Use Cases
Real-world applications solving critical operational challenges.

Production Analysis
Engineers spend hours manually gathering and cross-referencing production data from multiple sources.
Aquiom agents automatically aggregate, analyze, and contextualize production data from all connected sources.
85% reduction in analysis time. Faster identification of production anomalies and optimization opportunities.

Deviation Detection
Operational deviations go unnoticed until they cause significant production losses or equipment damage.
AI agents continuously monitor operational parameters, detecting deviations and alerting teams with contextualized explanations.
Early warning system reduces unplanned downtime by 40% and prevents cascading equipment failures.

Well Behavior Analysis
Understanding well behavior requires correlating data across multiple disciplines and decades of experience.
Specialized reservoir and production agents analyze well behavior patterns, providing insights that combine historical data with real-time performance.
10x faster access to well insights. Junior engineers can access senior-level analysis capabilities.

Consumption Queries
Answering questions about historical consumption patterns requires manual database queries and expert interpretation.
Natural language interface allows anyone to query consumption data with automatic contextualization and visualization.
Democratized data access. Non-technical stakeholders can self-serve analytical queries.

Technical Support
Technical support relies on senior engineers who are scarce and often unavailable in the field.
AI agents provide 24/7 technical support with access to the full knowledge base, manuals, and historical case data.
60% faster issue resolution. Reduced dependency on senior specialists for routine technical questions.

Engineering Assistance
Engineering calculations and analyses require specialized software and deep domain expertise.
Aquiom agents assist with engineering calculations, providing step-by-step analysis with full methodology transparency.
Accelerated engineering workflows. Consistent methodology application across teams.