Unbound’s core product is an AI Gateway that plugs into commonly used tools (e.g., Cursor, Roo, Cline or internal copilots) to provide real-time protection, model routing, and usage analytics for enterprise AI. Instead of simply blocking prompts, the platform redacts sensitive content in real time and reroutes high-risk requests to internal open-source models hosted in the organization’s cloud, preserving workflows while preventing data exposure. The company reports it has prevented the leakage of hundreds of secret credentials and more than 500 instances of personally identifiable information; customers have also cited prevention of over 7,000 potential data leaks. Unbound enables fine-grained control over model access and cost, letting teams allocate premium models to high-stakes workflows and route lighter tasks to smaller open-source models—mid-market customers have saved more than $10,000 annually and, per the company, cut AI tooling costs by nearly 70%. The product is in use with a growing base of mid-market and enterprise customers across sectors including tech and healthcare, including a deployment that supported 100+ engineers integrating Gemini 2.5 into production. The founding team—CEO Rajaram Srinivasan (former data security lead at Palo Alto Networks and Imperva) and CTO Vignesh Subbiah (former founding team member at Tophatter and Shogun)—draws on enterprise security and infrastructure experience to scale the product. Future plans for the new funding include expanding integrations across the AI ecosystem, deepening model routing capabilities, and supporting internal model orchestration for enterprises adopting open-source LLMs.

Total raised

$4M

Funding rounds

1

Latest round

Seed

Latest activity

Jun 2025