Key Takeaways

  • Bhavin Turakhia committed $30 million of personal capital to launch Neo as an AI-native alternative to Microsoft 365 and Google Workspace.
  • Neo integrates project management, documents, file storage, and generative AI in a model-agnostic platform aimed at mid-sized knowledge-work businesses.
  • Analyst forecasts from Gartner, Forrester, IDC, and McKinsey highlight why AI-first productivity suites are gaining traction as enterprises consolidate digital work environments.

Neo entered the enterprise software conversation with a provocative assertion from its founder, Bhavin Turakhia. Workplace tools built before modern generative AI, he argued, are limited by their foundations. They were designed for static documents, manual workflows, and only incremental automation. Retrofitting chatbots into these systems may help, but the core architecture remains unchanged. This tension pushed him to put $30 million of his own capital behind Neo, a new AI-native enterprise work platform.

Turakhia has made this kind of bet before, having bootstrapped Directi, Radix, Titan, and Zeta before scaling them into substantial companies. He told TechCrunch that AI represents a technology shift significant enough to require a complete rebuild of workplace software, not a light renovation. "If you want to build an iPhone, you can't take the parts of a Nokia and somehow convert it into an iPhone," he said.

Neo began internal testing in April 2026 across Turakhia's companies, including Zeta. The platform combines project management, documents, file storage, and generative AI into a single environment. The goal is to make AI an active participant in day-to-day work rather than just another assistant employees turn to separately. The platform is also model-agnostic, allowing enterprises to switch between AI models rather than being tied to a single provider.

According to Gartner, more than 60% of office productivity applications used by enterprise workers will be AI-augmented by 2026, a major jump from under 10% in 2023. Adoption of generative AI across large organizations has accelerated as vendors add assistants, copilots, and AI-powered automation into nearly every workflow.

Forrester projects global spending on generative AI software platforms and tools will reach about $36 billion by 2030, with a notable share concentrated in productivity and collaboration. IDC's 2024 analysis placed the collaborative applications market at more than $30 billion in revenue for 2023, growing at a high single-digit pace. This is partially driven by enterprises consolidating point solutions into unified hubs, bringing Neo's bundled approach into clearer focus.

Microsoft, Google, and Salesforce dominate the category, embedding AI into their suites at a rapid clip. Yet Turakhia argued most incumbents face a structural disadvantage when adding AI to products designed before generative AI. Startups like Neo, in his view, can move faster because they do not have to maintain compatibility with older architectures or patterns.

He is not the only one starting companies in this space with personal capital. Investor Chamath Palihapitiya launched the enterprise AI coding venture 8090, self-funding it before raising a $135 million round this week. The trend reflects confidence that AI is unlocking new enterprise categories where speed to market is critical.

Neo's go-to-market strategy begins with mid-sized businesses in technology, consulting, and professional services. These organizations rely heavily on knowledge-worker processes that can benefit from integrated AI generation, summarization, and coordination. Turakhia said the initial version of Neo was built in three months, helped substantially by generative AI during development. Without that assistance, he estimates the same work would have required a much larger engineering team and more than a year of effort.

The Bengaluru-based startup employs roughly 45 people today, including 18 engineers. Hiring is expected to reach about 100 employees by year end, with most new roles tied to AI and software engineering.

Industry frameworks will shape how platforms like Neo evolve. ISO/IEC 27001 remains a central benchmark for cloud-based productivity tools that handle business-critical information. Meanwhile, the NIST AI Risk Management Framework, published in 2023, serves as a reference point for enterprises evaluating how AI systems behave, how risks are monitored, and how transparency is maintained. Vendors entering this ecosystem align with these guidelines to establish credibility with CIOs and compliance teams.

According to McKinsey's 2023 work, generative AI could add between $2.6 trillion and $4.4 trillion in annual productivity across operations, marketing, software development, and other functions. Even a small share of global enterprise AI spending would represent a sizeable company. "Even if we end up with 2% to 5% market share, that's larger than anything I've built so far," Turakhia said.

Neo reflects a broader move toward AI-first architecture in workplace software and signals a willingness by founders to place large personal bets on systems designed specifically for the generative AI era. Whether Neo establishes a foothold in the productivity space depends on its execution and whether enterprises continue to consolidate their tools into unified environments, rather than patching AI capabilities into legacy platforms.