Unbound Raises $4 Mn Seed Funding To Secure Enterprise AI Adoption

Unbound, a startup focused on enterprise AI security and governance, has raised $4 million in a seed funding round led by Race Capital.

The round also saw participation from Wayfinder Ventures, Y Combinator, Massive Tech Ventures, and other notable angel investors.

The funds will be used to hire more people in India, grow the business, improve connections within the AI ecosystem, enhance model routing, and support companies using open-source AI models.

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"Their mission was clear: build a system that enables AI innovation without compromising enterprise-grade security. “Blanket bans on AI tools are outdated,” said Subbiah. “With Unbound, we provide surgical security controls for every AI request—allowing enterprises to move fast, without breaking trust.”

“Think of us as the reverse proxy for enterprise AI,” said Srinivasan. “We sit between users and models, ensuring privacy, performance, and cost-efficiency—without friction.”

“We’re proud to back Rajaram, Vignesh, and the team,” said Edith Yeung, General Partner at Race Capital. “Unbound is building the AI governance layer that enterprises desperately need—safe, observable, and built for the real world.”

About Unbound 

Founded in 2023 by Rajaram Srinivasan and Vignesh Subbiah, thre Bengaluru-based Unbound helps IT and security teams keep control when using AI tools. It shows how AI is being used, protects sensitive data, and enforces company rules. This makes AI adoption in businesses safer, clearer, and easier to handle.

Unbound’s AI Gateway connects with popular tools like Cursor, Roo, Cline, and internal copilots. It offers real-time protection, smart model routing, and detailed usage insights.

The product is already being used by many mid-size and large companies in industries like tech and healthcare. One customer even rolled out Gemini 2.5 to over 100 engineers in just a week using Unbound.

So far, Unbound has blocked hundreds of secret leaks—including passwords and API keys—and stopped over 500 cases of private information, like names, phone numbers, and patient data, from slipping out.

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