AI Engineering
Turn ideas and problems into working solutions.
Off-the-shelf tools don’t always fit what your business needs. We build custom applications, intelligent systems and AI-powered software that simplify complex tasks, support decisions and help your business grow on its own terms.
Ask about AI Engineering Book a free consultation
Prefer to write? Send us an email at [email protected]
Who it’s for
Businesses and teams that need a focused tool or a complete application designed and built, or an existing product made clearer and easier to use.
It may be for you if
- Part of your business runs on a spreadsheet that has outgrown it.
- Off-the-shelf software makes your team work around it.
- You have an idea for a tool or product and need it designed and built, not only drawn.
- An existing product works, but people find it confusing.
01What you get
What you get
- A clear definition of the problem, the people involved and what the product must do
- User flows, interface design and a design system you can keep using
- Working software, tested against real use rather than only reviewed as screens
- A deployed product, with its decisions and known limits written down
02In detail
What it involves
AI Engineering covers the whole path from an idea or a problem to software people use every day. Design and development happen together, so what is decided about the experience is what gets built.
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Discovery
We define the problem, the people who will use the software, what they need to do and what gets in their way today. The result is a short, agreed description of what the product must do.
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Design
User flows, interface design and a design system, checked with the people who will actually use the product.
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Development, with AI where it helps
We build the application and add AI features only where they make a task faster or better, such as handling free text, sorting or drafting. Everything else stays simple and predictable.
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Prototype, test, refine
A working version early, put in front of real use, then refined according to what people actually do with it.
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Launch and documentation
A deployed product, with its decisions and known limits written down, so it can be run, changed and grown.
03Why it pays off
Software that fits how your business works.
Off-the-shelf tools are built for the average customer. A focused tool built around your process removes the workarounds, and AI-assisted development has made such tools quicker to build than they used to be.
Many companies adapt their work to their software: data copied between systems, steps done outside the tool, and a spreadsheet that holds it all together. Each workaround costs a little time every day and adds risk, because it lives in someone’s head rather than in the system.
A tool built for the job reverses that. It does what your process needs and nothing it doesn’t, so it is simpler for the people who use it. It can bring AI into the places where it helps, such as drafting, sorting or searching, while leaving decisions with your team.
Building such tools is faster than it was. In a controlled experiment, developers with an AI pair programmer completed a programming task 55.8% faster than those without one. We use AI the same way: to speed up the routine parts of development, while design decisions, testing and review stay with experienced people.
Because strategy, design and code are handled by one team, decisions about the experience aren’t lost on the way to engineering. You receive a working product, tested in real use and documented, that you can run, change and grow.
Fewer workarounds
The tool follows your process, so steps no longer happen outside it.
Real software early
Working prototypes come early, so you judge something that runs, not only screens.
Simpler for the people who use it
Design and usability are part of the build, not an afterthought.
Built to be maintained
Decisions and known limits are written down, so the product can be changed later.
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Fig. 1
55.8% faster: developers with an AI pair programmer completed a programming task in a controlled experiment.
The task was to implement an HTTP server in JavaScript as quickly as possible.
About this figure: 55.8%
A controlled experiment with recruited software developers and GitHub Copilot, by researchers including GitHub staff (arXiv, February 2023). It measured one small, well-defined task; the speed of a whole product depends on much more than writing code.
These figures come from studies and rules in other settings. They show why the work matters, not what will happen in your business.
04How we work
How we work
Start from the work
How the task is done today, by whom, and where it breaks.
Prototype in code
A working version early, so questions are settled by use, not by opinion.
Ship and refine
Release, watch how it is used, and improve what matters.
We take a product from the first question to working software: what it should do, how it should feel, and how it is built. Strategy, interface and code are designed together, so a decision about the experience isn’t lost in translation to engineering.
We prototype in working code early, put it in front of real use, and refine. The result is a product you can run, change and grow, not a set of screens waiting for a developer.
Questions?
Have questions? Let’s talk.
Not sure whether this fits your situation? Tell us briefly what you’re working on. We’ll read it, ask a few questions and suggest a sensible next step, even if that step isn’t working with us.
- A short description of the problem is enough to start.
- No sales script and no obligation.
- You talk to one of the founders, not an account manager.
Ask about AI Engineering Book a free consultation
Prefer to write? Send us an email at [email protected]
05FAQ
Frequently asked questions
What kinds of software do you build?
Focused internal tools that replace a spreadsheet or a manual routine, complete applications from concept to deployment, redesigns of an existing product’s experience and front end, and installable applications that work offline.
Do we need a finished specification?
No. Discovery comes first: together we define the problem, the people who will use the software and what it must do. The result is a short, agreed description before design and development start.
Will the product use AI?
Only where it makes a task faster or better, such as handling free text, sorting or drafting. Everything else stays simple and predictable.
When do we see something working?
Early. We prototype in working code and put it in front of real use, then refine it according to what people actually do with it.
Can you improve a product we already have?
Yes. A redesign of an existing product’s experience and front end is one of the kinds of work we do.
Who designs and who builds?
One team. Strategy, interface and code are designed together, so a decision about the experience isn’t lost in translation to engineering.
Do you use AI to write code?
Where it speeds up the routine parts of development. Design decisions, testing and review stay with experienced people.
Can the application work offline?
It can. An installable application that works offline is one of the kinds of software we build, when the work calls for it.
What do we receive at launch?
A deployed product, with its decisions and known limits written down, so it can be run, changed and grown.
How much does it cost?
It depends on the scope. After a first conversation we describe what the work would include and what it would cost, in writing, before anything starts.