As the AI boom strains computing power, Nvidia is backing Indian startup Simplismart with a $14 million funding round, betting on software that allows companies to run AI models more efficiently and, in some cases, on fewer GPUs.
Nvidia participated in an all-primary Series B round along with Accel, Shastra VC, and Micromax, with investment led by Dallas Venture Capital. The deal values the four-year-old startup at about $100 million, including new funding.
Enterprises are currently spending millions on GPUs to power their AI applications, but running these models reliably and economically at scale remains a challenge. Different workloads require clear trade-offs between speed, cost, and performance. Deploying and operating AI models to meet business requirements often also requires complex adjustments. Simplismart says its software automates much of that work, orchestrating how models run on existing computing infrastructure without requiring customers to manage configurations themselves.
“The reality is that no one needs the fastest or cheapest inference,” said Amritanshu Jain (pictured above, left), co-founder and CEO of Simplismart, in an interview. He added that companies instead need to run AI models at a speed and cost that makes sense for their specific applications.
Simplismart’s software sits between AI models and the computing infrastructure on which they run, tailoring how models are deployed and managed to meet customer requirements. It enables companies to get more out of their existing GPU stacks by optimizing factors such as model response speed, the number of requests a model processes, and the computing power it consumes.
The Bangalore-based startup offers businesses a way to deploy and run AI models through its platform or within their existing cloud or on-premises infrastructure. It also provides tools to fine-tune models, automatically scale computing resources as demand changes, and monitor performance. Additionally, Simplismart allows cloud providers to use its software to build and operate their own AI inference services on GPU infrastructure.
Simplismart says its AI video generation platform InVideo has helped reduce the cost of GPU services by 56% using its software. The startup has also partnered with AI video companies HeyGen and Higgsfield, enterprise AI startup Ema, and more. Additionally, Indian cloud provider Yotta is using Simplismart’s technology to power its serverless AI inference services within the Shakti Studio platform.
Simplismart’s annual revenue run rate has increased 14x in the past six months, reaching eight digits in total revenue, Jain told TechCrunch. The company said this figure is based on recent customer usage, not contracted recurring revenue, and does not include revenue passed to infrastructure providers. He did not provide exact figures.
Even though Simplismart has more customers in India, more than half of Simplismart’s revenue comes from the United States, Jain said.
Alongside the investment, Nvidia is working with Simplismart on technology integration, including around its Dynamo inference software, Jain told TechCrunch. The partnership involves engineers from Simplismart and solution architects from Nvidia, with Nvidia also helping introduce the startup to potential customers and partners, Jain said.
Interestingly, this investment presents a clear contradiction, as Nvidia, a major supplier of AI chips, backs software that allows companies to run some workloads on fewer GPUs. However, Jain argued that making AI inference more efficient could make the hardware more attractive to customers, encourage broader adoption of AI applications, and ultimately benefit Nvidia.
Simplismart serves customers in an increasingly crowded market for AI inference software, competing with offerings from Nvidia itself as well as major cloud providers and hyperscalers such as Amazon Web Services, Google Cloud, and Microsoft Azure. The growing demand for AI applications and the need to make better use of expensive GPU resources is also driving demand in this segment, leading more startups to develop tools that allow them to run AI models faster and at lower cost.
“Where we tend to win is when people have to tighten up their SLAs (service level agreements) and TCOs (total cost of ownership),” Jain said, referring to tight performance requirements and tight cost constraints. Unlike competitors that offer preset options for faster or cheaper inference, Simplismart aims to find a balance that suits each customer’s needs, he said.
Simplismart was founded in 2022 by Jain, a former Oracle engineer, and Devansh Ghatak (pictured above, right), a former Google engineer, and grew out of their experience building and deploying machine learning systems. Jain said the two met while studying at BITS Pilani and the startup currently has 58 employees.
Simplismart plans to use the new funding to expand its U.S. presence, expand its team, and further invest in the development of its inference software. Jain told TechCrunch that the US remains an important market for the startup as the company wants to further strengthen its existing customer base.
The funding announcement follows a report in the Indian English-language daily Economic Times that Simplismart is 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 is not actively raising funds. He added that the Series B has ended and will not be extended.
If you make a purchase through links in our articles, we may earn a small commission. This does not affect editorial independence.
