Finance, supply chain, and field data scattered across cloud and on-prem systems—no unified view of profitability. One lakehouse, real-time.
A US-based hydraulic fracturing services company that scaled from startup to multibillion-dollar annual revenue within a few years, collecting roughly 1 GB of data per hour from field equipment while managing petabytes of operational data across North America.
Rapid growth left finance, supply chain, and workforce data siloed across cloud and on-premises systems with no single source of truth for...
“Oracle Fusion Agentic Applications and Autonomous AI Lakehouse give Liberty Energy one trusted platform for data, analytics, and automation, helping our teams make faster decisions to continually provide the best service we can to our customers in terms of safety, efficiency, and quality.”
Energy industry service provider specializing in hydraulic fracturing and power generation.
Assisted Liberty Energy in implementing Oracle Fusion Cloud and Autonomous AI Lakehouse
Enterprise database software and cloud infrastructure services.
Liberty Energy's Operations analytics is part of this use case:
Related implementations across industries and use cases
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Manual exports caused five-hour lags. AI cut fuel stockouts by 20% and audit prep from two weeks to one hour.
Analysts spent 5 days coding reports. Now, business users query millions of records in plain English for instant results.
Manual exports caused five-hour lags. AI cut fuel stockouts by 20% and audit prep from two weeks to one hour.
Fragmented tools slowed operations. A unified platform now connects experts and business users, cutting analysis time by 60%.
Generic energy tips ignored smart meter data. Now, AI analyzes 48 daily readings per customer to write personalized savings advice.
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Energy market research that took weeks now closes same-day. Staff freed from chasing information to make the calls that matter.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Finance, supply chain, and field data scattered across cloud and on-prem systems—no unified view of profitability. One lakehouse, real-time.
A US-based hydraulic fracturing services company that scaled from startup to multibillion-dollar annual revenue within a few years, collecting roughly 1 GB of data per hour from field equipment while managing petabytes of operational data across North America.
Rapid growth left finance, supply chain, and workforce data siloed across cloud and on-premises systems with no single source of truth for...
“Oracle Fusion Agentic Applications and Autonomous AI Lakehouse give Liberty Energy one trusted platform for data, analytics, and automation, helping our teams make faster decisions to continually provide the best service we can to our customers in terms of safety, efficiency, and quality.”
Energy industry service provider specializing in hydraulic fracturing and power generation.
Assisted Liberty Energy in implementing Oracle Fusion Cloud and Autonomous AI Lakehouse
Enterprise database software and cloud infrastructure services.
Liberty Energy's Operations analytics is part of this use case:
Related implementations across industries and use cases
Analyzing metrics for 100,000 projects meant navigating multiple systems. Now, teams instantly extract insights via AI chat or voice.
Manual exports caused five-hour lags. AI cut fuel stockouts by 20% and audit prep from two weeks to one hour.
Analysts spent 5 days coding reports. Now, business users query millions of records in plain English for instant results.
Manual exports caused five-hour lags. AI cut fuel stockouts by 20% and audit prep from two weeks to one hour.
Fragmented tools slowed operations. A unified platform now connects experts and business users, cutting analysis time by 60%.
Generic energy tips ignored smart meter data. Now, AI analyzes 48 daily readings per customer to write personalized savings advice.
350,000 track images reviewed by hand each month, always chasing failures. TrackDefectX now catches defects before they escalate.
Energy market research that took weeks now closes same-day. Staff freed from chasing information to make the calls that matter.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.