Bhavin Turakhia is making a personal $30 million bet that enterprise productivity software needs more than AI add-ons. According to TechCrunch, the Indian entrepreneur has launched Neo, a new company building what he describes as an AI-native workplace platform intended to compete with Microsoft Office and Google Apps, now widely known as Google Workspace.

The move matters because it targets one of the busiest parts of the AI software market: the suite of tools where employees write documents, manage projects, store files, and increasingly rely on automation. Rather than offering a standalone assistant layered on top of existing work apps, Neo is being positioned as a single system where AI is built into the product from the start. That is an ambitious claim in a market already crowded with large incumbents and fast-moving startups.

A familiar founder takes aim at office software

Turakhia is not entering the market as an unknown founder. TechCrunch reports that he has previously co-founded Directi, Radix, Titan, and Zeta, and has often started companies with his own capital before bringing in outside investors later. Neo is his fifth venture and his latest focused on enterprise software.

That history is part of the story. Founders with operating track records can sometimes fund longer product buildouts before facing pressure to show rapid venture-style growth. In Neo’s case, TechCrunch says Turakhia is again using his own money, arguing that generative AI is a technological shift large enough to justify rebuilding workplace software from the ground up rather than modernizing older systems.

His central argument, as reported by TechCrunch, is that products designed before the current AI wave are structurally constrained. In his view, adding chat interfaces or copilots to legacy products is not the same as designing workflows, storage, and collaboration around AI from day one. That is a sharper thesis than simply saying AI should be added everywhere; it suggests the core architecture of productivity software should change.

What Neo says it has built so far

TechCrunch describes Neo as an enterprise work platform that combines project management, documents, file storage, and AI in one product. The company launched the system internally in April, according to the report, and has been using it across Turakhia’s businesses, including Zeta.

The product direction is notable because it goes after multiple categories at once. Instead of building a narrow assistant for writing or meetings, Neo appears to be trying to replace pieces of a full productivity stack. That means it is competing not only with Microsoft Office and Google Workspace, but also with point tools such as Notion and adjacent workflow vendors.

Turakhia also told TechCrunch that Neo is model-agnostic, meaning enterprise customers would be able to switch among underlying AI models instead of being locked into one provider. For buyers worried about price volatility, model quality shifts, geographic restrictions, or governance requirements, that flexibility could be meaningful if it works in practice. But the article does not provide technical detail on how model routing, data controls, or performance tradeoffs are handled, so those capabilities remain more strategic positioning than independently verified differentiators.

The startup is based in Bengaluru and currently has around 45 employees, including 18 engineers, according to TechCrunch. It expects to grow to roughly 100 employees by year-end, with most of the hiring focused on AI and software engineering. The company plans to begin rolling out Neo to mid-sized businesses in the coming months, initially targeting knowledge workers in technology, consulting, and professional services.

Why this launch lands in a crowded AI workplace market

Neo is arriving at a moment when nearly every major enterprise software company is trying to redefine productivity around AI. Microsoft is embedding AI across Microsoft Office. Google is doing the same across Google Workspace. Salesforce is also pushing AI deeper into business workflows, while model providers such as OpenAI and Anthropic continue expanding into enterprise use cases that overlap with traditional software categories.

At the same time, startup competition is intense. Products like Notion and Superhuman are reworking user experiences around AI-assisted workflows rather than simple automation features. The result is a market where founders are no longer just competing on whether they have AI, but on whether AI changes speed, reliability, coordination, and cost enough to justify switching software.

That makes Neo’s challenge twofold. First, it must convince companies that AI-native design produces materially better work outcomes than AI features added to existing suites. Second, it has to overcome the distribution advantage of incumbents that already control email, documents, identity, and collaboration systems. Even if a startup offers a cleaner architecture, enterprises often prefer to consolidate around vendors they already trust for security, compliance, and support.

Turakhia’s view, per TechCrunch, is that enterprise software is not a winner-takes-all market. He reportedly argued that even a small slice of enterprise AI spending could support a large business. That is plausible in broad terms, but market share assumptions remain hypothetical until Neo reaches external customers and discloses meaningful deployment or usage data.

