NorthGravity Webinar on LLMs and Agentic AI in Commodity Trading

Applications of LLMs and Agentic AI for Commodity Trading and Fundamental Energy Data

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Commodity trading depends on fast decisions made from fragmented, often unstructured data. Fundamental information comes from many sources, reports, emails, operational updates, and market intelligence, and turning it into something reliable remains a major operational challenge.

On March 27, NorthGravity will host a webinar focused on the practical use of Large Language Models (LLMs) and agentic AI in commodity trading and energy data workflows. The session will explore how AI supports the normalization, structuring, and operational use of fundamental data in real production environments.

Rather than focusing on theory, the webinar is structured around real-world production workflows, including:

• parsing and structuring large volumes of unstructured historical and email-based data,
• mapping and normalizing refinery and operational datasets across inconsistent naming conventions and units,
• enriching data with contextual market news and credibility assessment of sources,
• applying AI-assisted validation and backtesting within structured commodity datasets,
• moving AI initiatives from pilot projects into scalable production systems.

A central theme of the session is the importance of data fundamentals. AI can only deliver value when the underlying data is consistent, trusted, and comparable. The discussion will also address practical considerations such as hallucination risk, QA verification layers, orchestration, and security when deploying AI in trading environments.

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Interested in joining the webinar?

Registration is available via Microsoft Teams.