The AI That Connects the Dots. Fuse petabytes of data and deep domain logic to achieve cognitive, field-wide performance.
Autonomous workflows reduce decision time from days to minutes, enabling real-time operational responses
Hybrid ML models continuously optimize production settings while physics-based validation ensures safe operations
Predictive maintenance and automated optimization significantly reduce OPEX while maximizing asset uptime
A multi-agent system that combines data extraction, physics models, machine learning, and autonomous execution
Extracts and validates unstructured data (failure modes, reservoir reports) from documents, PDFs, and scanned images
Runs first-principles models (e.g., Nodal Analysis) to define the physics envelope and validate operational constraints
Generates optimal production settings while running the Failure Predictor safety check to ensure equipment protection
Sends the final, validated prescriptive setting directly to the operational system (SCADA) for autonomous execution
What makes GeoAgent think and act like a lead engineer
Combines physics-informed models with data-driven ML to make predictions that are both accurate and explainable, ensuring trust and transparency
Event-driven architecture that monitors SCADA data, triggers autonomous decision-making, and executes validated actions without human intervention
Detects imminent ESP failures days or weeks in advance using motor current, vibration, temperature, and intake pressure analytics
Continuously recommends optimal VFD frequencies, injection rates, and choke settings that maximize production while protecting equipment
Seamlessly integrates with existing SCADA systems to monitor operations, trigger workflows, and execute autonomous actions in real-time
Every recommendation passes through physics-based safety checks (nodal analysis, material balance) to ensure operational constraints are respected
Real-world applications across E&P operations
Autonomously adjusts injector/producer rates to maximize pattern sweep efficiency and field NPV
Recommends VFD frequencies that maximize net oil production while avoiding pump wear-out
Identifies wells where water shut-off treatments will yield the highest economic benefit
Experience autonomous optimization that thinks and acts like your best engineer
