Meta Acquires Sundial: AI Data Push

Meta Acquires Sundial in a Strategic AI Data Push

Meta has acquired Sundial, an AI-powered data analytics startup founded by former Meta employees Julie Zhuo and Chandra Narayanan, as it moves to strengthen its internal analytics capabilities for the next phase of its AI strategy. The deal brings Sundial’s team and technology into Meta’s newly formed data analytics organization, where Narayanan will lead analytics tooling and agents work.

What Sundial Does

Sundial built an AI-driven analytics platform designed to help teams ask natural-language questions and turn complex datasets into actionable insights. Its system was aimed at reducing dependence on centralized data teams by making analysis faster and more self-serve for business users.

• Natural-language data analysis
• Self-service analytics workflows
• Tools for cleaning data and generating SQL
• Support for teams that need faster decision-making

Why Meta Bought Sundial

The acquisition fits Meta’s broader effort to improve how it uses data across products, teams, and AI initiatives. By bringing Sundial inside, Meta can combine the startup’s technology with its internal data operations and accelerate work on analytics tooling, agents, and AI-driven insights.

Meta’s new data analytics unit, led by Alex Schultz, is designed to find questions the company has not yet asked and improve the quality of analysis behind product and AI decisions. Sundial now becomes part of that effort instead of continuing as a standalone product.

Who Is Joining Meta

Both co-founders are moving into Meta as part of the deal. Julie Zhuo previously served as Meta’s vice president of product design, while Chandra Narayanan held senior analytics roles at Instagram, Facebook, and Sequoia Capital.

• Julie Zhuo, former Meta product design executive
• Chandra Narayanan, former Instagram and Facebook analytics leader
• Several additional Sundial team members

What This Means for Meta’s AI Strategy

The acquisition signals that Meta sees internal data infrastructure as a competitive advantage in AI. Better analytics can help Meta measure product performance, refine AI systems, and make faster decisions across its platforms.

It also suggests Meta is investing in tools that make data more accessible to employees, which can improve experimentation, reporting, and operational speed inside the company.

Impact on Sundial’s Future

Sundial will stop serving external customers once the deal closes, meaning the startup will no longer operate as an independent product company. Its technology will instead be folded into Meta’s internal systems and workflows.

For Meta, that means immediate access to a product already built for modern analytics use cases. For Sundial’s team, it means a direct role in shaping Meta’s next-generation data tooling.

Conclusion

Meta’s acquisition of Sundial reflects a clear focus on strengthening the data and analytics foundation behind its AI ambitions. By bringing in both the technology and the founders, Meta is betting that smarter internal analytics will help power smarter products, faster decisions, and stronger AI development.