I'm an AI Strategist with a Solutions Architect background, on a quest to help teams turn AI ambitions into business decisions. I've spent 12+ years framing business cases for data & AI, then shaping the results into artifacts a decision-maker can open and audit: benchmarks, cost models, reports, decks, as Streamlit apps, JS websites, After Effects videos or Excel spreadsheets.

My work at Magellan is an even mix of building and advising on AI strategy for a CCaaS product. Before an AI feature lands on a roadmap, I've usually built a rough version myself. That's how I know where it breaks and what it costs, not just the pitch. Lately that means benchmarking speech-to-text models and drafting cost-per-audio-minute models to feed a make-or-buy recommendation.

I'm also a university lecturer in MLOps, Big Data & NoSQL, and a member of the Streamlit Creators Ambassador Program.

• ✨   Practice decision craft in public: benchmark → cost model → recommendation, shipped as artifacts that look better than they need to.
• 👨🏽‍🏫   Help technical ICs move up the value chain now that agents write most of the code. Someone still has to pick the right problem, cost it honestly, and stand behind the recommendation.
• 🎥   Consistently produce YouTube videos around Streamlit apps and AI insights for technical ICs to management.

• 💵   I design business cases for AI features: market use case, risks, value proposition, and a first-pass financial model that tells you whether an idea deserves a full P&L.
• 🧑‍💻   I build rough versions of AI features to feel where the integration breaks, and I still explore customer datasets for value along the way.
• 👥   I teach Docker/APIs/PySpark to master students in statistics & BI here. I also talk at local meetups and write tutorials.
• 👀   You can find me 🏸 on a badminton court playing mixed doubles or 🎹 near a piano trying to improvise over pop songs.