Capability, not curiosity.
Most AI training teaches tools. Tools change every quarter. We build the judgment that outlasts them, in your leaders, your builders, and everyone else who has to make it work.
The tools arrived. The capability didn't.
Most organizations already have AI somewhere in the building. What they don't have is a shared way to decide where it belongs. These are the signals we hear most often before a program starts.
Your people use AI, but nobody agreed how
Individual tool use creates real value and real exposure at the same time. Without shared criteria, you get scattered effort and quiet risk.
There's interest, but no clarity on where to apply it
The conversation stays theoretical because no one has mapped AI opportunities against actual business processes and ranked them.
Leadership isn't aligned on priorities
Technology, operations, finance, and talent each hold a different picture of what AI is for. Investment decisions stall.
You have ideas that never became initiatives
Good use cases surfaced in a workshop months ago and nothing was built. The value evaporated with the enthusiasm.
You depend on vendors for every build
Each new AI system means another external engagement, because nothing internal can design or scale one.
Who are you training?
A director and an engineer need completely different things from the same technology. Pick the path that matches the people, not the trend. Run one, or sequence all three.
For the people who decide where the money goes. Directors, VPs, innovation and technology leaders. They leave able to evaluate AI on business impact rather than vendor claims.
AI Executive Briefing Series
A strategic read on how generative AI has actually evolved and what it changes about productivity. Ends with leaders who can tell a real opportunity from a pitch.
AI Opportunity Mapping Workshop
Identify and rank AI opportunities against your strategic goals. You finish with an opportunity map, a prioritized list of initiatives, and an implementation blueprint.
AI Experimentation Lab
Build prototypes of the prioritized use cases so feasibility gets proven in practice, not on a slide. You leave with validated cases and a concrete roadmap.
For the people who have to make it work. Two tracks, split by how close the person sits to production code, not by seniority.
AI Solution Builders - Functional Track
For analysts, product owners, and innovation managers working low-code and no-code. Advanced prompting, agent design, internal applications, governance. They leave building intelligent agents and reusable assets your organization owns.
AI Engineering Academy - Technical Track
For engineers, architects, and data scientists working full-code. Solution architecture, enterprise integration, agent development, deployment and scaling. The end of depending on a vendor for every build.
For everyone else. Adoption fails when training stays theoretical. This path runs against real work until the tool becomes routine rather than an initiative.
AI Sports - Productivity Challenge
Roughly fifteen minutes a day of gamified challenges across the whole organization. People finish using AI independently to lift their own productivity and cut repetitive routines.
AI Impact Lab - Use Case Development
The standouts from AI Sports turn the use cases they surfaced into working prototypes, so the ideas your own people generated actually get built.
Six dimensions, or it doesn't hold.
Training that addresses only one of these produces enthusiasm without change. We build across all six so AI moves in an orderly way instead of in pockets.
Executive vision and alignment
Leadership agreeing on what AI is for before anyone spends on it.
Use case identification and ranking
Opportunities mapped against real processes, then ordered by impact and feasibility.
Functional and technical training
The people who will build it, equipped at the depth their role actually requires.
Practical adoption by staff
Everyday use across the workforce, not a certificate that goes in a drawer.
Prototypes and actionable initiatives
Ideas converted into something working, while the momentum is still there.
Governance, security, responsible use
Clear rules for what people can put into a model, and what happens to it.
Built by people who ship, not lecture.
Your time zone, not an overnight gap
Sessions run in your working hours. Questions get answered while the work is still in front of you.
Delivered against your own processes
We run the labs on your data and your workflows. Participants leave with work in progress, not notes.
Thirty years of delivery behind it
Backed by Grupo Open, operating since 1995, with 700+ engineers across Latin America.
The same teams that build production systems
Our instructors come from delivery work, not a training catalog. They have shipped what they teach.
We tell you when a program isn't the answer
Sometimes the gap is a hiring problem or an architecture problem. We would rather say so than sell a workshop.
Practical questions.
Where should we start if we've never done this?
Almost always with the Directors path. Training the wider workforce before leadership has agreed on priorities produces energy that goes nowhere. One executive session and an opportunity mapping workshop is enough to know what's worth building.
Do we have to run all three paths?
No. Each path stands alone. Most organizations sequence them because the outputs feed forward, the opportunity map from the Directors path becomes the build list for Builders, but you can start anywhere that matches your gap.
Is this virtual or on-site?
Both, depending on the program. The executive series runs virtually or on-site, most labs run digitally, and on-site delivery is available for anything by arrangement.
How technical are the builder tracks?
The functional track is low-code and no-code, aimed at analysts, product owners, and innovation managers. The technical track is full-code, covering architecture, API integration, deployment, and scaling. The split is by how close someone sits to production, not by job title.
What do we actually walk away with?
Depends on the program, but always an artifact rather than a certificate. An opportunity map and implementation blueprint. Validated use cases. Working agents and reusable internal assets. Functional prototypes and a use case portfolio.
How is pricing structured?
Some programs price per group, others per person, and the organization-wide challenge prices per program. We'll walk you through the full catalog on the call and quote against your headcount and delivery format.
Start with a conversation, not a proposal.
Twenty minutes is enough for us to understand where your organization actually is, and tell you honestly which path fits, or whether you need one at all.