HomeLatest NewsStartupsKluisz.ai raises $9.6 million seed funding to build AI-native private cloud

Kluisz.ai raises $9.6 million seed funding to build AI-native private cloud

Kluisz.ai secures $9.6 million in seed funding from RTP Global, Unicorn India Ventures and others to develop intent-driven, AI-powered private cloud platform.

Preferred Source of Google

startup Kluisz.ai has raised $9.6 million in seed funding led by RTP Global, with participation from Unicorn India Ventures, Blume Founders Fund, Climber Capital and several individual investors. The company will use the capital to expand its team, accelerate product development and support early customer deployments, said a statement.

Founded in 2025, Kluisz.ai is building an AI-orchestrated cloud platform tailored for enterprise workloads that require real-time, hybrid and edge deployments. The startup was co-founded by Abhinav Sinha, former Global COO and CPO at OYO; Vamshidhar Reddy, former McKinsey Partner and executive; and Abhijeet Singh, who earlier led cloud initiatives at Jio and AT&T.

The company said it is building a cloud stack to automate performance, cost and compliance management. The platform integrates observability, zero-trust and AI-native orchestration to reduce manual intervention and support complex deployments.

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Its initial go-to-market focus includes the banking and financial services sector, manufacturing, and organisations with extensive edge computing requirements, said the company.

Abhinav Sinha, co-founder and CEO, said, “We are reimagining the private cloud for the AI era—automated, intelligent and secure from day one. We are building the first intent-driven, AI-orchestrated cloud for the next decade of enterprise workloads where every layer—from silicon to software—is optimised for performance, policy, and security without manual intervention.”

Kluisz.ai plans to scale hiring across engineering and go-to-market functions from its Bengaluru office. The team is also engaging with early enterprise customers to run pilots and evaluate deployment at scale.

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