DOTA AI turns your operational data (SCADA, OMS, AMI, historians, EMS, ETRM) into validated, audit-ready apps. Forecast load, score reliability, manage DERs, settle the market. Your team ships in weeks, in plain English, without a 14-month software project.
Forecast tomorrow’s system peak by zone.
Which feeders have the highest non-technical loss?
Rank circuits by reliability this quarter.
Where is non-revenue water trending up this month?
askForecast peak
4.82 GW
Peak load lands at 4.82 GW around 6 PM, 2.3% above plan on the heat ramp in the West zone.
Non-technical loss
9.1%
Feeders 12-A and 7-C show 9.1% unbilled consumption vs. a 2.3% network baseline.
System SAIDI
78.4 min
SAIDI improved 6.1% to 78.4 min; circuit 4421 drives a third of remaining interruption-minutes.
Non-revenue water
18%
District 4 non-revenue water rose to 18%; pressure anomalies flag a likely main leak.
Trusted by data teams across North America’s energy sector
SCADA, AMI, OMS, historians, EMS, DERMS, ETRM, market feeds: the data exists. But every new forecast, reliability report, or operations app means a 6–14 month IT project, a spreadsheet someone maintains by hand, or a request that dies in a queue. Regulators, reliability standards, and the next event do not wait.
6–14 mo
Typical build time for a single internal energy app
A reliability report, a forecasting tool, or a settlement check sits in the IT backlog for months while it gets scoped, procured, built, and tested before anyone can use it. By the time it ships, the question has often moved on.
40+
Disconnected systems in an average energy data estate
SCADA, OMS, AMI, historians, EMS, ETRM, GIS, and CMMS each hold a piece of the answer, and none of them were designed to talk to each other. Every new app starts by re-integrating the same systems from scratch.
$M penalties
Exposure from a single missed compliance deadline
One late NERC, FERC, or PUC filing, or one number a regulator can trace back to a bad source, can mean fines into the millions, plus the audit scrutiny and reputational fallout that follow.
DOTA replaces your current IT stack with four engines your control team owns: ask, define, scale, and operate.
Ask in plain English. Get validated charts, tables, and insights, with every answer cited back to the source system, row, and formula.
Define a metric once (EFOR, SAIDI, MAPE, hosting capacity, NRW) and it means the same thing across every app, team, and audit.
Turn any analysis into a parameterized app. Roll one feeder’s reliability tracker out to the whole service territory by changing a parameter.
Drag-and-drop control-room dashboards that auto-refresh from live feeds and share to ops, executives, and regulators.
Ask once, then pin it. DOTA assembles auto-refreshing, control-room-grade dashboards wired to your live data (operations, reliability, forecasting, markets, and more) that you can share from the ops floor to the C-suite.
Wired to historians, SCADA, OMS and market signals.
Reliability indices and event rules built in.
Control room to the boardroom, one source of truth.
Every tile traceable with GlassBox AI.
Every DOTA answer shows its work: the source systems queried, the exact rows returned, the business logic applied, and the formula that produced each number. When a regulator, a reliability auditor, or your VP of Operations asks "where did this come from?", you have the receipt.
Each metric links to the system, table and rows it was derived from.
See the exact KPI formula and event rules applied. No black box.
Every query, parameter and result is logged for compliance review.
Validate, override, and approve before anything reaches a filing.
General AI agents, BI suites, and data platforms are powerful, but an energy team still has to teach them the grid from scratch. DOTA already speaks EFOR, SAIDI, and LMP, and connects to the systems that hold them.
See the full comparisonForecasting, reliability, asset health, outage management, AMI, DER, front-office, settlement, billing, and more. Start from a proven app and tailor it to your fleet.
Short- and long-term forecasts at system, feeder, and customer level, including the data-center and electrification load growth reshaping your peak.
Compute IEEE 1366 reliability indices automatically and pinpoint chronic outage clusters by feeder, circuit, and cause.
Monitor wind, solar, and BESS output, curtailment, and degradation against resource forecast.
Analyze LMP, basis, and FTR/CRR value across nodes and zones to inform bidding and hedging.
Measure DR/VPP event delivery and verify behind-the-meter DER dispatch and settlement.
DOTA isn’t built for one kind of asset. It’s built for energy data. Pick your sector across generation, the grid, and markets.
DOTA puts app-building in the hands of the energy professionals closest to the data, while IT keeps governance and security. No data-science team required.
Performance and reliability engineers who own heat rate, availability, and the quarterly NERC GADS submittal.
Reliability and planning engineers who answer for SAIDI/SAIFI, storm response, asset risk, and the DER queue.
Owners of solar, wind, and battery performance who live in inverter, turbine, and BMS telemetry.
Desks and analysts who settle the ISO, manage position and risk, and optimize day-ahead and real-time bids.
The people who answer to NERC, FERC, and the PUC, and who need every number to trace back to a source.
Leaders who must clear the app backlog without sacrificing security, governance, or NERC CIP posture.
Illustrative scenarios across generation, the grid, and energy markets.
Securely connect your historians, SCADA, OMS, AMI, GIS and market feeds. Read-only by default.
Codify your KPIs, event rules and reliability indices in the Knowledge Base, once and for all.
Ask, generate, and assemble apps and dashboards. Validate every answer with GlassBox.
Roll out fleet-wide with templates. Share to ops and execs. Hand auditors the receipts.
Practical, technical writing on the apps utilities actually build.
See DOTA AI build a real utility app on your data in a 30-minute working session.