AI tools are standard. Engineering judgement is not.
Every engineer has AI in their editor now. We screen for the part that actually matters: whether it changed how they work, and whether the output is still reviewable, secure and maintainable.
Applied AI, built into your product.
Beyond AI-assisted delivery, we help bring AI into what you ship — from LLM integrations and retrieval to agents, evaluation and the guardrails that keep it safe and governed.
LLM integrations
Bringing language models into your product safely and reliably, not as a demo.
Retrieval pipelines (RAG)
Grounding models in your data with retrieval that stays accurate and current.
Agents & workflows
Applied-AI workflows and agents wired into real product paths, not side projects.
Evaluation & guardrails
Evals, guardrails and monitoring, with documentation that supports EU AI Act readiness.
The judgement we screen for.
AI in the editor is table stakes. What separates a senior engineer is what they do with it: review, security and maintainability that hold up when the model is confidently wrong.
Reviews AI output as critically as their own.
Every engineer has AI in their editor now. The senior ones read the generated code, test the generated path, and keep the reasoning — not just the output.
Catches the risk a suggestion introduces.
A confident wrong answer is the real danger. We screen for engineers who catch the security and correctness risk a suggestion carries, rather than paste it through.
Ships what the team can live with.
Maintainability over velocity theatre. What they ship with AI is still something the team can understand, own and change six months from now.
Three ways to bring AI capability in.
This runs across every model, not as a separate service. What changes is how much you keep on your side, and how much we run.
Staff augmentation
Add AI-fluent senior engineers to your existing squad.
Dedicated team
A squad that builds and runs your applied-AI features.
End-to-end delivery
We own an AI workstream with governance.
Inside your process, under your policy.
Your repos, your security policy and your review standards. Engineers use AI within your rules from onboarding, with a named lead and the visibility set out in how we work.
Search → RAG pipeline
AI rarely ships alone.
Applied AI is only as good as what surrounds it — the data it's grounded in, the services it runs on, and the surfaces it reaches. Built to the same senior bar, by teams that already work together.
A good fit when you want AI used with judgement — in how engineers work, and in what you ship — without loosening your security or review bar.
Questions teams ask.
Do your engineers use tools like Copilot and Cursor?
Yes, daily. We care more about how an engineer uses them than which one they prefer.
Can you help us integrate an LLM into our product?
Yes, including retrieval pipelines, evaluation and guardrails, not just the first integration.
How do you handle AI and security?
We screen for it, and engineers work to your security policy within an EU and GDPR-aligned environment.
What about the EU AI Act?
We can support the technical documentation and governance practices it expects. We are not a legal advisor, so compliance determinations should sit with your own counsel.
Is this a separate service?
No. It runs across staff augmentation, dedicated teams and end-to-end delivery.
Put AI to work, with judgement.
Tell us where AI should help — in delivery, in the product, or both. We map the right model and the right engineers.