AI UPSKILLING AND TRAINING
AI skills development for enterprise teams
We help business teams and engineers build practical AI skills, with courses matched to their role, starting knowledge and intended outcomes.
- Role-based tracks, from literacy to production LLM engineering
- Hands-on, built around your stack, not slideware
- Learn while building the systems your teams will own
AI training matched to your role.
We tier programs so each audience gets what it can actually use, from a shared literacy every function needs to the hands-on engineering skills that let teams ship production LLM applications themselves.
AI Literacy Program
For all roles, no technical background required. Build shared understanding of AI capabilities, limits and responsible use.
NEW TO AIAI for Beginners
For people new to AI. Practise prompting, check responses and complete guided everyday tasks.
BUSINESS AND OPSAI and GenAI Training
For teams familiar with AI basics. Apply generative AI to practical product, operations and business tasks.
ENGINEERSBuilding LLM Applications
For engineers with programming experience. Build an LLM application with retrieval, evaluation, safeguards and deployment.
PRACTITIONERSAdvanced LLMs
For experienced LLM practitioners. Compare fine-tuning, retrieval and agent approaches through measured experiments.
Learn through your own business context.
Hands-on learning tied to real work
Engineers build on the real patterns they will use in production; business teams work through use cases from their own functions.
Tied to your roadmap
New skills land on live work, so learning has somewhere to go immediately instead of fading after the session ends.
Learn while building
Where it fits, training runs alongside a delivery engagement, so teams learn by shipping the systems they will own.
Tiered by ability
Beginners and advanced practitioners run different depths, so nobody is bored and nobody is lost.
You can buy the platforms and hire the vendors and still hit a ceiling.
The engineering track covers production issues beyond prompt basics.
Demonstrate skills relevant to each role.
**Role-based proficiency.** Assess participants on tasks drawn from the work their role actually performs.
**Applied practice.** Use a reviewed work sample or engineering exercise to demonstrate learning.
**Sustained capability.** Agree follow-up checks and internal support so learning carries into day-to-day work.
Capability compounds when it is aligned with ambition and a platform.
Enterprise AI Services
The wider AI practice this sits within, from strategy through build, scale, and run.
ALIGNAI Strategy and Consulting
Align the capability you build with the ambition and roadmap it is meant to serve.
PLATFORMScaled GenAI and AI Platforms
Give newly built skills a platform to build on, so learning turns into shipped systems.
What enablement leads ask us first.
Role-specific. We tier content by audience and ability rather than teaching everyone the same material, so each track transfers directly to what people actually do.
Yes, and it works best that way. When teams learn while building the systems they will own, skills stick and adoption accelerates.
We design around your stack and real scenarios from your business, so what people learn applies immediately instead of staying theoretical.
Against capability outcomes agreed up front: proficiency levels, engineers able to ship independently, and reduced reliance on external delivery.
Design a training path that matches your roadmap and your teams.
Tell us where your capability gaps are and what your teams are building next. We will shape a role-based path that lands on live work.