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About Contact Us
AI-first engineering

AI Application Development Company for Energy.

AI application development for energy and utilities. Build applications for asset knowledge, maintenance, field operations, and decision support.

Get started

See Logiciel in action.

Tell us what you're building and we'll take it from there.

15+
Years building production software
120+
Engineers across delivery pods
75+
Clients served in North America
3K+
Successful product releases
Why Logiciel

Why Energy AI Applications Need More Than Predictive Outputs.

Why Logiciel · 01

Asset information is spread across maintenance systems, manuals, telemetry, inspection records, and engineering documents.

Why Logiciel · 02

Field teams need relevant information quickly, often with incomplete connectivity or changing operational context.

Why Logiciel · 03

An incorrect interpretation of an asset condition can affect maintenance planning and operational decisions.

Why Logiciel · 04

Sensor signals need validation, time context, and equipment history before they become useful recommendations.

Why Logiciel · 05

Safety-critical actions require established procedures, authorization, and accountable human oversight.

Why Logiciel · 06

Legacy operational technology and modern cloud services can have very different integration and security constraints.

Why Logiciel · 07

Production energy AI needs traceable sources, realistic evaluation, and workflows that respect operational boundaries.

What you get

What You Get From Logiciel AI Application Development for Energy.

We combine AI engineering, data integration, and operational software development to make technical information useful in real workflows.

01

Asset-aware AI assistance

using approved equipment records, maintenance history, manuals, and operational context

02

Connected field and office workflows

bringing information together across maintenance, inspection, planning, and engineering systems

03

Traceable technical guidance

linking summaries and recommendations to available source documents and validated data

04

Safety-conscious execution boundaries

keeping control actions, authorizations, and critical decisions in established procedures and systems

05

Better exception visibility

organizing alerts, missing records, unusual patterns, and follow-up information for review

06

Evaluation against operational scenarios

testing equipment context, stale signals, data gaps, permissions, and failure conditions

07

Maintainable production architecture

designed around existing infrastructure, security controls, monitoring, and changing asset information

Highlights

AI Applications Across Energy and Utility Workflows.

01

Asset Knowledge Assistants

What it meansHelp engineers retrieve approved equipment manuals, service history, procedures, and technical documentation.
02

Maintenance Planning Support

What it meansOrganize work-order context, equipment records, and condition information for planner review.
03

Field Service Knowledge Applications

What it meansGive authorized field teams contextual access to procedures, records, and guided information capture.
04

Inspection Document Processing

What it meansExtract findings, organize inspection evidence, and route exceptions to responsible reviewers.
05

Operations Incident Summaries

What it meansBring together relevant logs, event records, and approved context for incident investigation.
06

Energy Data Interpretation Workspaces

What it meansPresent validated operational trends and model-assisted explanations for analysts and engineers.
07

Utility Customer Service Tools

What it meansSupport service agents with approved outage information, account context, and published procedures.
What we build

AI Application Development Models Built Around Energy Teams.

01

Dedicated Energy AI Engineering Squad

A cross-functional team builds AI applications across asset data, technical workflows, integrations, testing, and deployment.

02

Energy AI Consulting and Team Extension

AI, data, cloud, and application engineers work with your engineering and operations stakeholders.

03

Outcome-Based Energy AI Engagement

A scoped initiative addresses asset search, inspection processing, maintenance support, or another defined operational task.

Under the hood

AI Application Development Services We Deliver for Energy.

01

Energy Workflow and Asset Discovery

We identify equipment, users, operational decisions, source systems, and measurable workflow outcomes.

Included
02

Asset and Operational Data Integration

We connect approved maintenance records, documents, time-series information, and business systems where supported.

Included
03

Technical Knowledge Application Engineering

We build retrieval and summarization workflows grounded in equipment context and available source evidence.

Included
04

Operational AI Interface Design

We create interfaces that distinguish observed facts, model suggestions, missing information, and review actions.

Included
05

Safety and Access Boundary Design

We separate AI assistance from control-system execution and preserve established authorization requirements.

