How our universal content processing platform Riviera evolved for AI and beyond
Riviera is the Dropbox content processing platform that’s been iteratively improving content transformation in our products for roughly a decade.
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Riviera is the Dropbox content processing platform that’s been iteratively improving content transformation in our products for roughly a decade.
We used DSPy to improve LLM judges and optimize our chat experience, creating an evaluation-driven feedback loop that produced better outputs.
Using an agentic AI system to surface threat models during code review and spot gaps between security requirements and implementation.
How Dropbox is moving from AI tools that assist engineers to agentic systems that can execute scoped tasks, and how we’re building platforms to support those workflows.
Nova lets engineers run multiple coding sessions in parallel and lets internal systems use AI agents as part of automated workflows.
By turning compaction into a layered, adaptive pipeline and strengthening our monitoring and controls, we made Magic Pocket more resilient to workload changes.
Monorepos will continue to grow as products evolve, but growth doesn’t have to mean friction.
We used DSPy to turn prompt engineering for our relevance judge into a measurable, automated optimization loop, improving task performance, cost, and how reliably it works in production.
How we train Dash's search ranking models with a mix of human and LLM-assisted labeling.
Making products like Dropbox Dash accessible to individuals and businesses means tackling new challenges around efficiency and resource use.
From Claude Code to Cursor, we're big adopters of AI coding tools at Dropbox. The early results have been promising, but there are still a lot of open questions about how to work with these tools most effectively and where they can have the most impact. To push this conversation forward, we hoste...