As demand for AI compute grows, Nvidia has participated in a $14 million Series B financing round in Bengaluru-based Simplismart, a startup that develops software to run AI models more efficiently and sometimes with fewer GPUs. The all-primary round also included Accel, Shastra VC and Micromax, with Dallas Venture Capital leading the investment. The deal values the four-year-old company at about $100 million including the new funding.
What Simplismart offers
Simplismart's software sits between AI models and the compute infrastructure they run on, automatically adjusting deployment and management to meet customers' requirements for speed, cost and performance. The company says this approach lets customers extract more value from existing GPU fleets and, in some cases, reduce the number of GPUs needed for certain workloads.
The startup provides a platform to deploy and run models either through Simplismart or within a customer's existing cloud and on-premises environments. Its tooling includes model fine-tuning, automatic scaling of compute resources as demand changes, and performance monitoring. Simplismart also enables cloud providers to build and operate their own GPU-based inference services using its software.
Customers and impact
Simplismart says it helped AI video-generation platform InVideo cut its GPU serving costs by 56% using the company's software. Other named customers include HeyGen and Higgsfield (AI video companies), enterprise AI startup Ema, and Indian cloud provider Yotta, which uses Simplismart to power the serverless AI inference service in its Shakti Studio platform.
CEO and co-founder Amritanshu Jain told TechCrunch that Simplismart's annualized revenue run rate has increased 14-fold over the past six months to an eight-figure sum, though the company did not disclose the exact amount. That figure is based on recent customer usage rather than contracted recurring revenue and excludes revenue passed through to infrastructure providers. Jain also said that more than half of the startup's revenue comes from the U.S., even though it has more customers in India.
Nvidia collaboration and the apparent paradox
Beyond investing, Nvidia and Simplismart are working on technical integrations, including around Nvidia's Dynamo inference software, Jain said. The collaboration involves Simplismart engineers and Nvidia solutions architects, and Nvidia has helped introduce the startup to potential customers and partners.
The investment raises an apparent paradox: Nvidia, the dominant supplier of AI chips, is investing in software that can help some workloads run with fewer GPUs. Jain argues that improving inference efficiency can ultimately benefit Nvidia by making its hardware more attractive and encouraging wider adoption of AI applications.
Competition and plans
Simplismart operates in a crowded market for AI inference solutions, competing with offerings from Nvidia itself as well as major cloud providers and hyperscalers such as Amazon Web Services, Google Cloud and Microsoft Azure. A growing number of startups are also building tools to make models faster and cheaper to run as demand for AI applications and efficient GPU utilization increases.
Jain said Simplismart tends to win contracts where customers face stringent service-level agreements (SLAs) and tight total cost of ownership (TCO) constraints; rather than offering preset "faster" or "cheaper" modes, Simplismart seeks a balance tailored to each customer's needs.
Founded in 2022 by former Oracle engineer Amritanshu Jain and former Google engineer Devansh Ghatak, who met while studying at BITS Pilani, Simplismart now employs 58 people. The company plans to use the new funding to expand in the U.S., hire more staff and further develop its inference software.
The funding news follows a report in The Economic Times that Simplismart was in talks to raise $40–50 million at a $300–400 million valuation. When asked about that report, Jain declined to comment and said the company was not actively fundraising; he added that the Series B is closed and will not be extended.
