OpenAI has built an in-house AI data agent to help employees get faster, more accurate answers from the company’s large data platform. The tool is internal only and is tailored to OpenAI’s data, permissions, and workflows, but it uses the same building blocks offered to developers, including Codex, GPT-5 models, the Evals API, and the Embeddings API.
The agent lets teams across Engineering, Data Science, Go-To-Market, Finance,e and Research ask complex questions in plain language and receive analysis in minutes. It can help track business health or evaluate product launches by exploring data, writing and running SQL, and turning results into clear explanations and reports. It is available in Slack, a web app, IDEs, the Codex CLI and OpenAI’s internal ChatGPT.
Rather than follow a fixed script, the agent checks its own work. If a query returns strange or empty results, it investigates, adjusts joins or filters, and tries again while keeping full context. Over time, it learns from each interaction and uses memory to avoid repeating the same mistakes.
To stay accurate, the system is grounded in several layers of context. It uses table metadata such as column names and types, records of how tables are linked, and expert-written notes about tables. Codex adds code-level insights that describe how data is produced and how fresh it is. The agent also pulls in company knowledge from Slack, Google Docs, and Notion, and stores important corrections and rules in global and personal memory. When needed, it runs live checks against the data warehouse and other data tools.
The agent is designed to act like a teammate. It supports follow-up questions, can change direction mid-task, and asks for clarification when instructions are vague. It also offers reusable workflows for repeated jobs such as weekly reports or table checks.
OpenAI tracks the agent’s quality using its Evals API and carefully chosen question sets paired with “golden” SQL queries. Generated SQL and outputs are compared to expected results to catch issues early. The agent inherits OpenAI’s security model, only accessing data that users are already allowed to see, and it shows its reasoning and query steps so people can verify answers. OpenAI plans to keep improving the agent’s reliability and integration into everyday work.
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