Indian tycoon puts $30M into Neo’s AI office

Neo’s AI – Bhavin Turakhia is funding his new startup Neo with $30 million of his own money, betting that workplace software built before generative AI can’t just be patched with chatbots. Neo launched internally in April and is designed from the ground up to make AI par

In April, Bhavin Turakhia quietly started using a new workplace platform inside his own companies. By now, the question he’s really betting on is bigger than product—can an enterprise AI office ever carve out real space when the giants are already embedding AI everywhere?

Neo is Turakhia’s answer, backed by a $30 million personal investment. At 46, the Indian serial entrepreneur says he’s not seeing a simple upgrade path from the pre-AI era. Workplace tools built before generative AI, he argues, can’t be “converted” into something new just by adding chatbots.

“If you want to build an iPhone, you can’t take the parts of a Nokia and somehow convert it into an iPhone,” Turakhia told TechCrunch.

That mindset is the backbone of Neo’s pitch: workplace software redesigned from the ground up, with AI woven into the flow of work rather than bolted on as a separate assistant.

Neo is an enterprise work platform that combines project management, documents, and file storage with AI into a single product. Turakhia says the goal is to make AI an active participant in day-to-day work, not something employees consult on the side.

He also points to flexibility as a reason Neo’s approach may hold up as the AI landscape shifts. Neo is built to be model-agnostic, which Turakhia says lets enterprises switch between AI models instead of becoming locked into one provider.

Turakhia’s record suggests he understands how hard these bets can get. Over the past two decades, he has co-founded companies including Directi, Radix, Titan, and Zeta, a banking software firm—often using his own cash before bringing in outside investors. He is doing the same with Neo.

In his view, enterprise AI may be competitive, but it’s not automatically winner-takes-all. He argues that even a small slice of global enterprise AI spending would still be meaningful.

“Even if we end up with 2% to 5% market share, that’s larger than anything I’ve built so far,” he said.

The timing is sharply felt. Enterprise AI has turned into one of the most crowded corners of technology. with Microsoft. Google. and Salesforce embedding AI across their workplace software. At the same time. startups are racing to rewrite the way businesses work with AI—ranging from major AI labs like Anthropic and OpenAI to productivity companies such as Notion and Superhuman.

Neo’s emergence sits inside that surge, but Turakhia is leaning into a different framing: the tools that businesses depend on can’t survive generative AI without being rebuilt around it.

He also says Neo isn’t alone. Investor Chamath Palihapitiya initially launched enterprise AI coding venture 8090 using his own capital before raising a $135 million funding round this week.

For now, Turakhia is still moving fast and small. Neo began as an internal platform in April. and for the past few months it has been used across Turakhia’s companies. including Zeta. The company plans to roll it out to mid-sized businesses in the coming months. starting with knowledge workers at technology. consulting. and professional services firms.

The company’s ramp-up is tied to how quickly Turakhia believes generative AI can speed development. He says Neo’s initial platform was built in three months. with AI extensively used during development—work he estimates would have taken more than a year with a much larger engineering team without generative AI.

Bengaluru is the base, and Neo is still lean. The startup currently employs about 45 people, including 18 engineers. Turakhia told TechCrunch the company expects to grow to around 100 employees by the end of the year, with most new hires focused on AI and software engineering.

That’s the human stakes inside the pitch: Turakhia isn’t just launching another workplace app. He’s putting his own money behind a belief that the center of enterprise software may need to be rebuilt, not re-skinned—before the market decides what “AI office” even means.

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