Logiciel builds AI systems for energy operators, utilities, renewables and oil and gas companies. Demand and generation forecasting, grid anomaly detection, asset performance, field operations copilots and trading analytics, built for production.

Book an Intro Call Common Questions

6 reasons

Why AI stalls in energy operations

6 outcomes

What you get working with Logiciel

Why Logiciel

Why AI Stalls in Energy Operations.

Why Logiciel · 01

OT and IT systems use different identifiers for the same asset.

Why Logiciel · 02

Sensor data is dirty, with gaps, drift and unit mismatches.

Why Logiciel · 03

Operational decisions cannot wait for an analyst to interpret a dashboard.

Why Logiciel · 04

Regulatory and safety reviews arrive late and reshape the architecture.

Why Logiciel · 05

Field teams need AI that works on tablets, in poor connectivity and under time pressure.

Why Logiciel · 06

Trading and market teams need AI that ties cleanly into existing risk and audit workflows.

What you get

What You Get When You Work With Logiciel on Energy AI.

A clear use case framing, agreed with the people who will operate the system.

Pipelines that handle the realities of sensor data, OT-to-IT integration and historian systems.

Models built around operational decision windows, not generic accuracy scores.

Field-ready interfaces for engineers, technicians and dispatchers.

Audit, safety and risk controls aligned with NERC CIP, ISO 27001 and internal HSE requirements.

A production operating model with monitoring, retraining and on-call.

What we build

Energy AI Solutions Built for Production.

Demand and Generation Forecasting

What it meansShort-term and day-ahead forecasting for load, wind, solar and hybrid portfolios, with calibrated uncertainty.

Grid and Asset Anomaly Detection

What it meansAnomaly detection on grid telemetry, substation data, SCADA signals and asset health indicators.

Asset Performance and Predictive Maintenance

What it meansPredictive maintenance for turbines, transformers, compressors, pumps and similar assets, integrated with CMMS and EAM systems.

Field Operations Copilots

What it meansField-ready AI assistants for engineers, technicians and dispatchers, with offline-capable workflows.

Trading, Market and Renewables Analytics

What it meansPrice forecasting, scheduling support, risk analytics and market intelligence with audit-ready decision logs.

Document and Knowledge AI

What it meansRAG over standards, manuals, permits and historical incident data, with grounded generation and audit trails.

Engagement

Engagement Models Designed for AI for Energy Operations Delivery.

Dedicated Energy AI Squad

A long-running team of AI engineers, data engineers and domain specialists embedded in your operations or product team.

↳ Engagement

AI Advisory and Staff Augmentation

Senior AI architects with energy experience who reinforce your in-house team during build or evaluation phases.

↳ Engagement

Outcome-Based Energy AI Use Cases

Fixed-scope work for a defined use case, for example a forecasting model, an anomaly detector or a field copilot pilot.

↳ Engagement

Under the hood

Energy AI Services We Deliver.

Energy AI Strategy and Roadmap

Use case selection, ROI framing, regulatory shaping and a phased roadmap aligned with operational priorities.

Included

Forecasting Models for Energy

Load, generation, price and weather-driven forecasting with calibrated uncertainty and integration into operational systems.

Included

Anomaly Detection for Grid and Assets

Detection models for grid telemetry, SCADA, substation and asset data, integrated with control rooms and CMMS.

Included

Predictive Maintenance and Asset Performance

Predictive models for rotating equipment, transformers and similar assets, integrated with EAM and maintenance workflows.

Included

Field Operations Copilots

LLM-based assistants for field engineers, technicians and dispatchers, with offline-capable workflows.

Included

Trading and Market Analytics

Price forecasting, scheduling support, risk analytics and market intelligence with audit-ready outputs.

Included

Insights

AI for Energy Operations Insights & Frameworks.

Patterns from our AI engineers that have run through real energy deployments.

Insights

Energy AI Evaluation Framework

A practical approach to evaluating AI systems against operational decisions, including human-in-the-loop scoring and safety review.

Insights

Industrial AI Operating Pattern

A reference for monitoring, retraining and on-call for AI systems running against grid, generation and asset workloads.

Insights

How we work

Our AI for Energy Operations Framework.

Use Case Discovery and Operational Framing

We map the operational workflow, the data, the decision windows and the safety and regulatory shape.

Data and Architecture Plan

We design the data pipelines, the model strategy and the operational integration points.

Build and Evaluate

We build the system in code, with evaluations tied to operational decisions, not generic metrics.

