How our universal content processing platform Riviera evolved for AI and beyond

Every day, Dropbox products transform enormous amounts of content behind the scenes. Open a PowerPoint deck on your phone in Dropbox, and it’s rendered into a crisp preview you can quickly browse. Finalize an agreement in Sign, and it's flattened into a PDF. Upload a video to Replay—our video review and approval tool—and it's transcoded into a lightweight version that streams instantly. These experiences span different products, but they're all powered by the same underlying system.

That system is Riviera, our content processing platform that’s been iteratively improving content transformation in our products for roughly a decade. Whenever a file needs to be prepared for another application, Riviera does that heavy lifting in the background while operating at a massive scale. (For example, Riviera transforms vast amounts of massive media into streamable content, each day producing output equivalent to 8 years of video). Initially, Riviera started as an internal service for generating file previews, but over time, it evolved into a shared platform used across Dropbox by product teams like Search, Replay, Sign, and Dash. We are now making these capabilities available to our developer ecosystem and design partners through API and Model Context Protocol tools.

As Dropbox built AI-powered products like Dash, the need for reliable, reusable content transformation only grew. Before an AI model can answer questions about a document or summarize a report, that content has to be extracted, converted, and prepared in a consistent way—a challenge many developers now face as they build AI applications of their own. Whether you're building a content management system, automating document workflows, indexing files for search, or preparing documents for AI applications, you can now use our API to build on the same infrastructure that powers Dropbox products.

In this story, we’ll cover how Riviera grew from a preview service into a shared platform, the architectural decisions that made that possible, and why we've opened those capabilities to engineers outside of our organization.