How OpenAI accelerated growth with Sundial
Overview
In mid-2023, the exceptional product momentum of ChatGPT underscored the need for a more scalable and comprehensive analytics approach at OpenAI. A small data team juggled ad‑hoc SQL, spreadsheets, and legacy tools to answer basic questions, making it hard for leadership to align on a single source of truth. By adopting Sundial, OpenAI reclaimed months of data engineering and data science bandwidth, democratized data access, and kept decision‑making as fast as product innovation.
Accelerating Growth with Unified Analytics
As OpenAI’s user base surged at an historic pace, insight requests from product, marketing, sales, legal, operations quickly outpaced the capacity of the small analytics team, making it difficult to support data-driven decisions at the speed the company was growing.
After evaluating multiple enterprise analytics solutions, OpenAI chose Sundial for its unique blend of depth, speed, and intuitive simplicity. The impact dramatically accelerating decision-making across the organization:
Sundial's pre-built growth accounting templates provided visibility into daily new, retained, and churned users instantaneously. Overnight, decision makers had access to the data and insights they needed. They no longer had to wait for the small data team to build out custom dashboards or publish ad-hoc analyses.
"We went from raw logging to comprehensive data visibility virtually overnight," explains David Sasaki, VP of Analytics and Insights at OpenAI. "Sundial automated complex data engineering work that would have taken our small team months to build internally."
From Reactive to Responsive
As the ChatGPT audience grew from millions to hundreds of millions, Sundial scaled seamlessly, continuing to return most queries in under a second. Yet the real breakthrough lay in its automated diagnostic analytics.
Before Sundial, a sudden drop in conversion rates meant:
Today, Sundial performs the same investigation automatically. Within seconds it surfaces whether the decline is tied to a particular country, platform, user segment, or even a specific input action—turning what was once days of detective work into an instant, pinpoint answer.
This dramatic compression of the “observation-to-action” window has reshaped how OpenAI interacts with its metrics. Teams can now detect, diagnose, and resolve issues fast enough to prevent them from denting KPIs.
The ease of access led to widespread, organic adoption at OpenAI—by data scientists, engineers, marketers, and executives alike. With metrics findable and filterable in seconds, not hours, and accessible to anyone in the company, data-informed decision-making quickly became the default.
Michael Musson, a data engineer says: “The product team had Sundial first, but it soon spread to other teams across the company.”
The Sundial Difference
What set Sundial apart wasn’t just what it enabled, but the experience of using it. In a world of complex analytics tools that demand specialized expertise, Sundial stood out by making powerful analysis accessible to everyone.
Three core advantages set Sundial apart from alternative solutions:
Valuable templates: Pre-packaged templates for analyzing growth, monetization, and engagement provide immediate value without lengthy implementation.
Accessible and performant self-serve: Sundial speaks the language of businesses and metrics, allowing it to be used by hundreds of people across OpenAI, while its cloud-native architecture delivers answers in seconds rather than minutes, maintaining performance even as OpenAI's data volume grew exponentially.
Insights out of the box: Automated diagnostic tools—including AI-powered anomaly detection and interactive visualization—transform raw data into actionable intelligence, elevating analytics from what happened to why it happened.
The business impact extended beyond improved analytics:
“Sundial is a small but exceptionally capable team iterating with uncommon speed, continually shipping innovations that show they intuitively “get” the problems modern product and business leaders face,“ says Khatereh Khodavirdi, a data scientist at OpenAI. She added “The product is so great that I could generate valuable insights on my first week itself.”
Speed at Scale
For startups and growth-stage companies evaluating analytics solutions, the OpenAI approach offers a compelling model for scaling analytics. When growth takes off, having fast, reliable visibility into key metrics isn’t just helpful—it’s a competitive edge.
By eliminating the engineering burden of building and maintaining complex data pipelines, Sundial enabled OpenAI to focus on its core mission—advancing AI capabilities—while maintaining the data-driven decision making essential for navigating hyper-growth.
In the end, the most valuable metric might be the simplest: how quickly can your team access the insights they need? For OpenAI, Sundial ensured the answer was always "fast enough to keep up."
