AI Startups Are Finding That GPUs Are Only Part Of The Problem
India’s AI startup ecosystem is entering a phase where building a working AI product is no longer the only challenge. As startups move from experimentation to production, infrastructure decisions are becoming closely tied to their ability to control costs, handle rising workloads, and meet enterprise requirements.
For early-stage founders, cloud credits can make experimentation easier. But the infrastructure choices made during that period can also influence how a product is built for years. Once usage grows, startups can face a different set of challenges around inference costs, storage, networking, observability, data governance and portability.
The same shift is visible in the conversation around AI compute. While GPU availability remains important, having access to GPUs does not automatically translate into an efficient production environment. Startups also need to ensure that data can move efficiently, workloads can scale, and infrastructure costs remain aligned with the economics of the product.
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