Pilot in a Real Operational Setting

We pilot in a controlled operational environment with human-in-the-loop, monitoring and feedback.

Scale and Operate

We move into a production operating model with monitoring, retraining and on-call, and widen the use case across assets or regions.

Resources

Insights for tech leaders.

Whitepaper · PDF

How an Energy Retailer Used Agents to Automate 40% of Customer Ops

Whitepaper · PDF

How an Energy Utility Built Grid-Trustable AI for Anomaly Detection

Whitepaper · PDF

How an Energy Company Stopped Paying for Silent Data Quality Failures

Selected work

Selected work.

Leap · Construction Scaled to 7-figure ARR with AI-augmented software teams.

Construction

Scaled to 7-figure ARR with AI-augmented software teams.

KW · Real Estate 56M+ workflows automated, saving agents 30% time with AI-powered tasks.

Real Estate

56M+ workflows automated, saving agents 30% time with AI-powered tasks.

Questions

Frequently asked questions.

What does AI for Energy Operations include?

We cover strategy, architecture, build, deployment and operations for AI for Energy Operations, aligned with your business priorities and operating constraints.

How long does AI for Energy Operations typically take?

Most engagements reach a working pilot within 4-8 weeks, while larger rollouts run across phased waves over several months.

Can Logiciel integrate AI for Energy Operations with our existing systems?

Yes. We integrate with cloud platforms, CRMs, ERPs, EHR, OT systems, analytics tools and other operational infrastructure depending on the use case.

Do you offer fixed-cost engagements for AI for Energy Operations?

Yes. We offer milestone-based pricing once scope, KPIs and delivery requirements are agreed.

Who owns the deliverables from a AI for Energy Operations engagement?

You retain ownership of all workflows, integrations, prompts, infrastructure, systems and implementation assets.

How do you handle governance and compliance for AI for Energy Operations?

We implement governance frameworks, observability, access controls, audit trails and compliance-aligned deployment practices.

How do you optimize cost for AI for Energy Operations?

We tune infrastructure, automate resource management, optimise deployment workflows and report operational cost back to teams and product lines.

Do you support ongoing operations after launch for AI for Energy Operations?

Yes. We run managed operations with SRE, observability, on-call and continuous improvement.

Let's build

Accelerate AI for Energy Operations.

Ready to move AI for Energy Operations from pilot into production? Partner with Logiciel to design, build and operate AI for Energy Operations that engineering, security and business teams can all defend.

Plan your energy AI rollout

AI for Energy Operations.

See Logiciel in action.

Why AI Stalls in Energy Operations.

OT and IT systems use different identifiers for the same asset.

Sensor data is dirty, with gaps, drift and unit mismatches.

Operational decisions cannot wait for an analyst to interpret a dashboard.

Regulatory and safety reviews arrive late and reshape the architecture.

Field teams need AI that works on tablets, in poor connectivity and under time pressure.

Trading and market teams need AI that ties cleanly into existing risk and audit workflows.

What You Get When You Work With Logiciel on Energy AI.

Energy AI Solutions Built for Production.

Demand and Generation Forecasting

Grid and Asset Anomaly Detection

Asset Performance and Predictive Maintenance

Field Operations Copilots

Trading, Market and Renewables Analytics

Document and Knowledge AI

Engagement Models Designed for AI for Energy Operations Delivery.

Dedicated Energy AI Squad

AI Advisory and Staff Augmentation

Outcome-Based Energy AI Use Cases

Energy AI Services We Deliver.

Energy AI Strategy and Roadmap

Forecasting Models for Energy

Anomaly Detection for Grid and Assets

Predictive Maintenance and Asset Performance

Field Operations Copilots

Trading and Market Analytics

AI for Energy Operations Insights & Frameworks.

Patterns from our AI engineers that have run through real energy deployments.

Energy AI Evaluation Framework

Industrial AI Operating Pattern

Our AI for Energy Operations Framework.

Use Case Discovery and Operational Framing

Data and Architecture Plan

Build and Evaluate

Pilot in a Real Operational Setting

Scale and Operate

Insights for tech leaders.

How an Energy Retailer Used Agents to Automate 40% of Customer Ops

How an Energy Utility Built Grid-Trustable AI for Anomaly Detection

How an Energy Company Stopped Paying for Silent Data Quality Failures

Selected work.

Scaled to 7-figure ARR with AI-augmented software teams.

56M+ workflows automated, saving agents 30% time with AI-powered tasks.

Frequently asked questions.

Accelerate AI for Energy Operations.