Training and consulting in AI and technology
Companies that pay for AI tools their people don't use, executives who need to decide what to do about AI without relying on a vendor's pitch, and technical teams that need to catch up.
Who it's for
- Executives: general management and the executive committee.
- Business teams: finance, operations, sales, people.
- Technical teams: development, data and infrastructure.
Training
Executive AI workshop
A short session for executives: what AI can and can't do today, cases from their industry, and how to decide where to start
Role-based programs
Hands-on training with each area's own cases and tools, not generic courses
Corporate copilot adoption
Support so the company actually uses the AI assistant it already pays for (the one in its productivity suite or another), with cases by area and usage measurement
Technical training
Data, applied AI, AI-assisted development and good practices for technical teams
Consulting
AI strategy and roadmap
Use cases ranked by value and feasibility, with a staged roadmap
Data and AI governance
See the next section
Technology consulting
Architecture, tool selection and technical review of projects, with no licensing interests
Data and AI governance
What it solves
Nobody knows for sure who owns each piece of data, who can use it, what personal data is being handled, or which AI tools people use and with what information. That's a risk for any organization and an obligation for government.
Roles and owners
Who owns each data domain and who answers for its quality
Inventory and classification
What data exists, where it lives, and which of it is sensitive or personal
Data policies
Access, quality, retention and use, aligned with each country's data protection regulations
AI usage policies
Which tools are allowed, with what data, and under what human oversight
AI use case inventory and risk assessment
Which AI cases are underway, what risk each one carries, and what controls it needs
Implementation and follow-up
Putting the policies into practice in the systems and measuring compliance
It connects with the data and analytics line (data assessments feed the inventory) and with AI automation (every automation enters the case inventory with its assessment).
Typical deliverables
- Program materials tailored to the company and its cases.
- Measurement of actual tool usage before and after the program.
- An AI roadmap with ranked cases.
- A data and AI governance model: roles, inventory, policies and an implementation plan.
How it connects with the other lines
It closes every project in the other lines: the handover is training.
Workshops and roadmaps surface cases for automation and data.
It's a low-risk entry point for a new client.
How we measure success
- Actual tool usage 30 and 90 days after the program.
- Use cases participants launch on their own.
- Participant evaluations.
What we don't do
- Generic off-the-shelf courses that don't touch day-to-day work.
- Recommend a tool because we resell it.
Start with an assessment
We start with a fixed-price assessment, and from there each phase comes with its own fixed price.
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