How energy companies use Amazon Quick
AI assistant that energy customers can configure across their data sources and workflows. Ask questions in natural language, surface information across systems, and help teams analyze and act faster.
Quick prompts you can use
Use cases for Energy
Production — produce more from what you already have
Which wells are underperforming, and why? Once your production data is connected, engineers can use Quick to help benchmark every well against its optimal envelope, investigate the root cause, quantify the upside in barrels, and identify the highest-value action. Engineers decide, not search.
Reliability — identify potential failures before they cost you millions
Unplanned downtime on critical assets can mean millions in loss. Connected to your equipment data, teams can use Quick to help monitor health data, identify degradation patterns, estimate remaining useful life, and support intervention planning. Your team shifts from reactive to condition-based decisions.
Planning — make high-stakes decisions in hours, not weeks
Market shifts, tight deadlines, or closing capacity windows - all demand fast answers across multiple disciplines. With your systems connected, teams can use Quick to help coordinate workflows end-to-end, access their engineering models, and surface cited information in one conversation, not weeks.
Insights — one conversation across every system and every discipline
Energy companies run on fragmented data across siloed systems. With your existing systems connected, anyone on the team can use Quick to ask questions in plain language. No toggling between tools, no tickets, no waiting on someone else’s report. One person’s insight becomes the whole team’s advantage.
Compliance — meet regulatory deadlines without the manual assembly
Regulatory reporting requires pulling data from many systems. Once your source systems are connected, teams can use Quick to help assemble data from connected sources, reduce the manual extraction that slows reporting workflows, and maintain traceability to the origin.
Safety — make historical safety data searchable
Relevant near-misses and hazards should not stay buried in databases nobody searches. Connected to your incident records, teams can use Quick to help search historical incident records and surface relevant information, so they can incorporate it into their existing safety processes.
Featured Customer Story - TGS
At TGS, Scout, built on Amazon Quick, shows how AI can turn fragmented operational knowledge into trusted, source-backed guidance for our technical teams. We are giving our Imaging users a 24/7 support experience today, while building toward a more proactive agentic model that can support earlier issue detection, recommended remediation, and deeper workflow integration over time.
Jérôme Cousin, Vice President Enterprise IT - TGS
