About Us
Useful AI, built around your business.
In the Muisca culture of the Colombian Andes, the Zipa was the leader who guided people toward what mattered. That idea sits at the heart of what we do. We started Zipa because too many businesses were getting lost in the AI conversation pulled toward the impressive rather than the useful. We’re here to change that: to lead you toward the AI investments that genuinely move your business forward, and build them with you
Who Are We
Two people with deep roots in data and a shared frustration with AI that looks good on paper but never quite lands in practice. Between us, we cover the full journey: from figuring out what’s worth building to actually building it.
Our Mission
To make AI useful for the businesses that need it most. Not headline-grabbing, not investor-deck material. Practical, well-built solutions that work on a Tuesday afternoon when nobody’s watching.
What We Do
We sit with you, understand your business, and find where AI can make a real difference. Then we help you get your data ready, and we build it. Strategy through to delivery, without the handoffs and the gaps that usually swallow projects whole.
Our team
Bart Pepping
Bart has built and delivered data science solutions across banking, retail, and international organisations. His work spans customer retention, marketing, logistics, and financial risk — the kind of breadth that comes from years of being dropped into complex problems and being expected to make them work. Most recently, he led the development of a tool that helped unlock over a billion dollars in IMF lending capacity.
Valentina Giraldo
Valentina knows what it takes to get data working inside a real organisation — not in theory, but in the messy, deadline-driven, politically complex reality of it. She has spent her career inside demanding industries helping businesses build the data structures, governance, and processes that turn scattered information into something a company can actually rely on and act on.
Her specialism is data strategy: figuring out what a business needs, what it already has, and how to close the gap in a way that holds up over time. That’s exactly what SMEs need before they invest in AI — clarity on their foundations, and a strategy that makes the investment worthwhile rather than wasteful.
