Hands-on AI and machine-learning training built around your domain, your tools, and your real production constraints, not generic curricula and quiz-shaped certificates.
Most AI training is a stack of generic videos and a multiple-choice exam at the end. Our learners come back to work and discover that their codebase, their data, and their constraints don't look anything like the ones they trained on. We do the opposite: we build the curriculum around your codebase, your data, and your constraints, and the capstone project is something your business actually needs.
From executive briefings for leaders who need AI-literacy without writing code, to engineering bootcamps for ML practitioners who need to ship models that survive production, we tailor the depth, the language, and the hands-on work to the audience in front of us. The output is a team that's measurably more capable on Monday than they were before they started.
Every program is designed and delivered by senior engineers and researchers with real production scars, the same people who would lead a project in your organisation. There are no junior trainers reading a script. There is no AI 101 deck recycled from a conference talk. Just working software, working models, and the people on your team who can now build them.
We tune the depth, the tooling, and the language to the people in the room. These are the most-requested formats, though every engagement gets shaped to fit.
A focused half-day or two-day session for executives, board members, and senior decision-makers. We cover what AI can and can't do, where the regulatory and reputational risks live, how to read a model evaluation, and how to ask the right questions of your technical team. No code, plenty of judgment.
A 12-week intensive for software engineers and data scientists moving into production ML. Curriculum covers the full stack: data pipelines, modeling, deployment, monitoring, and on-call ownership. Capstone projects are graded on real data, not toy datasets, by senior engineers.
Healthcare AI, Defense ML, Finance modeling, Manufacturing predictive maintenance, Public Sector LLMs. Curriculum, datasets, and case studies tailored to your sector, including the regulatory and ethical considerations that come with the territory.
Bring an entire team or department through the same curriculum at the same time, with content adapted to your codebase. Everyone learns the same language, the same patterns, and the same conventions, so the team that finishes the program looks like a team, not a collection of individuals.
Ongoing 1-on-1 and small-group coaching for engineers and leaders past the formal training. Bring real problems, real code, real production incidents, and get help from senior practitioners who have shipped through them before.
Before-and-after assessments that measure actual skill, not seat-time. We design role-specific evaluations, design review, code review, model review, on-call drill, and produce a defensible signal of who's ready for what kind of work.
Three representative engagements, the audience, the problem, and the capability that team walked away with.
A clinical AI team needed to use large language models on patient data without breaking HIPAA, leaking PHI, or hallucinating diagnoses. We delivered a four-week curriculum covering RAG patterns, evaluation harnesses for medical accuracy, prompt-injection defences, and an audit-trail design that satisfied legal review.
A manufacturing operations team had a vendor-supplied predictive-maintenance model and zero idea how it worked. We ran a six-week program that covered the underlying ML, how to read its outputs, when to override it, and how to detect when the model itself was drifting away from reality.
A bank's risk and compliance team was asked to sign off on ML models without the technical vocabulary to do so. We built a custom curriculum covering model documentation, fairness testing, monitoring, and the questions a compliance reviewer should ask before a model goes live.
Bad corporate training is everywhere, and most of it fails for the same reasons. These five rules are how we stay on the right side of that line, in every program we deliver.
Tell us the audience, the gap, and the outcome you need by when. We'll come back with a one-page program proposal: agenda, instructor, capstone project, and the measurable capability the team will walk away with.