Meta AI Director Rohit Patel Exits to Build Ndoc, an AI-Native Rival to Microsoft Office and Google Workspace

After eight years developing AI at Meta, Rohit Patel is leaving the company, TechCrunch has exclusively learned. The former director at Meta Superintelligence Labs has launched Ndoc, a startup he is pitching as an AI-native replacement for the Microsoft Office suite and Google Workspace.

Patel is the latest in a string of high-profile departures from Meta, following the exits of Chief Global Affairs Officer Joel Kaplan, AI researcher Andrew Tulloch, and Head of Product for AI-for-Work Emily Dalton Smith.

A Unified Workspace, Not Another Add-On

Patel designed Ndoc to be more than just another AI tool layered onto an existing workflow. The goal is to replace the fragmented way people work across tools like Excel, Word, PowerPoint, Tableau, Replit, and "ChatGPT copy-paste" with one unified workspace that all colleagues can access—even if they are not signed up for Ndoc.

Ndoc brings three components together in a single layout:

• Stage tab — where presentations of key findings live, such as slide decks, dashboards, simulations, or mini apps.
• Narrative tab — featuring analyses, numbered citations, generated figures, and generally the "why" behind the numbers.
• Model tab — where underlying datasets and Python scripts are housed.

Built for Verifiability

The design reflects Patel's background. During his tenure at Meta, Patel focused on reinforcement learning—a type of machine learning in which AI agents learn to make decisions through trial and error to maximize rewards—and on evaluating whether AI output is trustworthy. Patel believes that if AI is going to build the spreadsheets and slide decks companies use to make decisions, someone should be able to check its work. For instance, users can inspect the Python scripts used to create the documents.

"Even if you don't know any Python, you can ask [the AI chat], 'Hey, what does this script do? Which line has my formula?' And you can verify that formula," Patel said. "There's nothing hidden behind the curtain here."

In practice, users can upload a dataset and ask Ndoc to perform an analysis and write a narrative about the findings. They can also add document-specific context, including audience, tone, and memory. "It maintains a memory across your person, that particular document, your team, and your company," Patel said.

Lower Costs, Higher Appeal

Patel also says Ndoc is built and fine-tuned using a mixture of open-source models. Because the platform was developed from scratch, he says it costs considerably less to run than alternatives built on frontier AI models.

"I thought that's what people would be excited about, but people don't care about that," he said, referring to his early trial users. "What people are excited about is that they love seeing all their end-to-end in one place."

Reinventing the File Itself

Patel's larger ambition is to reinvent the file itself. He says documents can be exported as a single ".ndoc.html" file that can be opened in any browser—a format he plans to open-source so other developers can build apps that work with it without being locked into Ndoc the way so many have been locked into Microsoft or Google for years.

His desire to open-source the project was partly why he left Meta and decided to go it alone. At a big company like Meta, getting everyone to agree on an open-source format would undoubtedly require the input of "hundreds of peopl..."

via TechCrunch AI