As the AI boom strains computing capacity, Nvidia has backed Indian startup Simplismart in a $14 million funding round — betting on software that helps companies run AI models more efficiently and, in some cases, with fewer GPUs.
Simplismart (Credits: TechCrunch)
Nvidia participated in the all-primary Series B round alongside Accel, Shastra VC and Micromax, with Dallas Venture Capital leading the investment. The deal values the four-year-old startup at about $100 million, including the new funding.
Nvidia Backs Simplismart to Run AI Models With Fewer GPUs
Companies are spending heavily on GPUs to power AI applications, but running those models reliably and economically at scale remains a challenge. Different workloads demand distinct trade-offs between speed, cost and performance, and deploying models to meet business requirements often involves complex configuration work.
Simplismart says its software automates much of that work. It sits between AI models and the computing infrastructure they run on, tailoring how models are deployed and managed to meet each customer’s requirements — optimizing response speed, request volume and computing power consumed, so companies get more out of their existing GPU stack.
“Nobody actually needs the fastest or the cheapest inference,” co-founder and CEO Amritanshu Jain told TechCrunch, adding that companies instead need to run AI models at speeds and costs that make sense for their specific applications.
Simplismart Growth, Customers and Nvidia Partnership
The Bengaluru-based startup lets companies deploy and run AI models through its own platform or within their existing cloud and on-premises infrastructure, with tools to fine-tune models, auto-scale resources as demand changes, and monitor performance. Cloud providers can also use its software to build their own AI inference services.
Simplismart says it helped AI video-generation platform InVideo cut its GPU serving costs by 56%, and it also works with HeyGen, Higgsfield and Ema, while Indian cloud provider Yotta uses its technology to power the serverless AI inference service in its Shakti Studio platform.
Its annualized revenue run rate has grown 14-fold over the past six months to an eight-figure sum, Jain said, with more than half of revenue coming from the US despite having more customers in India.
Alongside the investment, Nvidia has been working with Simplismart on technical integrations around its Dynamo inference software, and has introduced the startup to potential customers and partners. The apparent paradox — the dominant GPU supplier backing software that can reduce GPU use — is one Jain brushes aside: making inference more efficient, he argues, could ultimately benefit Nvidia by making its hardware more attractive and encouraging wider AI adoption.
Also Read: 32GB RTX Spark vs Snapdragon X2 Laptop for Local AI: Only One Could Actually Run the Model
Source: TechCrunch AI — read the full story there.