Your Data Isn’t a Moat. Yet.: The Vertical AI Architecture for Decision-grade Production

Every enterprise has proprietary data. Far fewer have an AI system they’d trust to make a decision that carries real consequence. RAG can retrieve the right context, but production takes more than retrieval: governed data with lineage, domain-specific evaluation, workflow integration, and execution a human can override.
Akash Sharma draws on Enverus’ work taking AI to production in energy, one of the hardest domains there is, where a wrong answer is a misallocated capital budget, a failed compliance filing, or a safety incident. If a system earns trust there, the architecture behind it holds anywhere. He lays out that architecture, the Vertical AI blueprint for turning proprietary data into decision-grade systems, then names why promising pilots stall, what production-ready systems do differently, and how to find the weakest layer in your own program. You’ll leave with a diagnostic you can run on your own architecture on Monday, and a clear read on what to build next.