Are they competent? Are they priced right? Most hiring teams can't tell. We train developers on proven AI development workflows and put them inside your business, or take the team you already have and train them the same way.
Founder-led from the UK, delivered by our team in the Philippines.
Hiring AI capability is guesswork on three fronts at once. Talent: anyone can put AI on a CV, and you're as new to judging it as they are. Technique: even a capable developer may use AI in an ad-hoc, inconsistent way. Price: demand outstrips supply, so there's no benchmark for what any of it should cost. You end up committing budget without ever being sure what you've bought.
Same workflows, same training and assessment programme, same standard. The difference is who ends up running it.
We recruit, train and deliver developers who have come through the same programme our own team runs on, then embed them in your business as a working unit with every discipline the work needs.
Best if you need AI delivery capability now and hiring it yourself has stalled.
Your team, our workflows. We baseline how they build today, put them through the same training and assessment programme, and leave them working to a consistent standard you can hold them to.
Best if you have a good team whose AI use is inconsistent and unmeasured.
Tested workflows we call playbooks, refined on our own products before they reach yours. One standard the whole team builds to, rather than every developer improvising their own.
We know the skills a competent AI developer needs, teach them, and measure who actually has them. We built the learning platform ourselves in a month, and every graduate comes through it.
The playbooks live in GitHub. Your team pulls them down and builds to the same standard from day one, with nothing held back to keep you dependent on us.
We baseline your team before we change anything, then measure against it. 60%+ is what we saw in our own team; we won't quote a figure for yours until we've measured it.
A dedicated R&D team runs constant experimentation on models, tooling and delivery patterns. Everything on this page came out of that, and it reached our own team before it reached anyone else's.
We measure how your team builds today, so the uplift is a number rather than a claim either of us can argue about later.
We set one standard for AI use across the team: which models handle which work, the delivery patterns, and the quality gates that catch what AI gets wrong.
The whole team goes through the programme, not the keen few, and we assess where each person lands rather than assuming. Engineers, designers and QA on the same path.
We stay close while it beds in, measure against the baseline, and feed each R&D improvement back in. The gap widens rather than plateaus.
A US residential mortgage lender with over 80 underwriters and more than 1,000 appraisals a month brought in a trained team built and embedded by us. It started with one appraisal-review tool; live automations now reach across due diligence and document work, and each one funds the next.
Four people running constant experimentation on models, tooling and delivery patterns. Every improvement they find reaches the whole team, and yours.
Agents do the volume, a named developer owns the result. That's the rule the workflows are built around, and it's why speed hasn't cost us quality.
We build and embed AI teams, train graduates in AI through our own learning platform, and ship AI products for clients. It's what we do daily, not a capability we picked up for the pitch, and 4.9 on Clutch across 21 verified reviews is the record behind it.
Need AI built into a product rather than into a team? Our AI product development page is the better place to start. If you're not sure which applies, book the call and we'll point you the right way, even if that's not us.
No, and if that's all you need, don't pay us for it. Tool training is the easy part and your team can do it themselves. What's hard is the layer above: deciding which model handles which kind of work and at what cost, structuring work so agents can pick it up, and putting quality gates in place so speed doesn't cost you correctness. That's what our workflows cover, and it's what makes the difference between developers who use AI and a team that builds differently.
Nothing stops it entirely, and anyone telling you otherwise is selling. What changes is the cost when it happens. Today, losing your one AI-capable developer sets you back months. With the workflows written down and the training and assessment programme in place, the next person reaches the same standard in weeks. There's also a retention argument in the other direction: developers tend to stay where they're getting better, and this makes them measurably better.
Our own development team, measured against how they worked before these workflows. It's a real internal number, not a market statistic. We're not going to promise you the same figure before we've seen how your team builds today, which is why the first thing we do is baseline. If the uplift for your team turns out to be smaller, you'll hear that from us rather than find it out yourself.
Either. Some clients want a trained team delivered to them because their own hiring has stalled. Others have a good team and just need it working to a consistent standard. Plenty do both: train the existing team, and add trained developers alongside them where there's a capacity gap. The workflows and the programme are the same in every case.
The call takes 20 minutes and is free. From there, a baseline assessment can usually begin within a couple of weeks, and it's the shortest piece of work here. Book a call, tell us how your team builds today and where it's stretched, and we'll tell you which of the two routes fits and what the first step costs.
Book a free 20-minute call. Tell us how your team builds today and where the AI capability sits. We'll tell you which route fits, what it would take, and if we're not the right answer we'll say so.
Book a Free AI Capability Call