How OpenAI Uses an Internal Tool to Help Teams Extract Insights Quickly

The millions of customer support tickets generated every year contain important signals, but analyzing them required specialized work from data scientists and a long time. This limited the ability to immediately resolve teams' questions.

To address this, OpenAI built a Research Assistant that combines a dashboard with a conversational interface. This tool shows patterns through existing Classifiers and charts, while also leveraging GPT-5 to summarize raw data and generate flexible reports in natural language.

Through this system, product teams are achieving the following concrete results:

• After the GPT-5 launch: Reduced feedback theme analysis time from weeks to days
• Enterprise connector rollout: Quickly discovered bugs in the onboarding process, helping engineers adjust priorities
• Image generation feature: Identified marketing use cases and rendering delay issues simultaneously, feeding them into the roadmap

This tool doesn't replace data scientists—instead, it helps them focus on more valuable work like automation and tool building instead of simple analysis. As a result, OpenAI is building a scalable customer UX research environment that immediately reflects the customer's voice in products, policies, and practices.