Data enablement
Turn fragmented operational data into a trusted backbone. Connect SCADA, sensors, control systems, asset platforms, and engineering tools into a secure, governed data foundation, ready for AI, analytics, digital twins, and automation.
How it works
From fragmented sources to a trusted operational data backbone
Data is collected from existing operational and business systems through secure integration patterns suited to your architecture and cybersecurity requirements, including edge, DMZ, cloud, and hybrid setups.
It is then harmonised into common asset, signal, event, and alarm models, enriched with context, and made available through governed data products, APIs, event streams, dashboards, and analytics environments. Reusable accelerators, protocol adapters, data models, tagging, quality monitoring, and reference architectures, cut implementation time and risk.
Scenarios
Three ways customers realize value
Establishing a trusted data foundation
A renewable operator with data spread across SCADA, asset management, engineering, and cloud platforms gets secure pipelines, harmonised models, and dashboards. Result: a data backbone supporting consistent reporting, faster analysis, and scalable digital development.
Preparing data for AI and advanced analytics
An asset owner wants AI for performance optimisation, fault detection, forecasting, or digital twins, but the underlying data is incomplete and inconsistent. Antire validates availability and quality, structures historical and real-time streams into reusable AI-ready data products.
Scaling data enablement across a portfolio
An operator expanding across sites, markets, or technologies onboards new assets, vendors, and data sources using reusable integration patterns, protocol adapters, semantic models, and governance without rebuilding integrations each time.
Proven in production
Through our Asset Insights Portal, designed to retrieve, filter, and crunch wind turbine data, Ingka has reduced data latency from hours to minutes, and data is automatically unified, thus applicable straight away.
An AI solution that surfaces answers to questions from various data sources for faster and easier knowledge sharing and patient care.
Why now
Without a data backbone, AI and analytics stay stuck at proof-of-concept
Operators are scaling renewable and distributed asset portfolios, increasing both the volume and complexity of operational data that must be managed and used in real time. Regulation such as NIS2 and the AI Act is tightening cybersecurity, data governance, and operational resilience requirements at the same time.
AI and advanced analytics have matured and are becoming central to competitiveness, but their success depends entirely on access to high-quality, structured, trusted data.
Organisations without a robust data backbone risk falling behind in efficiency, reliability, and digital innovation.
Proof of Value sprint
Validate an AI-ready data foundation in 4–8 weeks
Start with one focused data flow such as a secure pipeline from SCADA into analytics, a harmonized performance feed across sites, or an AI-ready data product for predictive maintenance.
Together, we connect the sources, structure the data, set up the governance model, and deliver a working data product your teams can use, validate, and scale.