AI agents and automation, engineered for production.

Most production AI agents run $35,000–$120,000 depending on integration count and compliance scope.

Usually yes. We audit what you have, keep the parts that hold up, and rebuild the parts that will not survive real traffic — auth, data model, error handling, deploys. You get the audit document either way, whether or not you continue with us.

A consultancy delivers a recommendation. An engineering company delivers a running system and then operates it. We write the code, own the deployment pipeline, and stay on call after launch. The deliverable is software in production, not a slide deck.

First production release typically ships in four to six weeks. Discovery call within 48 hours, scope back within a week, first sprint inside two weeks. Complex integrations or regulated environments extend that to eight to twelve weeks.

A two-week diagnostic producing four deliverables: a system map of your current stack, a risk register, a shortlist of automation candidates ranked by payback, and a costed roadmap. The documents are yours to keep and to take elsewhere.

If you place software on the EU market, yes. Cyber Resilience Act vulnerability reporting obligations begin 11 September 2026: an early warning to ENISA within 24 hours of an actively exploited vulnerability, full notification within 72 hours, final report within 14 days. It covers products already on the market.

Every line an agent writes gets human review before merge, tests cover the paths that carry money or personal data, and dependency and secrets scanning run in CI on every push. Speed comes from removing waiting, not from skipping review.

You meet the engineers who will do the work before you sign, and one accountable lead stays on the engagement from start to finish. Juniors pair with seniors rather than learning on your budget.

Yes. Code, models, prompts, training data and documentation are yours from the first commit, held in your repositories and your cloud accounts. There is no licence-back clause and no vendor lock to us.

Claude, GPT, Gemini, Llama and Mistral for models; LangChain, the Model Context Protocol and n8n for orchestration; PyTorch and TensorFlow for custom models. We pick per workload rather than standardising on one vendor.

Yes, and it is usually the point. Most engagements are integration work: Salesforce, HubSpot, Zendesk, WordPress, Shopify, internal REST and GraphQL APIs, and databases you already run. We build against what you have rather than asking you to replace it.

We sign your NDA before the discovery call. Client data stays in your cloud accounts and your region. We do not train models on your data, and we do not send it to third-party providers without a signed data processing agreement naming them.

Thirty days notice, no exit fee, and a documented handover of everything running, including infrastructure access and runbooks. We would rather tell you early that we are the wrong firm for the work than bill through a bad engagement.