AI modules for
the wind industry.
Our module library is designed to grow. We combine reusable AI capabilities around a specific operational workflow, then adapt the system to customer data, assets, terminology, business rules and infrastructure.
Different AI capabilities. One operational system.
A deployment can use one capability or combine several. The technical layer can include classical machine learning, deep learning, computer vision, retrieval, LLM reasoning and deterministic logic.
AI Workers & Workflow Agents
Coordinate multi-step operational work: triage cases, collect context, check missing information, prepare follow-ups and route approvals.
Engineering Copilot
Help engineers investigate issues with relevant manuals, historical cases, procedures, alarms and technical context in one place.
Document & Regulatory Intelligence
Extract, classify, compare and validate information from PDFs, reports, certificates, requirements, emails and regulatory documents.
SCADA Intelligence
Analyze multi-sensor turbine behaviour, identify deviations from normal operation and surface anomalies for engineering review.
Predictive Maintenance
Use condition and maintenance history to generate early-warning signals, degradation indicators and maintenance priorities.
Computer Vision & Inspection
Support blade, tower and component inspection by detecting, segmenting and classifying visible defects from image or video data.
Knowledge & RAG Systems
Search manuals, procedures, historical cases and internal technical records with answers grounded in company knowledge.
Performance & Forecasting
Model production patterns, power-curve deviations and operational KPIs using asset history together with contextual inputs such as weather.
Base modules first. Your operation on top.
Fine-tuning can mean very different things depending on the task: retraining a time-series model, calibrating thresholds, learning turbine-specific baselines, adapting a vision model, configuring retrieval on private documents or encoding company rules into deterministic checks.
Connect
Map SCADA, CMS, images, documents, work orders, APIs and the systems your team already uses.
Adapt
Configure or fine-tune the relevant AI capabilities for site-specific behaviour, language and failure modes.
Benchmark
Test on historical or live cases and compare results with known events, engineering judgement or the current workflow.
Integrate
Deliver outputs through an interface, API or existing operational system with permissions and review controls.
Use the model that fits the problem.
Not everything should be an LLM. Time-series tasks may need anomaly detection or regression; vision tasks may need detection or segmentation; business rules may be best kept deterministic. We combine methods when the workflow requires it.
Built around enterprise constraints.
Solutions can be designed for controlled cloud environments, private infrastructure and self-hosted components when security, data access or governance requires it.