Energy data changes continuously.
Optimization should keep up.
Energy is a chain of constrained decisions. Optimizing each one in isolation leaves value behind. OSM connects planning, trading, scheduling, and operations through one optimization layer.
Every energy system runs on constrained decisions. Almost optimal is expensive.
Energy decisions connect across markets, assets, and time. OSM optimizes planning, bidding, scheduling, and dispatch together.
Energy decisions are connected across time and across the system. Capacity plans shape market exposure. Forecasts and bids shape asset schedules. Prices, grid limits, contracts, and asset state change dispatch. Optimizing each step in isolation leaves value behind.
OSM turns operational data, forecasts, objectives, and constraints into mathematical optimization models. The same layer supports capacity planning, day-ahead bidding, storage scheduling, and power dispatch. Exact formulations return feasibility and optimality evidence with the result.
The optimization layer is designed to work with existing data and operational systems. Start with one problem, then reuse inputs, models, and constraints across the next. OSM owns the optimization infrastructure while your team keeps control of the energy system.
A small team of optimization researchers and engineers in Germany and the US. We develop mathematical optimization systems and put them into production. Between us, we have built systems that optimized billions of transactions and saved millions of dollars. We bring that rigor to energy.
Built by people from
Our optimization stack comes from decades of research and is designed for production use. Two foundational papers behind OSM were accepted at VLDB 2026.
VLDB 2026 · Accepted ∎
VLDB 2026 · Accepted ∎
arXiv 2026 · Preprint ∎