The spread of agentic AI in energy trading

 

 

Artificial intelligence and language learning models are driving efficiencies across a multitude of workflow processes in commodities. 

One area particularly suited to this new AI approach is the automation of invoicing processes, a notoriously time-consuming and error-prone activity for most natural gas firms. NatGasHub.com’s newly launched invoice automation service – which covers more than 300 pipelines –  uses AI agents to extract invoices from the many pipelines firms do business with, standardises them and carries out reconciliation. Jay Bhatty, CEO and founder of NatGasHub.com, offers an example of a trading shop that has cut the time spent processing invoices from 18–20 days a month down to just one day a month with agentic AI. 

Bhatty will be attending Energy Risk USA on May 7 as a panellist on a session entitled AI at work: practical use cases across the energy value chain.

Key discussion points:

00.50 – Why did you create NatGasHub.com, and what does the firm do? 

1.50 – Is AI always the answer? What’s the sweet spot for applying AI to commodities workflow processes? 

3.26 – What sort of areas are ripe for AI agents, and how is NatGasHub using them? 

4.55 – How many pipelines are covered by NatGasHub.com’s AI-powered invoicing service?

5.24 – How does this service impact the day-to-day role of natural gas settlement? 

6.41 – Does the software have decision-making capability? 

7.38 – If a firm decides to allow the agents to make decisions, how would that process be rolled out?

8.35 – Do firms need to hand their data over? How does security work? 

9.48 – How many hours might be saved using AI on invoice processes?

11.35 – What inspired you to write NatGasMillions?

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