AI AND GENAI TRAINING
Applied AI and generative AI training
We help business and operations teams apply generative AI to their own tasks, building on basic familiarity through practical workplace exercises.
- Role-based, so each team learns to apply GenAI to its own function
- Workshops, cohorts, and hands-on labs on your own tools and data
- Every module lands on scenarios from your business, used the next day
Modules we tailor to each team's role and your stack.
Every module lands on scenarios from your business, so people leave with prompts and workflows they use the next day. This program is one track in the full AI Upskilling and Training path. Beginners who need a gentler on-ramp start with AI for Beginners; engineers who need to build applications, not just use them, move to Building LLM Applications.
Skill sticks when people practice, not when they watch slides.
Active formats over lectures, mixed to fit each team.
We tier every format by ability, so newcomers and confident users progress at the right depth rather than one being bored while the other is lost.
Instructor-led workshops
Focused, interactive sessions where teams work through their own use cases live, not slideware.
Cohorts
A group learning together over several weeks, building shared practice and momentum across a function or business unit.
Hands-on labs
Guided, practical exercises on your tools and data, so skill is built by doing, then applied immediately.
Learn while building
Where it fits, training runs alongside a live delivery engagement, so teams learn by shipping real work they will own.
Four steps, from scope to skill that outlasts the sessions.
Scope
Map the roles, current skill levels, and the functions where GenAI will pay off first.
Design
Build a role-based curriculum around your stack, your policies, and real use cases from each team.
Deliver
Run the workshop, cohort, and lab mix that suits your teams and calendar.
Embed
Playbooks, reference prompts, and a support channel so skill outlasts the sessions.
Apply AI with a clear quality check.
- A useful workflow. Participants practise an approved task using examples relevant to their function.
- A checked output. Assess whether participants can spot unsupported claims, errors and sensitive information.
- Measured usefulness. Compare time and output quality on a suitable task before deciding whether to adopt the workflow.
One track on a role-based path.
AI Literacy Program
A shared, practical grasp of what AI can and cannot do, and how to use it responsibly.
AI for Beginners
Confidence with core generative AI concepts through hands-on, guided exercises.
Building LLM Applications
Designing and shipping production LLM apps: RAG, evaluation, guardrails, deployment.
Advanced LLMs
Fine-tuning, advanced retrieval, and agent design for experienced teams.
Scaled GenAI and AI Platforms
Give trained teams a platform to build on, so skill turns into shipped systems.
AI Upskilling and Training
The full role-based path this program belongs to, from literacy to production engineering.
What enablement leads ask us first.
Non-technical and semi-technical business, product, and ops teams. It teaches applying GenAI, not building it, with no coding required.
Yes. We build labs and workshops around the assistants, copilots, and platforms your teams already use, tuned to your environment and data.
Workshops suit focused teams and fast wins; cohorts build durable practice across a function; labs and learn-while-building embed skill deepest. We usually blend them.
Design a role-based program in the formats that fit your teams and your stack.
Workshops, cohorts, and hands-on labs built on your own tools and use cases, so people leave with prompts and workflows they use immediately.