Corporate AI training for one team or the whole org chart: private cohorts on your own code, taught by people who have shipped agentic systems.
Agentic AI transformation through hands-on corporate AI training, not a syllabus. You are not buying a course. You are bringing in people who read where AI already sits in your organisation, build the program around that, and hand back what changed when it is over.
Before anything is taught, a read of where AI already sits across the organisation and what each function can realistically own in six months. Afterwards the same people are still reachable when the plan meets reality.
Roles, levels, tools and timeline decide what gets taught, per function and per business unit. Modules a group does not need are dropped, and every exercise runs on your own codebase, backlog or process.
What success means is agreed before day one, then reported back per cohort and rolled up across the company when more than one cohort runs: checkpoint scores, capstone results and a capability map, so the next decision is an argument rather than a guess.
Company size and how regulated you are decide how many cohorts run and in what order. The corporate AI training stays the same: practitioners in the room and your own systems on the screen.
One cohort, one track, the people already building. Sessions run part-time so the roadmap does not stop, and the capstone is something the team ships rather than an exercise.
Two or three cohorts, usually engineering first and product next. Tracks run in parallel or one after the other, and the capability report says which function is ready for more.
Parallel cohorts across business units on one calendar, one point of contact, on site or live online across countries, and every result rolled up for leadership.
Where the answer has to hold up to an auditor. Governance across the software development lifecycle, EU AI Act readiness, and cohorts that include the people who sign off, not only the ones who build.
Agentic AI does not land through one team. The engineers have to build it, the product side has to decide what is worth building, and leadership has to own what it does once it is running. Smaller companies start their AI upskilling with one track, larger ones run two or three in parallel.
From the first LLM call to multi-agent systems running in production, in the language the team already uses.
What agents make possible, what they cost, and how the week around them gets redesigned.
Strategy, governance and the questions a board asks before the first incident does.
Sessions spread across the calendar so nobody leaves delivery for days, or consecutive days when the capability is needed now — the same bootcamp format we run in public alongside our summits.
On site when the team sits together, live online when it does not. Same exercises and same assessment either way.
Every cohort is closed. Everyone in the session works on the same systems and the same constraints, so the examples are yours and nothing said in the room leaves it.
Your corporate AI training is built after the discovery call, not selected from a menu. Roles, levels, tools, units and timeline all change what gets delivered.
Delivered by people who have put these systems into production and hit the walls your team is about to hit.
After delivery you get module scores, capstone results and a readiness map per cohort, so the next budget line is an argument rather than a guess.
Participants earn the same verified certificate as any other route, which is what makes the AI upskilling worth their evenings as well as your budget.
Strategic advisory and fractional AI leadership for companies that want the expertise in the decision, not only in the training room.
Between the strategy and the rollout. If you already have an adoption plan, the discovery call maps the programs onto the milestones in it, cohorts are sequenced per function, and the capability report tells you which parts of the plan the organisation can actually carry.
AI upskilling built for one organisation rather than a public class. Cohorts are private to your people, built after a discovery call, taught live by practitioners, and worked on your own systems. A large organisation runs several cohorts in parallel, one per role or per business unit.
Yes. One cohort on one track is a full program, and it is how most smaller companies start. The discovery call sizes the group and picks the track. For one or two people, the open bootcamp days we run alongside our summits are the faster route.
Nine programs across three tracks: engineering, product and operations, and leadership. One group takes one program, or the organisation runs a sequence across roles and units.
Built and quoted per group after the discovery call, not per seat from a price list. What moves the number is how many cohorts run, the hours, the format, and whether delivery is on site or live online.
That is settled on the discovery call, not by a fixed number. Cohorts usually run part-time so teams stay on their roadmap, and an intensive is used when a group can be taken off it. Each program page carries its own length.
Yes. On-site delivery travels, and live online runs to the group's working hours.
Yes. Enterprise rollouts run in parallel cohorts, split by function or business unit, on one shared calendar with a single point of contact.
Every cohort is closed, the exercises run on your own systems, and nothing said in the room leaves it. We sign the agreements your company requires and work to your procurement timeline.
Yes. Governance across the software development lifecycle and EU AI Act readiness are a full program, cohorts can include the people who sign off and not only the ones who build, and the capability report per cohort is written to stand in front of an auditor.
Tell us which functions have to move first and what they have to be able to do. We come back with the sequence, the cohorts and the plan that gets you there.