The Problem AI Needed to Solve in Critical Infrastructure

The Infrastructure Problem That Started It All 

A year ago, our CEO and Co-founder, Sean Shahini, joined Cota Capital to discuss a problem we believed would define the future of critical infrastructure. 

That problem wasn’t AI. 

It was fragmented information. 

Across telecom and other critical infrastructure industries, every project depends on thousands of documents, disconnected systems, and decades of accumulated knowledge. Before engineers can design, validate, permit, or build anything, they first have to answer a simple question: 

What is actually true about this asset? 

That challenge slows every stage of execution. Teams spend valuable time searching for information, reconciling conflicting records, and validating data before meaningful work can begin. 

In the conversation below, Sean explains why this problem exists and why it became the foundation for Inorsa. 

A lot has changed since this interview was recorded. 

Over the past year, we’ve expanded well beyond document intelligence to build The AI Platform for Critical Infrastructure. 

Today, Nora orchestrates specialized AI Coworkers that ingest, validate, and generate work from infrastructure data, transforming fragmented information into trusted operational intelligence that helps organizations automate execution and deliver completed outcomes. 

But while the platform has evolved, the problem hasn’t. 

Critical infrastructure organizations still face increasing complexity, growing project volumes, and information scattered across documents, systems, and teams. 

The need for trusted operational intelligence has only become more important. 

Looking back at this conversation is a reminder that successful technology companies don’t succeed because the market changes every year. They succeed because they stay relentlessly focused on solving the right customer problem. 

That’s the problem we’re still solving today.