AI, ML, and advanced analytics for utility teams. Built alongside your engineers, grounded in real data, architected so your team owns it after we leave.
Four service areas, each delivered with our own tools and models: your data, your engineers, your ownership after the engagement ends.
Grid modernization strategy, implementation oversight, and regulatory support, backed by Monte Carlo analytics that hold up under cross-examination. Provenance-tracked data across a variety of sources. No magic numbers; every assumption is auditable.
SAIDI/SAIFI-derived budgets, burn-rate alerting, Weibull regime detection, CEMI equity overlay. The SRE methodology, adapted for distribution.
Outage prediction, load forecasting, hosting capacity, predictive maintenance. Trained on your data, documented so the team maintains it long after the engagement.
For projects where deliverable power is the schedule risk. Behind-the-meter generation modeled as a development decision, not a procurement line item. Monte Carlo across utility milestone slip, equipment lead times, fuel and tariff exposure, and stranded-capex outcomes.
In the power sector, the word fits. The grid will never be "done." Load patterns shift. Distributed resources multiply. Regulations evolve. Infrastructure ages even as it's upgraded. Every modernization cycle solves today's problems and reveals tomorrow's—the boulder always rolls back.
Most people hear "Sisyphean" and think futility. Camus saw it differently. In his reading, Sisyphus finds meaning not in reaching the summit, but in the discipline of the climb. The struggle itself is the craft. That's the philosophy behind this company: sustained, iterative improvement beats silver bullets every time. You won't modernize the grid in one project. But you can make each cycle leave the system measurably better than you found it.
The struggle itself toward the heights is enough to fill a man's heart. One must imagine Sisyphus happy. — Albert Camus, The Myth of Sisyphus
That's why I build tools and internal capabilities instead of writing reports. Internal team capabilities and tools compound, while transformation decks and reports stagnate beginning with publication. A well-built optimization model gets used every week, refined every quarter, and eventually becomes part of how your team thinks about the problem. The climb continues, but you climb smarter.
Transformation projects die at Year 3. Small, durable wins compound. We ship something your team uses in week six, then again in week twelve.
The grid isn't a spreadsheet. Ranges, distributions, and regime changes are what your decisions actually depend on. Not single numbers.
Every model is documented, every notebook is yours. The day we leave, your team owns the thing. No API keys held hostage, no "support retainer" trap.
15+ years across generation and distribution means we start from what the engineer actually sees. Not what a product demo promises in a deck.
30 minutes. Share what you're trying to move. I'll tell you whether I'm the right person for it, and if not, who I'd call instead.