Rohit Patel, the director at Meta Superintelligence Labs, has left the company after eight years to launch Ndoc, a startup aiming to replace Microsoft Office and Google Workspace.
This departure follows a series of exits from Meta, including Chief Global Affairs Officer Joel Kaplan, AI researcher Andrew Tulloch, and Head of Product for AI-for-Work Emily Dalton Smith.
Ndoc is designed to consolidate fragmented tools like Excel, Word, PowerPoint, Tableau, Replit, and various AI chat interfaces into a single workspace. Colleagues can access this environment even if they are not signed up for the platform.
The interface combines three distinct sections. The Stage tab hosts presentations, dashboards, simulations, and mini apps. The Narrative tab displays analyses, numbered citations, generated figures, and the reasoning behind data points. The Model tab stores underlying datasets and Python scripts.
Patel’s background in reinforcement learning and trust evaluation shaped this approach. He argues that if AI generates the documents companies rely on for decisions, the work must be verifiable. Users can inspect the Python scripts used to create files.
“Even if you don’t know any Python, you can ask [the AI chat] to explain, ‘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.”
Users upload a dataset and request an analysis. Ndoc then writes a narrative about the findings. The system retains context regarding the audience, tone, and memory across individual documents, teams, and the wider company.
The platform runs on a mixture of open-source models. Because it was built from scratch rather than relying on frontier AI infrastructure, Patel states the cost to run the system is considerably lower.
“I thought that’s what people would be excited about, but people don’t care about that,” he said regarding early trial users. “What people are excited about is that they love seeing all their end-to-end in one place.”
Patel intends to reinvent the file format itself. Documents can be exported as a single “.ndoc.html” file openable in any browser. He plans to open source this format so developers can build compatible applications without being locked into Ndoc or competing proprietary suites.
This desire to open source the project influenced his decision to leave Meta and work alone. At a large organisation, agreeing on an open-source format would require input from hundreds of people regarding how the structure should look.
Patel wanted to move quickly. “Humans can only move at human pace, whereas…I can move at the pace of what AI can do.”
Attempting to become the central platform for enterprise work is a significant risk for a founder with a team of three and no funding, particularly when other AI labs are targeting the same space.
OpenAI, Anthropic, Meta, SpaceXAI, and Google have all released enterprise AI tools connecting to Google Workspace, Microsoft 365, and other workplace apps. Last month, OpenAI launched Space, a shared workspace inside ChatGPT that competes directly with these established tools.
Patel acknowledges that Space could be a threat but believes the major labs have the wrong idea.
“Companies are basically attaching AI to spreadsheets and it fills your cells for you,” he said. “It just sort of kills my soul. This is like if you just figured out electricity, and then you decided the best use case is to put lights on my bulls that till my soil. No. Get a tractor.”
There is a reason the AI labs have tried to bring their models to existing work environments. Changing habits and replacing entire workflows is difficult. Patel understands this, which is why he built connectors allowing customers to import existing data from tools they already use.
“My bar was that I’m not going to release anything I don’t love using,” he said. “I have very optimized AI workflows for everything I do. If I start using this tool, and I keep going back to my workflows, I haven’t built a good enough tool…I have a graveyard of tools that did not meet that bar.”
Patel applies a similar standard to gaining customer traction before seeking funding. “I didn’t want to take money until I had some proof that people love the product,” he said.
As of Tuesday, Ndoc is running an enterprise pilot and opening an alpha version to a limited number of customers on the wait list. Registration is free, but customers will pay for usage and tokens. A beta version is expected in the coming weeks, with a full launch planned for next year.
For Patel, speed is more important than having a perfect product initially.
“Execution is extremely cheap…so go execute on a suboptimal plan and worry about it later,” he said. “By the time you make the best plan, the execution will be done by somebody else.”
What it means
Patel’s strategy contrasts with the current industry trend of layering AI onto existing software. While competitors integrate models into spreadsheets or document editors, Ndoc aims to replace those tools entirely. The ability to export to a universal HTML format and the lower cost of running open-source models offer a potential alternative for enterprises tired of vendor lock-in, though the startup faces a steep climb against established giants.
