Five practices that fit together
Most engagements open with the question of what is worth building, or with an audit of what you already run, then go where the findings point. Sometimes that is code, sometimes training, sometimes policy. You can take one practice on its own, and plenty of clients do.
Which parts of the business AI improves, what the return looks like once someone checks the arithmetic, and what to do first. Then we help you do it.
- Workflow mapping
- Sizing the opportunity
- Build, buy or wait
- Operating model
We do not run a course catalogue. We take your documents, your tools and the tasks in front of people this week, and build the sessions around them. Then we redraw the roles and handovers the new tools have changed.
- AI literacy programme
- Team enablement on your own work
- L&D design
- Organisation and role design
Our engineers and coding agents ship production AI with logging, evaluation and human review in place from the first commit.
- Agents and automation
- Retrieval and knowledge systems
- Evaluation suites
- Observability and audit trails
04
AI audit
We go through every AI tool, licence and system in the business. We work out what each one costs and returns, and hand you a written picture you can make decisions from.
- Tool and system inventory
- Spend and usage
- Does it do what it was bought to do
- Risk and exposure
We classify the systems you run and close the gaps against the rules that bind you. We leave documentation that reads as evidence rather than as intent.
- Classification and role
- General-purpose model posture
- DPDP Act readiness
- Impact assessments
Start with a conversation
Thirty minutes, no deck. Tell us what you have tried and where it stalled. We will tell you what we would look at first, and whether we are the right people for it.