Most utility AI projects fail because they're built like software-company AI projects. We don't build them that way.
Most energy and utility companies are trying to use AI in their operations but aren't sure where it actually pays off, how to build it in their real environment, or how to ship it safely under audit. Implementation is where most of these projects fail.
Figuring out where AI is actually worth doing in your operation, and where it isn't.
Building the systems themselves, inside your environment. Agents and model integrations on your infrastructure, against your real data, shipped to production by us.
Shipping under audit. The engineering discipline that holds up to a regulator: evals, guardrails, spec-driven development, continuous delivery.
Measurably accelerating your own engineers with AI in their daily work.
When a VC, PE firm, or acquirer is about to write a check on an energy or grid-tech company, you need someone independent to look at the technology and tell you what's real. We analyze the risk and deliver a memo for the investment committee.
Does the architecture actually scale, or only the demo?
Do the claims hold up under real load and real data?
What would it cost to take the prototype to production?
Where's the technical risk, and where's the key-person risk?
How mature are the target's AI practices?
There aren't many people deep in both energy/utilities and modern AI engineering at the same time. Pete Baker spent two decades inside grid analytics, twice as VP of product, and is now in hands-on agentic AI development. His PhD is in agentic AI for grid infrastructure.
Modern AI tools have widened the range one experienced person can cover, enough to work the full arc from deciding what to build, through building it, to running it in production. What we build with your team stays with your team.
Safe AI isn't built on vibes. The essential controls that have long been a mainstay of regulated industries are the foundation for safe, effective AI. Our combination of AI engineering and regulated-industry discipline is what makes production AI actually run.