Bhavin Turakhia, the billionaire co-founder of banking tech unicorn Zeta, has announced his fifth venture, an AI-powered enterprise software platform named Neo. Backed by a massive $30 million injection of his personal capital, Neo is designed to directly challenge legacy productivity suites like Microsoft Office and Google Workspace, according to reports.
The platform, which has been undergoing internal testing since April 2026, integrates project management, document handling, and file storage into a single ecosystem where artificial intelligence operates as an active participant rather than a bolt-on assistant. The core premise of Neo is that simply adding AI chatbots to legacy software architectures is fundamentally insufficient.
Turakhia believes that enterprise productivity tools must be rebuilt from the ground up to truly harness artificial intelligence. He highlighted that giants like Microsoft and Google face significant structural disadvantages because their foundational architectures were never designed for an AI-first world. To illustrate the major technological shift, Turakhia was quoted saying, "If you want to build an iPhone, you cannot take Nokia parts and somehow turn them into an iPhone."
Neo marks Turakhia's fifth major entrepreneurial outing, following successful ventures like Directi, Radix, Titan, and Zeta. True to his historical playbook of heavy early-stage bootstrapping, Turakhia is funding the $30 million development phase himself. While the corporate AI sector is one of the most competitive and globally-dominated by heavyweights like Salesforce, Microsoft, and Google, Turakhia plans to scale Neo independently before eventually opening the floor to external investors.
Key Features of Neo
Unlike traditional productivity suites that treat AI as a secondary feature (like drafting an email or summarizing a document), Neo is built to integrate human and AI workflows seamlessly.
- Model-Agnostic Infrastructure: Enterprise clients are not locked into a single AI provider. Neo allows businesses to easily swap between different large language models (LLMs) such as those from OpenAI or Anthropic, ensuring they can leverage the best model for specific tasks or control data costs.
- Active AI Participation: The platform is engineered to bring tasks, documents, and institutional knowledge together, allowing AI agents to proactively collaborate on daily workflows rather than just reacting to user prompts.
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