Magdalena Picariello — CEO
“We have to do AI” - concluded the board meeting. The goal is clear: Don't miss out. That mandate is yours. So you start. You roll out Copilot. You run a few AI pilots. You give access to “AI tools”. But the reality hits you fast: - Every vendor promises the “ultimate AI agent” - IT says it is “not feasible” - Departments try random ideas - Employees experiment chaotically - Pilots don’t result in ROI - And nobody knows which use cases actually matter That’s the silent killer of AI. Not the model. Not the data. Not the prompts. The wrong use cases. Most AI Portfolios are full of shiny objects. They have two ideas worth building. Three that look like a low-hanging fruit but aren't. And seven shiny objects that will drain your budget. So what’s next? You stop guessing. You start killing shiny objects. And ship the rest as software people use on Monday. That's the program I run. Three pillars. Detect. Bi-weekly sounding board. We evaluate your ideas. Bad ones die early. We keep 2-3 ones worth building. Plan. Roadmap with system architecture, milestones, and costs. The plan your board can sign off on. Build. MVP shipped by my engineers. Not a demo. Not a prototype. Real software: system architecture, data pipelines, monitoring, evals, CI/CD and all that jazz. Plan in 6 weeks. Build in 6 months. Results our clients can show in board meetings: - 416 hours saved annually on real estate analytics (Swiss Pharmacies Chain) - 504 hours saved annually on report generation (Swiss Manufacturer) - 8000+ new customers thanks to better credit risk model (MPower, Energy) - 60K+ CHF savings per R&D project (Scrona, Deep Tech) - 50-100K CHF savings on marketing campaigns (ImmobilienErben, Real Estate) - 3M+ CHF saved on strategic purchases (Zugerland Verkehrsbetriebe, Transport) - 18M+ CHF annually from production optimization (Axpo, Energy). If you just got the AI mandate and your portfolio feels way too heavy: Book an AI Portfolio Audit. 2x30 mins. I will tell you what to kill first. → https://datali.ai/en/book-a-call
Stackforce AI infers this person is a SaaS expert specializing in AI solutions and data engineering.
Experience: 11 yrs 6 mos
Skills
- Artificial Intelligence (ai)
- Data Engineering
- Machine Learning
- Data Analytics
- Technical Product Development
- Risk Analytics
- Financial Analysis
Career Highlights
- Saved clients over 183M CHF through optimized AI solutions.
- Expert in transforming AI ideas into actionable software.
- Proven track record in mentoring future AI professionals.
Work Experience
University of Lucerne
Lecturer in AI Management (0 mo)
Lucerne University of Applied Sciences and Arts
Lecturer in AI (1 yr)
Zazuko GmbH
AI & Data Engineer (5 yrs 8 mos)
Kickstart Innovation
Advisor in AI & Data Analytics (3 yrs)
Constructor Learning
Lecturer in Machine Learning (6 yrs 1 mo)
Datali
CEO | AI Solutions Architect (6 yrs 11 mos)
swissQuant Group AG
Quant Engineer (2 yrs 1 mo)
Something different
Career break (11 mos)
Axpo Group
Data Science Intern (9 mos)
UBS
Quant Engineering Intern (5 mos)
IBM
Junior Data Analyst (1 yr 7 mos)
Education
Master of Arts (M.A.) at University of St.Gallen
Master's degree at Jagiellonian University
Student exchange at Pontificia Universidad Católica del Perú
