The governed decision layer for
home energy
Multi-asset optimisation across heat pump, battery, solar PV, and hot water — with every decision explained.
Your customers have heat pumps, batteries, solar panels, and smart tariffs. But every device runs its own logic, decisions lack an evidence trail, and you’re managing three vendor layers to optimise a single home. As Ofgem tightens its AI governance requirements, you need a decision layer that coordinates the whole system — and can prove why every decision was the right one.
The Home Energy Agent
One governed agent. Two headline capabilities. Every steering decision traceable from trigger to outcome.
System Modelling & Prediction
Models the entire home — heat pump, battery, solar PV, hot water cylinder — as a single coordinated system. A dynamic digital twin compares predicted and observed performance in real time, detects drift, and quantifies gaps across every asset. Not single-device monitoring — genuine whole-home intelligence.
Multi-Objective Optimisation
Balances billing, energy cost, comfort, carbon intensity, and flexibility revenue simultaneously — with visible trade-offs, not hidden compromises. Every steering decision carries full evidence: what was optimised, what was traded off, and what policy bounds applied. See why every decision was made.
Five questions we answer
The decisions your teams face daily — answered with evidence.
Is this home’s energy system performing as designed?
The digital twin models the whole home — heat pump, battery, solar PV, hot water cylinder — as a single coordinated system. When performance drifts from prediction, you see the gap and the contributing factors immediately.
Are we optimising across cost, comfort, carbon, and revenue — or just one?
Most platforms optimise for a single objective. The Home Energy Agent balances billing, energy cost, comfort, carbon intensity, and flexibility revenue simultaneously — with visible trade-offs, not hidden compromises.
Can we explain every automated decision to a regulator?
Every steering action — when to charge, discharge, heat, or export — carries an evidence pack: what data drove it, what model was used, what alternatives were considered, and what policy bounds applied.
What flexibility value is each home delivering to the grid?
See exactly what each home earned from grid services this month. Broken down by asset, by programme, by time period. Not aggregated — per-home, per-decision.
How do we scale from 20 homes to 200,000 without losing visibility?
Fleet dashboards for portfolio-wide performance. But every metric drills down to the individual home, the individual decision, the individual evidence pack. Scale without opacity.
How it works
Five stages from first connection to continuous improvement.
Connect
The agent connects to each home’s energy assets — heat pump, battery, solar PV, hot water cylinder. Data quality and consent artefacts are established.
Model
A whole-home digital twin is built, modelling all assets as a single coordinated system. Thermal dynamics, generation profiles, storage capacity, and tariff structures are calibrated.
Optimise
Multi-objective optimisation balances cost, comfort, carbon, and flexibility revenue. Every steering decision is policy-bounded and evidence-carrying.
Respond
Automated participation in flexibility markets — balancing services, DNO procurement, smart tariff response. Each dispatch is logged with full decision provenance.
Learn
Outcomes feed back into the home model. Predictions improve. Optimisation strategies refine. Fleet-wide patterns surface. Institutional knowledge is captured.
What you buy
Four capabilities that turn home energy data into governed, revenue-generating value.
System Performance Intelligence
Multi-component digital twin modelling the entire home as one system. Prediction vs actual, anomaly detection, and drift quantification across heat pump, battery, solar, and hot water.
Tariff & Cost Optimisation
Real-time response to smart tariffs and dynamic pricing. Bill minimisation, self-consumption maximisation, and intelligent scheduling — balanced against comfort and carbon objectives.
Flexibility & Revenue Intelligence
Automated participation in flexibility markets with per-home revenue quantification. Balancing mechanism, DNO services, and capacity market access — with full decision provenance.
Governed Decision Trail
Every steering decision logged, explained, and auditable. What was decided, why, what alternatives existed, and what policy bounds applied. Ofgem-ready from day one.
Outcomes by function
How each part of your organisation benefits.
Head of Digital / Innovation
A decision layer that works alongside Kraken or Kaluza — not instead of it. Reduce multi-vendor complexity and add auditability without replacing your retail platform.
Head of Flexibility / VPP
See what flexibility value every home is delivering, broken down by asset, programme, and time period. Stack revenue across wholesale, balancing, and DNO services.
Regulatory / Compliance Director
An audit trail you can show a regulator. Every automated decision explainable, every policy bound documented, every override logged.
Social Housing Asset Manager
Portfolio-wide performance across thousands of homes. Verify that retrofitted systems are delivering the savings promised to tenants and funders.
Installer / Field Engineer
Verify the system is performing as designed at commissioning. Benchmark against predicted performance. Evidence packs travel with the installation.
FAQ
Start with a pilot
Pick your starting point — system performance intelligence or flexibility revenue.
20–1,000 homes. 6–8 weeks. Assist-only. See results, then scale.
