Demand and Generation Forecasting
Short-term and day-ahead forecasting for load, wind, solar and hybrid portfolios, with calibrated uncertainty.
Make AI a real operating tool for grid, generation and field work.
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.
Energy AI rarely fails on the model. It fails on the operating environment around it.
We give energy teams AI that operations, engineering and compliance can all trust.
We cover the high-value AI use cases across the energy value chain.
Short-term and day-ahead forecasting for load, wind, solar and hybrid portfolios, with calibrated uncertainty.
Anomaly detection on grid telemetry, substation data, SCADA signals and asset health indicators.
Predictive maintenance for turbines, transformers, compressors, pumps and similar assets, integrated with CMMS and EAM systems.
Field-ready AI assistants for engineers, technicians and dispatchers, with offline-capable workflows.
Price forecasting, scheduling support, risk analytics and market intelligence with audit-ready decision logs.
RAG over standards, manuals, permits and historical incident data, with grounded generation and audit trails.
A long-running team of AI engineers, data engineers and domain specialists embedded in your operations or product team.
Senior AI architects with energy experience who reinforce your in-house team during build or evaluation phases.
Fixed-scope work for a defined use case, for example a forecasting model, an anomaly detector or a field copilot pilot.
Use case selection, ROI framing, regulatory shaping and a phased roadmap aligned with operational priorities.
Load, generation, price and weather-driven forecasting with calibrated uncertainty and integration into operational systems.
Detection models for grid telemetry, SCADA, substation and asset data, integrated with control rooms and CMMS.
Predictive models for rotating equipment, transformers and similar assets, integrated with EAM and maintenance workflows.
LLM-based assistants for field engineers, technicians and dispatchers, with offline-capable workflows.
Price forecasting, scheduling support, risk analytics and market intelligence with audit-ready outputs.
Patterns from our AI engineers that have run through real energy deployments.
Energy AI Evaluation Framework
A practical approach to evaluating AI systems against operational decisions, including human-in-the-loop scoring and safety review.
Industrial AI Operating Pattern
A reference for monitoring, retraining and on-call for AI systems running against grid, generation and asset workloads.
We map the operational workflow, the data, the decision windows and the safety and regulatory shape.
We design the data pipelines, the model strategy and the operational integration points.
We build the system in code, with evaluations tied to operational decisions, not generic metrics.
We pilot in a controlled operational environment with human-in-the-loop, monitoring and feedback.
We move into a production operating model with monitoring, retraining and on-call, and widen the use case across assets or regions.
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.
We cover strategy, architecture, build, deployment and operations for AI for Energy Operations, aligned with your business priorities and operating constraints.
Most engagements reach a working pilot within 4-8 weeks, while larger rollouts run across phased waves over several months.
Yes. We integrate with cloud platforms, CRMs, ERPs, EHR, OT systems, analytics tools and other operational infrastructure depending on the use case.
Yes. We offer milestone-based pricing once scope, KPIs and delivery requirements are agreed.
You retain ownership of all workflows, integrations, prompts, infrastructure, systems and implementation assets.
We implement governance frameworks, observability, access controls, audit trails and compliance-aligned deployment practices.
We tune infrastructure, automate resource management, optimise deployment workflows and report operational cost back to teams and product lines.
Yes. We run managed operations with SRE, observability, on-call and continuous improvement.