Evidence, product claims, and what is still unproven

The reporting here is based primarily on TechCrunch’s interview with Turakhia, making many of the most important product and market claims founder-reported rather than independently verified. That does not make them untrue, but it does mean readers should separate confirmed facts from company assertions.

Confirmed facts reported by TechCrunch include the launch of Neo, Turakhia’s $30 million personal investment, the company’s Bengaluru base, the current team size, internal deployment across affiliated companies including Zeta, and the plan to target mid-sized businesses in the coming months.

Several other points should be treated as claims from the company. One is the strategic thesis that older workplace software cannot be effectively adapted for the AI era. Another is the assertion that Neo is genuinely model-agnostic in a way enterprises will find useful at scale. A third is the founder’s estimate that Neo’s initial platform was built in three months, with heavy use of AI during development, versus more than a year using a larger engineering team before generative AI. That timeline may reflect real productivity gains, but it is still a self-reported estimate rather than a benchmark audited by an outside party.

There are also no external customer references yet in the available reporting. Internal use across the founder’s own companies can be a useful proving ground, but it is not the same as independent enterprise adoption. There is no disclosed pricing, retention data, security certification detail, or public evidence yet on how well Neo performs against Microsoft Office, Google Workspace, or more focused tools in day-to-day production environments.

What this means for builders and enterprise buyers

For AI builders, Neo is another sign that some experienced founders believe the defensible opportunity is not just model access, but application architecture. If that thesis is right, the next generation of enterprise winners may come from products that collapse separate tasks such as writing, retrieval, project updates, and file management into a single AI-mediated workflow.

For product teams, Neo’s launch underscores a practical design question: should AI remain a sidecar, or should it be the organizing layer of the application? Companies building internal tools, coding assistant products, or workplace automation software will need to answer that clearly. Buyers are increasingly skeptical of shallow copilots that save a few clicks but do not reduce real work.

For enterprise AI buyers, the model-agnostic promise is attractive, especially as concerns grow over vendor lock-in and changing model economics. But enterprises will likely need more than flexibility claims. They will want evidence on data governance, auditability, workflow reliability, and whether switching models affects user experience or output quality. In productivity software, trust and consistency usually matter as much as raw model performance.

Neo may also appeal to companies that feel boxed in by fragmented software stacks. If one platform can unify project management, documents, and file storage with useful automation, there is a budget and simplicity argument. The hurdle is migration. Replacing entrenched systems is difficult even when users dislike them.

What to watch next

The next signal to watch is external rollout. Neo says it plans to target mid-sized businesses soon, so the first credible proof point will be named customers, even if only a small number, outside Turakhia’s own portfolio.

Second, watch for product detail. Enterprises will want to see how Neo handles permissions, admin controls, document provenance, model switching, and integration with tools they already use. Without those details, “AI-native” risks remaining a branding phrase rather than an operational advantage.

Third, watch hiring and pace of execution. Growing from about 45 employees to around 100 by the end of the year, as TechCrunch reports the company expects to do, would suggest Turakhia is preparing for a larger commercial push rather than a long private incubation.

Finally, watch whether incumbents respond by tightening integration across Microsoft Office, Google Workspace, and Salesforce. The more deeply those vendors fuse AI into existing workflows, the harder it becomes for a newcomer to argue that greenfield design alone is enough to win adoption.

Creati.ai perspective

Neo is an important launch less because it introduces a confirmed breakthrough and more because it sharpens a serious strategic wager in enterprise AI: that the winning workplace software of the next decade may need to be rebuilt, not retrofitted. Turakhia has the capital and operating history to test that wager without immediately depending on outside funding, which gives the company unusual room to iterate.

But execution risk is high. Enterprise buyers already have Microsoft Office, Google Workspace, Salesforce, Notion, and a growing set of AI agents competing for the same daily workflows. To break through, Neo will need to show not just cleaner AI integration, but measurable improvements in collaboration, deployment, and reliability. In this market, architecture matters—but distribution, trust, and switching costs still decide who gets used.