AI grounded in reality.
Hands-on sessions with the tools you have
“How do we actually use this on our own work?”
Team workshops
Half a day or a full day with your team, working on their own files rather than made-up examples.
“How do we keep this from fading after a month?”
Ongoing training
A session a month. The tools keep changing and people keep joining; this keeps everyone level.
“Our analysts and our ops team need different things.”
Role-specific tracks
Separate sessions for each group, built around what they do all day, so nobody sits through an hour meant for someone else.
Deciding what to do before anyone builds anything
“Where would this actually save us time?”
Readiness audit
We work through your workflows, tools and data, then write up where the time goes and what’s worth changing.
“Everyone has ideas. Which ones are worth doing?”
Opportunity assessment
We take the list of things you could do with AI and put numbers against them: what each one would save, what it would take to build, and which two to start with.
“What should we roll out, and what should we hold back?”
Leadership advisory
Time with the people making the calls: what to do first, what to leave alone, and how you’ll know if it’s working.
Systems that fit what you already run
“Could something handle this step without us?”
Agents
An agent that does one job in your workflow: triaging requests, pulling figures together, drafting the first version of a routine document. You sign off its work until you’re happy not to.
“Why is the answer always in someone’s head?”
Knowledge bases
Your documents, policies and past work in one place the team can ask questions of, with answers that show where they came from.
“What happens when it breaks and we don’t know why?”
Support & maintenance
We keep an eye on it, fix it when it breaks, and extend it as the work changes.