SUCCESS CASE

Data Lake and
AI: Operational
efficiency and predictivity for energy generation

We centralized data and applied AI for a multinational energy company. With a Data Lake in a medallion architecture and predictive models, the solution enabled predicting equipment failures, speeding up decision-making, and moving from reactive to predictive management.

Machine Learning
Data Lake
AI

Results

Consolidation of multiple scattered data sources into a single Data Lake

Dashboards optimized for fast visualization and decision-making

Internal corporate AI assistant for secure strategic queries

Equipment maintenance prediction with sending of preventive alerts

Overview

A multinational company in the power generation sector operates under an Energy as a Service model in Latin America, serving industries and cities. With distributed operations and fragmented data, the company needed to eliminate rework in analyses, make strategic decisions faster, and shift from a reactive operational model to a highly efficient predictive approach.

The challenges

Decision-making impaired by data scattered across multiple sources.
Excessive time spent by the team on manual dashboard creation.
Reactive operation, identifying equipment failures with delays.
Lack of unified monitoring and predictive alerts to act before outages occur.

Journey
and solutions

ília built a Data Lake with a medallion architecture and pipelines to standardize and centralize the data. The consumption layer integrates AI-optimized Power BI dashboards. We developed an internal corporate assistant (RAG/OCR) for quick queries of strategic documents by department and implemented Machine Learning models for failure prediction and preventive maintenance.

What did we deliver?

Centralized Data Lake with medallion architecture and data processing pipelines.
Multi-cloud analysis and visualization dashboards integrated with Power BI.
AI corporate assistant with access segregation for internal queries.
Machine Learning models for maintenance prediction with real-time alerts.

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