- Map every workload to what it actually needs: latency, data gravity, burst profile, compliance boundary.
- Place each one deliberately across owned hardware, AWS, Azure or GCP — and write down why.
- Keep one developer experience across all of it, so placement is an operations decision and not a rewrite.
- Unify identity and access — OIDC and RBAC that stay coherent as the estate grows rather than fragmenting.
- Build the integration layer properly: contracts, retries, idempotency, and visibility when it fails at 3am.
A placement review that produces a workload-by-workload recommendation with the cost and risk of each move stated plainly, then the migration itself.
Sometimes the honest recommendation is that your current setup is right and the money is going somewhere else. We will say so.
Make it intelligent
There is data, and there is an AI mandate, and between them a gap made of latency, governance, cost and the difference between a demo and a system.
- A prototype works on someone's laptop and has been stuck there for months.
- The data your model needs cannot leave your network, which rules out the easy path.
- Per-token cost is fine in a demo and indefensible at your real volume.
- Your data is spread across systems that disagree with each other, and no model will fix that.
- You need to be able to explain to a regulator or a customer what the system did and why.
- Start with whether the problem needs a model at all — a surprising number do not, and we would rather tell you.
- Get the data in order first: pipelines, lineage, quality, and a retrieval layer that returns the right thing.
- Serve models on infrastructure you control, with bounded context and concurrency scheduled against real memory.
- Put it in the product path with the latency and failure behaviour a user-facing system requires.
- Add the parts that make it operable: evaluation, monitoring, audit trail, and a way to roll back a bad model.
One narrow use case taken all the way to production, instrumented, before anyone commits to a programme.
We are not interested in shipping you a demo. A demo is the easy 20% and it is where most of this work quietly stops.
Then describe it in your own words and we will tell you honestly.
These four cover most of what comes to us, but they are our categories, not your problem. If yours sits across two of them, or outside all of them, that is worth a conversation either way — including the conversation where we say it is not for us and point you somewhere better.
We work on engagements measured in months rather than weeks, with a small senior team rather than a large one. If your problem is smaller than that, say so anyway — we will point you at someone who is a better fit rather than take the work.
Describe your problem ↓Start with the symptom, not the solution.
Send the bill, the incident report, or the roadmap that keeps slipping. We will tell you which of these four it actually is — or that it is none of them.
- Within two working daysA reply from an engineer who would be on the work, not an account manager and not an automated acknowledgement.
- Then a callForty-five minutes about your problem rather than our capabilities. Bring the architecture diagram, the bill, or the incident report.
- Then something in writingA short written view of what we think is actually going on. Yours to keep and act on, with or without us.