Bengaluru-based startup Unbound has raised US$4 million in a seed funding round led by Race Capital.

Other investors include Wayfinder Ventures, Y Combinator, and Massive Tech Ventures, along with several angel investors.

The startup was co-founded by Rajaram Srinivasan and Vignesh Subbiah, who have backgrounds in enterprise security and infrastructure.

Unbound provides enterprises with tools to manage and secure AI usage. Its AI Gateway helps prevent data leaks, monitor usage, and manage model access and costs.

It also allows real-time redaction of sensitive content and routes high-risk requests to internal models.

The platform is used by mid-market and enterprise clients across sectors like technology and healthcare.

🔗 Source: Unbound

🧠 Food for thought

1️⃣ AI governance market emerges from shadow IT transformation

The evolution of Unbound reflects a larger pattern in enterprise technology adoption, where employee-driven tools become mission-critical infrastructure requiring governance.

This mirrors the journey of cloud computing, which began as shadow IT before evolving into a managed enterprise function. By 2026, Gartner predicts 75% of businesses will use generative AI for synthetic customer data, up from less than 5% in 20231.

McKinsey’s research shows this rapid adoption comes with significant challenges: while 92% of companies plan to increase AI investments, only 1% consider their organizations mature in AI deployment practices2.

Unbound’s focus on making AI “safe, observable, and governable” addresses the governance gap that emerged during previous technology waves, with enterprises now facing the challenge of balancing innovation with control.

The company’s approach of working with existing tools rather than blocking them entirely reflects lessons learned from previous technology transitions, where overly restrictive policies often drove adoption underground.

2️⃣ Data leakage becomes central AI security concern with quantifiable costs

Unbound’s success in preventing leakage of credentials and personal information highlights data protection as a primary enterprise AI security concern.