Bengaluru-based Nava closed a $22 million Series A led by Greenoaks Capital to build what it calls a "full-stack AI cloud" targeting Asia's compute shortage. The startup combines AI-optimized data centers, GPU compute infrastructure, orchestration layers, and developer tooling into a single platform—positioning itself as a regional alternative to hyperscalers like AWS and Google Cloud for AI workloads.
This matters because Asia's AI infrastructure gap is real and expensive. While we covered Sarvam AI's $250M funding round in March—the largest pure-play AI raise in India—that highlighted the demand side. Nava is betting on the supply side: that Asian developers and companies want local compute that doesn't route through US-controlled infrastructure. With global GPU shortages still constraining AI development, regional providers with dedicated AI-native stacks could capture significant market share if they execute well.
The timing aligns with broader regional infrastructure pushes. Karnataka is expanding its deeptech initiatives beyond Bengaluru, and multiple sources indicate growing investor appetite for Asian AI infrastructure plays. But Nava faces the classic chicken-and-egg problem: they need scale to compete on pricing with hyperscalers, but need competitive pricing to achieve scale. Their "full-stack" approach could differentiate them if it actually simplifies deployment compared to stitching together multiple cloud services.
For developers, this represents another option in the increasingly fragmented AI infrastructure landscape. If Nava delivers on latency and pricing promises for Asian markets, it could be worth evaluating for production workloads—especially for teams concerned about data sovereignty or tired of hyperscaler complexity.