let schedule: OptimizedSchedule = Optimizer::new()
.asset(compressor)
.pricing(pricing)
.constraints(constraints)
.horizon(Duration::from_hours(24))
.interval(Duration::from_mins(15))
.objective(Objective::MinimiseCost)
.solve()?;
let receipt = field
.push_schedule(&schedule)
.site("cork-south")
.asset("COMP-4471")
.mode(FieldMode::RealTime)
.send()?;
println!("Dispatched to field: ", receipt.confirmation_id());Full Stack Energy
Solving most energy challenges means crossing hardware, data and markets at once. We prove the right combination, then deliver it.
Engagements that draw on every layer at once.
Sensing and control, out in the field.
The models that find the value.
Platforms that run it in production.
Where capability turns into captured value.
Compressors pinned at a fixed 80% load, hour after hour, completely indifferent to the electricity price or the solar sitting on the roof. With power prices getting twitchier every year, that indifference was quietly costing real money. The client could smell the arbitrage — they just needed it proven, and proven quickly.
Biogas value chain — dispatch, upgrading & export
Most clients arrive with a question, not a brief — and the answer almost always crosses hardware, data and markets at once. These are the ones we hear most, across generation, industry, mobility and markets.
"Are we capturing the full financial value our assets could be generating — and if not, where exactly is the gap?"
"Our energy costs keep rising — but we can't get a clear, unified view of why, or where the biggest opportunities sit."
"How do we make the right decisions on where to invest, what to charge, and how to optimise?"
"We have a concept or early product — can you build it quickly, robustly, and to a standard we can grow a business from?"
"Are we dispatching against the right price signals — and can we trust the model when the market turns volatile?"
Deep discovery. Your challenges, context and constraints — before a line of anything gets built.
Our people work next to yours, not at arm's length down an email chain. Closer to outsourcing a colleague than hiring a vendor.
Engineering, data science and market experience pointed at the problems that don't fit neatly into anyone's existing lane.
Judged on one thing: did the financial outcome actually move — and can you see exactly why it did?