From data to action
Decisions with confidence: forecasts → alerts → suggested actions, pushed to your tools.
Energy · Analytics
AI Energy Analytics
Forecast demand and PV, detect anomalies and optimize energy costs with transparent, explainable models. Results flow back to settlement, billing and portals.
ExplainableNear real-timeAPI-first
Explainable by design
Feature importance, reasons and confidence — no black boxes for regulators or finance.
Fast to adopt
Uses the same normalized data as Gateway/Platform. APIs and exports fit existing flows.
Key features
The core capabilities to forecast, detect and optimize — explainable, auditable and production-ready.
Forecasts
Short/long-term demand & PV forecasts with calendar/temperature effects and uncertainty bands.
Anomaly detection
Find outliers, missing/late reads and drift. Each alert includes cause hypotheses and context.
Cost optimization
Tariff/TOU scenarios, storage scheduling and curtailment what-ifs with expected impact.
Explainability
Feature importance, SHAP-like summaries and confidence scores for every prediction.
APIs & events
Push forecasts & alerts via webhooks, query KPIs and export batches to BI/finance.
Dashboards & reports
Ready views for communities, utilities and finance with exportable, auditable reports.
Architecture
Normalized data → Feature pipelines → Models → Explainability → Exposure. Kubernetes-native, reproducible, observable.
Data & features
Gateway/Platform inputs, weather & calendar joins; lineage and quality checks.
Models & training
AutoML + curated templates; retraining schedules, backtests and drift alerts.
Exposure & governance
APIs, webhooks, reports; RBAC, audit and retention policies for compliance.