AI Anomaly Detection for Energy: Assess & Deploy

Frame Data & AI is a professional services firm specialising in Azure data platform and AI implementations for the energy sector. This consulting offer covers the full engagement lifecycle for oil and gas operators, midstream and gas storage companies, and oilfield services firms moving from reactive maintenance to live, AI-driven anomaly detection on Microsoft Azure.

Why AI Anomaly Detection for Energy Energy operations depend on high-value rotating equipment — compressors, pumps, and wells — running around the clock at critical infrastructure sites. Operational data is typically fragmented across SCADA historians, trading and risk platforms, ERP, and maintenance systems, and maintenance practices remain manual and reactive. Equipment anomalies are caught late or by chance, exposing operators to preventable failures, curtailed deliveries, penalties, and safety risk. AI models trained on an operator's own SCADA time-series history learn the normal operating envelope of each asset class and detect deviations that precede failures — signals invisible to threshold-based SCADA alarms and human review across thousands of sensor streams.

Engagement Structure This professional services engagement is structured in three phases, delivered as a continuous programme or as standalone engagements depending on your readiness.

Phase 1 — Assessment & Data Foundation: Frame evaluates your data landscape and establishes a governed Bronze/Silver/Gold medallion data estate on Azure Data Lake Storage Gen2, unifying SCADA/historian time-series data with enterprise and market data into a single analytical backbone. Phase 2 — Model Development & Historical Validation: Frame trains AI anomaly detection models on your own operational history using Azure Machine Learning and validates early-warning detection against real historical events with your operations SMEs — proving value before production investment. Phase 3 — Live Deployment & Managed Optimisation: Frame establishes streaming ingestion from SCADA historians via Azure IoT Hub, Azure Event Hubs, and Azure Stream Analytics, deploys the validated models against live production assets, and operationalises alerting with contextual anomaly explanations and real-time asset-health dashboards in Power BI — with UAT, documentation, and IT handoff. The design is human-in-the-loop: AI surfaces early warnings and context; your operators decide and act.

Azure Services Deployed Azure Data Lake Storage Gen2, Azure Data Factory, Azure IoT Hub, Azure Event Hubs, Azure Stream Analytics, Azure Machine Learning, Azure Functions, Azure Key Vault, Azure Monitor, and Power BI.

Pricing The listed price is a placeholder: every engagement is custom. Pricing is estimated and scoped per engagement based on factors including asset count and asset classes in scope, data readiness, number of source systems, and which phases are delivered. Contact Frame for a tailored proposal.

Why Frame Frame Data & AI is a Houston-based professional services firm purpose-built for the energy sector, combining deep Azure data platform and AI engineering expertise with real-world energy operations experience. Frame has delivered this solution for energy operators including the largest privately owned independent natural gas storage operator in the United States, taking the client from fragmented data to validated AI in under two months.