EDGE AI FOR ENERGY SYSTEMS

AI-native edge intelligence for renewable energy

EdgeNex unifies industrial edge control, energy forecasting and optimization, and an operations agent so renewable energy sites can sense in real time, reason intelligently and execute reliably.

01

Industrial edge control

02

Multi-protocol integration

03

AI forecasting & diagnostics

04

Offline local autonomy

FIELD INTELLIGENCE

More than connectivity: a complete intelligence loop at the physical site

The edge understands data, deterministic control executes critical actions, and AI continuously forecasts, diagnoses and improves strategy.

01CONNECT

Unify

Connect meters, inverters, PCS/BMS, chargers, environmental sensors and critical loads.

02PREDICT

Forecast

Forecast PV output, demand, charging behavior and SOC to inform site strategy.

03DIAGNOSE

Diagnose

Correlate alarms, logs and signals to explain anomalies and surface root-cause clues.

04OPTIMIZE

Optimize

Refine strategy around demand, tariffs, asset life and site constraints.

EDGE-TO-AI ARCHITECTURE

An explainable, replayable loop from device integration to AI decisions

01

Field devices

PV, storage, charging, meters, HVAC, fire systems, sensors and loads

02

AI edge control

Industrial I/O, protocols, buffering, rules, lightweight inference and fallback

03

Models and data

Forecasting, anomaly detection, root cause, knowledge and constrained optimization

04

Cloud and agent

Project operations, remote service, reporting, collaboration and model iteration

DETERMINISTIC SAFETY

AI forecasts, diagnoses and optimizes. Industrial control executes safely.

AI is never the sole basis for critical protection. Deterministic rules, hardware safeguards, human authorization, fallback and complete logs define the safety boundary.

  • Confirmation for critical commands
  • Offline local autonomy
  • Versioned strategy and rollback
  • Permissions and audit logs
PILOT PROGRAM

Prove AI value on a real project

We prioritize pilots with a real site, device documentation, historical data and clear acceptance criteria.

Start a pilot
  1. 01

    Share the site and device context

  2. 02

    Define data and acceptance criteria

  3. 03

    Integrate, run and review the outcome