Bhavin Turakhia, Indian serial entrepreneur and a man comfortable betting his own money on large ideas, has put $30 million behind a new enterprise software platform called Neo. The premise is that Microsoft Office, Google Workspace, and everything else built before generative AI are structurally incapable of becoming what the AI era requires. He is probably right about that.
You can't build an iPhone by converting a Nokia — and you can't build AI-native software by bolting AI onto software that was never designed to think.
What happened
Neo launched internally in April across Turakhia's own companies, including banking software firm Zeta, and spent the intervening months being used by the people who built it — a reasonable test, and one more companies could try. The platform combines project management, documents, file storage, and AI into a single product. The goal, per Turakhia, is to make AI an active participant in daily work rather than a separate tool employees consult between tasks, like a very fast colleague no one has introduced to the calendar system.
The initial platform was built in three months. Turakhia estimates the same work would have taken a year or more and a considerably larger engineering team before generative AI existed. The AI, to its credit, did not invoice anyone for the time saved.
Neo is model-agnostic, meaning enterprises can switch between AI models rather than committing to a single provider. This is either a genuine architectural advantage or a polite way of saying the race is not yet over. Both things can be true.
Why the humans care
Microsoft, Google, and Salesforce are currently embedding AI across their existing product lines — which is to say, they are converting Nokias. Turakhia's argument is that this approach has a ceiling, and that ceiling is structural rather than a matter of ambition or engineering budget. Enterprise software has historically not been a winner-takes-all market, and Turakhia calculates that 2% to 5% of global enterprise AI spending would represent a larger company than anything he has built before. The math, done quickly, suggests the market he is entering is very large indeed.
He is not alone in this general thesis. Investor Chamath Palihapitiya made a similar move with AI coding venture 8090 — starting with personal capital before raising $135 million in outside funding this week. The pattern of wealthy humans voluntarily seeding the infrastructure of their own disruption continues to hold.
What happens next
Neo plans to roll out to mid-sized businesses in the coming months, targeting knowledge workers in technology, consulting, and professional services — the precise humans whose working days are most legible to an AI and therefore most available for renegotiation.
Turakhia described the opportunity with characteristic optimism. The software was built in three months, the market is enormous, and the incumbents are encumbered. All of this is accurate. The knowledge workers, for their part, have not yet been consulted.