Nava, an AI infrastructure startup, has secured $22 million in a Series A round led by Greenoaks Capital, with participation from existing backers RTP Global and Unicorn India Ventures. The fresh capital will accelerate expansion of its integrated “neocloud” platform that helps businesses deploy and manage AI workloads across cloud, on-premises and edge environments.
Nava’s platform and funding history
Founded by former OYO executive Abhinav Sinha alongside Vamshidhar Reddy and Abhijeet Singh, Nava had earlier raised $9.6 million in a seed round. With the latest infusion, the company’s total funding exceeds $31 million as it scales its AI infrastructure offerings.
Building a full-stack AI cloud ecosystem
Moving beyond pure GPU rental, Nava is assembling a full-stack AI infrastructure that integrates data centres, GPU compute, developer tools and managed services. The platform is designed to let enterprises specify constraints such as budget, compliance and performance, after which the system automatically schedules and runs AI workloads in the optimal environment—public cloud, private data centre or edge nodes.
Services include GPU-as-a-service, bare-metal servers and orchestration layers to simplify deployment, monitoring and scaling of AI applications, reducing the operational complexity faced by companies adopting large models and ML pipelines.
Asia-Pacific focus and expansion plans
Nava has established regional headquarters in Singapore while maintaining core operations in India. The Series A proceeds will be directed to expanding GPU capacity, building AI-focused data centre infrastructure and hiring engineering and operations talent across India and Southeast Asia.
The company cites strong projected growth in AI infrastructure demand across the Asia‑Pacific market through 2030 and aims to capture market share by establishing capacity and compliance-ready facilities early.
Market positioning
With founders experienced in scaling technology businesses and backing from prominent investors, Nava is positioning itself as a regional contender in the AI infrastructure space, seeking to support enterprises as they adopt generative AI, model training and inference at scale.
