Workshops
Short sessions on the client's own stack. The first level of the offering, scalable to the whole workforce.
See the workshopsAI School
AI School: the in-house academy that sets the standard for working
The model plus role-based training, with internal capacity to sustain it, assessment included.
Architecture
- Group level, power users: cohorts by role, more than 50% hands-on, real automations live in production before finishing.
- Leadership level, 1:1: a personal agent per executive, connected to their data and email. They decide, the agent executes.
- Train-the-Trainer: an internal network of trainers to sustain the program autonomously.
The differentiator
- Learning paths come from the client's own discovery: real use cases with an owner, a validated prompt, and a KPI. Never a canned catalog.
- Governance as a module: usage policy, approved tools, evidence of AI Act art. 4 compliance.
- Sign-off KPIs at 3 layers: individual commitments, per-case KPIs, business results. Never attendance or hours delivered.
Why now
- FUNDAE-subsidized: AI is a priority sector in 2026.
- AI Act art. 4: mandatory AI literacy since Feb 2025, penalties in force from Aug 2026. A budget with a deadline.
- If it follows Consulting, it starts with the map already done: zero weeks of duplicated assessment.
Base realInstructor for Nestlé's Everyday AI program (on Copilot). A 13-week AI Academy currently running at a food-industry holding group (Claude + Lovable): 25 power users plus 1:1 leadership coaching, a catalog of 30 to 40 use cases sourced from discovery.
AI School · learning paths
From how each role works today to how it will work using AI well
One itinerary per level of maturity, from basic use through to production. Each cell becomes a use-case sheet: task, tool, estimated saving, indicator and owner.
| Role | FoundationalUse AI well | Intermediatebuild with AI | Advancedoperate in production |
|---|---|---|---|
| SALES | Assisted drafting of proposals, emails and visit preparation. ESTIMATED SAVING≈ 4 h/week≈ 190 h/year per rep | A proposal assistant wired to the CRM and the catalogue. ESTIMATED SAVING≈ 6 h/week≈ 280 h/year per rep | A semi-automated proposal flow with human review. ESTIMATED SAVING≈ 9 h/week≈ 420 h/year per rep |
| FINANCE AND ADMIN | Summaries, reconciliations and assisted email. ESTIMATED SAVING≈ 3 h/week≈ 140 h/year per person | A semi-automated monthly report, straight from the source data. ESTIMATED SAVING≈ 5 h/week≈ 235 h/year per person | Closes run by agents wired to the ERP, with human validation. ESTIMATED SAVING≈ 8 h/week≈ 375 h/year per person |
| OPERATIONS | Assisted documentation, reports and incident handling. ESTIMATED SAVING≈ 5 h/week≈ 235 h/year per person | Automated flows over the team's own processes. ESTIMATED SAVING≈ 8 h/week≈ 375 h/year per person | Automations in production, with quality control and a named owner. ESTIMATED SAVING≈ 12 h/week≈ 565 h/year per person |
| LEADERSHIP | A daily summary and assisted document analysis. ESTIMATED SAVING≈ 3 h/week≈ 140 h/year per executive | A conversational dashboard over their own data. ESTIMATED SAVING≈ 4 h/week≈ 190 h/year per executive | A personal agent wired to data and email: the team decides, the agent executes. ESTIMATED SAVING≈ 6 h/week≈ 280 h/year per executive |
Indicative estimates per person, worked out over 47 working weeks. The real saving depends on the volume of tasks, on adoption, and on how far it is integrated.
Real stories with Ironhack
AI Consulting
Phase by phase, with estimated savings per task and a go / no-go decision at the end of each one.
See the consultingReal stories with Ironhack
The same activation, consulting and school model, already delivered.
Real stories with Ironhack