As demand for AI computing power continues to surge, Nvidia has thrown its support behind Indian startup Simplismart through a $14 million funding round. The investment reflects a bet on software designed to help businesses operate AI models more efficiently—sometimes even with fewer GPUs. Nvidia joined the all-primary Series B round alongside Accel, Shastra VC, and Micromax, with Dallas Venture Capital leading the deal. The funding values the four-year-old company at approximately $100 million, inclusive of the new capital.

In today's landscape, organizations are pouring significant resources into GPUs to fuel AI applications, yet running those models reliably and affordably at scale remains a persistent hurdle. Different workloads require unique trade-offs among speed, cost, and performance. Deploying and managing AI models to satisfy business needs frequently demands intricate adjustments. Simplismart claims its software automates much of this complexity, customizing how models operate on existing computing infrastructure rather than leaving customers to handle configurations on their own.

"Nobody actually needs the fastest or the cheapest inference," said Amritanshu Jain (pictured above, left), co-founder and CEO of Simplismart, in an interview. He noted that what companies truly need is to run AI models at speeds and costs that align with their specific use cases. Simplismart's software operates between AI models and the computing infrastructure they run on, adjusting deployment and management to meet customer requirements. The company says it can optimize factors like model response time, request handling capacity, and computing power consumption—helping businesses extract more value from their existing GPU resources.

Based in Bengaluru, the startup provides companies with a way to deploy and run AI models either through its own platform or within their existing cloud and on-premises infrastructure. It also offers tools for fine-tuning models, automatically scaling computing resources as demand fluctuates, and monitoring performance. Additionally, Simplismart enables cloud providers to build and operate their own AI inference services on GPU infrastructure using its software.

Simplismart reports that it helped AI video-generation platform InVideo reduce its GPU serving costs by 56% using its software. The startup also works with AI video companies HeyGen and Higgsfield, as well as enterprise AI startup Ema, among others. Furthermore, Indian cloud provider Yotta leverages Simplismart's technology to power the serverless AI inference service within its Shakti Studio platform. The figure is based on recent customer usage rather than contracted recurring revenue and excludes revenue passed through to infrastructure providers, the company said. He did not disclose the exact figure. More than half of Simplismart's revenue originates from the U.S., even though the startup has more customers in India, according to Jain.

The collaboration involves Simplismart's engineers working alongside Nvidia's solutions architects, and Nvidia has also helped connect the startup with potential customers and partners, Jain stated. Interestingly, the investment presents an apparent paradox: Nvidia, the dominant supplier of AI chips, is backing software that can help companies run some workloads with fewer GPUs. Jain, however, contended that making AI inference more efficient could ultimately benefit Nvidia by making its hardware more appealing to customers and encouraging broader adoption of AI applications.

Simplismart operates in an increasingly competitive market for AI inference software, going up against offerings from Nvidia itself, as well as major cloud providers and hyperscalers including Amazon Web Services, Google Cloud, and Microsoft Azure. A growing number of startups are also building tools to make AI models faster and cheaper to run, driven by rising demand for AI applications and the need to maximize expensive GPU resources. "Where we tend to win is where people have to be more stringent on their SLAs [service-level agreements] and TCO [total cost of ownership]," Jain said, referring to demanding performance requirements and tight cost constraints. Unlike competitors that offer preset options for faster or cheaper inference, Simplismart aims to find a balance tailored to each customer's needs, he said.

Founded in 2022 by former Oracle engineer Jain and former Google engineer Devansh Ghatak (pictured above, right), Simplismart grew out of the pair's experience building and deploying machine-learning systems. The two met while studying at BITS Pilani, and the startup now employs 58 people, Jain said. Simplismart plans to use the new funding to expand its presence in the U.S., grow its team, and invest further in developing its inference software. The U.S. remains a key market for the startup as it looks to build on its existing customer base there.

The funding announcement follows a report by Indian English daily The Economic Times that Simplismart was in talks to raise $40 million to $50 million at a valuation of $300 million to $400 million. Asked about the report, Jain declined to comment, saying the startup was not actively fundraising. He added that the Series B was closed and would not be extended.