Integrate end-to-end AI workflows with domain-ready algorithms, enabling faster deployment of intelligent solutions in exploration and production.
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Integrate end-to-end AI workflows with domain-ready algorithms, enabling faster deployment of intelligent solutions in exploration and production.
JuraML is a universal machine learning service, covering preprocessing, feature engineering, model building, evaluation, management, and deployment. With built-in algorithms for clustering, regression, time series, and more, it supports scenarios like log interpretation, reservoir prediction, drilling warnings, and ESP diagnostics. Integrated with JuraData, it simplifies data sharing. Models built in JuraML can be managed in JuraComponents or converted into JuraAgent operators, fueling intelligent applications.
Industry users face lengthy, high-threshold workflows involving fragmented steps from preprocessing to deployment.
General ML tools lack built-in algorithms for key oil and gas scenarios like log interpretation, reservoir prediction, and drilling warnings.
Separate systems for data, features, and models result in inefficient flow and low reusability.
Turning models into production applications (e.g., warning or diagnostic systems) requires heavy engineering efforts.
Complete lifecycle support from data prep to deployment, reducing integration complexity and collaboration cost.
Built-in algorithms for oil and gas scenarios like log interpretation, reservoir prediction, and drilling diagnostics, enabling out-of-the-box use.
Package trained models into reusable operators for quick integration into business systems, lowering engineering barriers.
Plug-and-play architecture that supports both standard workflows and custom extensions, balancing usability and flexibility.
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