Why We Built PINN AI
Two decades in oil & gas taught us one hard truth: guessing gets expensive — fast.
For more than 20 years, we’ve watched subsurface decisions driven by gut feel, SWAGs, and legacy workflows.
Sometimes it worked.
Sometimes it didn’t.
We’ve been around long enough to see both ends of the curve—from marginal wells to four-digit initial oil production rates that redefine a development plan.
We’ve seen plays where nearly anyone would have hit pay. And others where only rigorous integration separated success from disappointment.
The gap wasn’t intuition.
It was the lack of consistent science applied at scale.
We’ve lived with those outcomes — operationally, financially, and reputationally.
Subsurface data has always existed.
What hasn’t — until recently — is the ability to combine it, learn from it, and act on it systematically at scale.
The Gap No One Was Talking About
When we stepped back and looked at the industry as a whole, the numbers were staggering.
More than 90% of U.S. operators do not have — and do not use — AI or data science in subsurface decision-making.
The majors and supermajors do. They’ve had dedicated data science teams for years. That advantage is a major reason they’ve consistently outperformed in shale while others struggled or failed.
Most operators simply can’t afford that talent, don’t know where to start, or are too busy fighting daily fires to build it internally.
That’s not a failure of ambition. It’s a failure of access.
So We Built It For Everyone.
PINN AI was created to put institutional-grade subsurface intelligence into the hands of every operator — from family-owned independents to global majors.
Our platform combines subsurface data, domain expertise, and advanced data science to replace guesswork with evidence.
We offer it as secure software-as-a-service (SaaS) or deploy it on-premises — air-gapped if required — so data never leaves your building.
Same intelligence. Same rigor. No compromises.
Math that Drills Deeper
Meet The Team
Founders representing decades of operational and data science experience in energy
PINN AI was founded by industry veterans who’ve lived on both sides of the problem — operating assets in the field and building advanced analytical systems to understand them.
20+ years in oil & gas across operations, finance, and asset development.
Has led subsurface and capital decisions where technical rigor, economic accountability, and real-world outcomes intersect.
Brings an engineering mindset, financial discipline, and applied data science to replacing gut-feel decisions with evidence.
A subsurface scientist and data scientist specializing in machine learning, statistical modeling, and geophysical systems.
Spent her career translating complex earth data into production-grade analytical models used for real operational decisions.
Leads PINN AI’s core architecture, modeling, and applied AI systems.