About Us
Secure Lasting Services builds bidding and trading software for battery storage in US wholesale power markets, starting with day-ahead and real-time offer optimization in ERCOT.
Storage bidding is, at its core, a stochastic control problem wearing a market's clothes. The object that matters is the marginal value of energy in your battery: a curve over time and state of charge, computed against the full distribution of prices rather than a single forecast. Every offer curve, every ancillary commitment, and every real-time deviation trade is a derivative of that one object. Getting it right demands calibrated probabilistic forecasting, honest backtesting, and optimization under uncertainty. That is precisely the work our founder has spent his career doing.
Our founder's path here was anything but linear: mechanical and electrical engineering as an undergraduate, a master's in computer science, more than a decade in software engineering, then a PhD in economics, specializing in Bayesian econometrics. When the current AI wave arrived, he was shipping production machine learning systems: first deep learning models, then two and a half years as a founding AI engineer building decision-support systems in a regulated industry. SLS began as an AI engineering consultancy built on that experience. In 2026 we focused the company on the market where rigorous probabilistic modeling pays its way most directly, every single day.
The economics training matters more here than in most industries, because US wholesale power markets were designed by economists. The price at every node is the shadow price of a welfare-maximizing optimization, an idea that traveled from peak-load pricing theory through spot-pricing research into the settlement software of every ISO. ERCOT's scarcity pricing, the ancillary service demand curves, the two-settlement structure a battery arbitrages: all of them began as economics papers before they became protocol provisions. We traced that history in a survey published in our resources: How Economists Have Shaped the US Electricity Markets. For an economist, this market is not an exotic domain to adapt to. It is the one industry built in the language he was trained in.
We came to power markets with a conviction formed by that background: the operator's core engine is optimization, not a black-box price oracle. Nobody reliably predicts prices. What you can do is model the distributions that matter, with information available before each deadline closes, and construct the offers that are optimal against those distributions. Then you measure the result honestly: walk-forward, point-in-time, attributed between forecast and execution, against benchmarks anyone can verify. ERCOT is where we prove that discipline in public, on the most transparent market data in the world. The engine underneath is market-agnostic by construction, built to travel as storage economics spread to other markets.
That last part matters most in this industry. Vendor uplift claims are marketing figures on non-comparable baselines. Ours is a business built on the opposite premise: every number we show a client is one they can audit.