Autonomous AI discovery built for energy operators.
Your platform already holds the asset telemetry, the load forecasts, the dispatch records, the outage logs, and the weather feeds. DecisionBox runs discovery against all of it overnight — and ships a ranked list of findings by the time you walk into the weekly operations review.
Built for Heads of Asset Management, Heads of Operations, and VP Engineering at utilities, grid operators, renewables operators, and energy retailers.
Your asset dashboard shows fleet uptime. Not the unit drifting toward next month's outage.
DecisionBox runs them while you sleep. An autonomous AI agent picks what to investigate, runs the analysis, and re-checks every number against your data from a second angle before it ships. By morning you have a ranked list of findings — each with the affected asset, region, or window — and a numbered recommendation.
How the agent picks what to investigateWhat stays hidden when the questions don't get asked.
Three benchmarks every energy operator already knows by heart. The discovery loop runs against all of them in a single pass — and surfaces where your numbers diverge from the curve.
Three findings the agent surfaced on a grid operator's data.
One overnight run. The agent picked the analysis areas, ran them against the platform's data, re-checked every number, and ranked what to fix. Three shapes of finding — one drift in a single asset, one pattern across forecast and dispatch, one anomaly the fleet aggregate was hiding.
Point it at your operations data. See what the discovery loop ranks before the next weekly operations review.
Same data, five sets of questions.
One discovery run produces findings ranked for the team that owns the metric. Each panel is what the agent investigates in your data — questions it picks on its own.
The asset that started drifting two months ago.
Your SCADA dashboard shows current readings. The agent reads telemetry trend by asset against your historical incident library — and ranks assets whose drift signatures match past failures before the failure happens. Pair with Detect operational anomalies.
- Which assets show drift signatures matching past failures
- Where efficiency degradation is accelerating beyond normal aging
- Which substation or feeder is trending toward its operational ceiling
- Where vibration, temperature, or load patterns disagree with manufacturer profiles
- Which install cohorts show shared failure patterns
Three properties your weekly operations review can defend.
DecisionBox is built so the findings on the ops-review call are not the kind that fall apart under a follow-up question.
Sees what nobody had time to look for.
The agent picks the questions. It reads every asset against every telemetry trend, every region against every forecast curve, every dispatch decision against the historical outage record. The investigations nobody had time to formally request happen anyway — overnight, ranked by morning.
Every number you'd defend in the operations review.
An independent re-check runs every number from a second angle. If the agent can't reproduce its own claim, the finding is dropped or adjusted with the corrected number, visibly. Every step of the agent's reasoning stays attached to the finding for review.
Your operational data stays where it already lives.
Run DecisionBox on your own infrastructure or as a managed service — either way, asset telemetry, customer records, SCADA outputs, and dispatch logs never leave your environment. The platform is open source, so your team can see exactly how it works and what it touches.