Included
06

Operational AI Testing and Evaluation

We test stale signals, asset mismatches, missing documents, permission boundaries, and representative failure scenarios.

Included
07

Deployment and Performance Monitoring

We monitor integration health, source freshness, latency, usage, and workflow outcomes across supported environments.

Included
Insights

Energy AI Application Insights & Frameworks.

01

Asset Information Opportunity Model

A method for prioritizing workflows by document search effort, data availability, decision impact, and operational value.

Insights
02

Advisory AI vs. Control-System Framework

A way to define where AI can explain or prepare information and where deterministic controls and human authorization remain required.

Insights
03

Operational AI Reliability Model

A framework for evaluating source freshness, equipment context, exception handling, traceability, and system performance.

Insights
How we work

Our AI Application Development Framework for Energy.

01

Asset and Operations Workflow Discovery

We map the task, responsible teams, equipment context, existing procedures, and expected operational value.

02

Data and System Readiness Assessment

We assess maintenance records, technical documents, telemetry access, integration boundaries, and security constraints.

03

AI Application and Control Design

We define retrieval, model tasks, interfaces, source validation, approval boundaries, and evaluation requirements.

04

Build, Integrate, and Validate

We implement the application and test representative assets, data gaps, exceptions, and access controls.

05

Deploy, Observe, and Improve

We monitor information freshness, integration health, user outcomes, and operational feedback before expanding scope.

Selected work

Tailored engineering for your industry.

Zeme · Real EstateCut development costs 50% and launched 3× faster with dedicated dev teams.
Real Estate

Cut development costs 50% and launched 3× faster with dedicated dev teams.

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

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

KW · Real Estate56M+ workflows automated, saving agents 30% time with AI-powered tasks.
Real Estate

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

Resources

Insights for tech leaders.

Whitepaper · PDF

The Model Evaluation Report

Read more
Whitepaper · PDF

The Economics of Model Evaluation

Read more
Whitepaper · PDF

Benchmarking Model Evaluation

Read more
In their words

What our clients say.

Teams that needed to ship fast, and did. Here's what partnering with Logiciel felt like from the inside.

Patrick Fingles

I would highly recommend them to anyone looking to scale quickly or needing support in engineering, product, or QA.

Patrick Fingles
Patrick Fingles
CEO, Leap
Elior Alayev

We don't just call them Logiciel; they're part of the Zeme team. Within the first week they were contributing meaningfully to our codebase.

Elior Alayev
Elior Alayev
Founder & CEO, Zeme
David Buzzelli

The Logiciel team worked tirelessly and built everything we needed, with security and best practices across our entire platform. It allowed us to become #1 in our industry, and we couldn't have done it without them.

David Buzzelli
David Buzzelli
Co-Founder, JobProgress
Questions

Frequently asked questions.

What AI applications can be built for energy and utilities?

Examples include asset knowledge tools, maintenance planning support, inspection document processing, incident summaries, field service assistance, and utility service applications.

Can AI applications connect to existing maintenance systems?

Yes, where suitable interfaces and permissions exist. Integrations may use maintenance records, work orders, equipment metadata, and approved operational services.

Can AI directly control industrial equipment?

Safety-critical control should remain within appropriately engineered and authorized systems. AI assistance can support information gathering and recommendations without receiving unrestricted control authority.

How do you handle inaccurate or stale sensor information?

We assess data freshness, source quality, equipment context, and validation needs, then define how the application should handle missing or conflicting signals.

Can AI help field engineers find technical documentation?

Yes. A knowledge application can retrieve approved manuals, procedures, and service records associated with the relevant asset and user permissions.

Can AI features work in field mobile applications?

Yes. Mobile experiences can support contextual lookup and information capture, with connectivity and synchronization requirements designed around field conditions.

How is AI application quality evaluated for energy workflows?

We test source accuracy, asset association, permission boundaries, incomplete data, exception handling, performance, and completion of defined operational tasks.

Let's build

Turn Energy Data Into Usable Operational Context.

Share the asset, maintenance, or field workflow you want to improve. We’ll help design an AI application that fits your systems and respects operational controls.