i2k AI Platform & SPE’s EnRG-LLM Model
The EnRG-LLM™ model, a domain-specific LLM for oil and gas powered by the i2k AI Platform, is designed to help engineers, geoscientists, and executives quickly access the knowledge already within their organizations in seconds.
Built specifically for energy industry workflows, the EnRG-LLM model is a large language model fine-tuned with peer-reviewed papers and technical journals from the Society of Petroleum Engineers (SPE), helping teams reduce manual research effort and make more confident operational decisions.
The EnRG-LLM model was selected as a winner of the OTC 2026 Spotlight on New Technology Award, which highlights technologies with strong potential to advance offshore energy development.
Recognized by OTC’s Spotlight on New Technology Program
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Trained on info from 100,000+ SPE papers and books, delivering trusted GenAI
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Domain-specific LLM for oil and gas taxonomies that structure complex technical information
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Retrieval-augmented generation (RAG) that grounds AI answers in trusted engineering sources
Your Next Breakthrough
Might Already Be in Your Data
Oil and gas organizations generate petabytes of information across research papers, engineering reports, well files, and seismic studies. Much of this expertise resides in disconnected repositories, making it difficult for teams to locate when critical decisions need to be made.
The EnRG-LLM model and the i2K AI Platform work together to organize and connect this content using domain-tuned AI, allowing IOCs, NOCs, and service companies to securely unlock the value of decades of technical knowledge without copying or restructuring their data.
- Reduce manual research effort by up to 90 percent
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Enable engineers and analysts to make faster, more confident decisions
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Embed trusted GenAI directly into drilling, completions, production, and subsurface workflows
