Rohit Patel has departed Meta after an eight-year tenure to launch Ndoc, an early-stage startup building an artificial intelligence-native workspace designed to challenge dominant platforms like Microsoft Office and Google Workspace. Patel, who previously served as a director at Meta Superintelligence Labs focusing on reinforcement learning and output evaluation, is betting that enterprises are ready to move beyond traditional document formats in favor of unified environments.
Reimagining Enterprise Workflows
Ndoc is structured to consolidate fragmented workflows that typically require users to jump between spreadsheets, slide decks, and external coding tools. Instead of layering chat interfaces onto legacy applications, the new platform merges data analysis, presentation layouts, and underlying code into a single interface. The workspace is divided into three primary sections:
- The Stage tab houses visual deliverables such as slide decks, live dashboards, and functional simulations.
- The Narrative tab contains written analyses, automated citations, and generated figures explaining the data.
- The Model tab stores raw datasets and Python scripts, allowing team members to inspect and verify the logic behind generated outputs.
Patel emphasizes transparency as a core differentiator for the platform. By exposing the underlying Python scripts, users without coding experience can ask the built-in assistant to explain formulas and verify calculations, mitigating the black-box problem common in modern productivity software.
Challenging Tech Giants and Traditional Formats
The startup enters a crowded market where major artificial intelligence labs and technology providers are actively embedding agents into existing office applications. While competitors focus on bringing intelligence to where employees already work, Patel argues that incremental integration misses the opportunity to fundamentally redesign how digital documents function. Ndoc introduces a proprietary file format that exports as a browser-compatible file, which the founder plans to open-source to prevent vendor lock-in.
Operating with a lean team and relying on a mixture of open-source models to keep operational expenses low, the startup has initiated a closed alpha release for selected customers. Patel plans to gather user feedback and validate product engagement before pursuing external venture capital funding, positioning speed of execution as the primary driver for early growth.