Nvidia invests in Simplismart’s AI inference efficiency software
Nvidia has participated in a $14 million Series B round for Bengaluru-based Simplismart, a startup that develops software for deploying and operating AI models more efficiently. Dallas Venture Capital led the all-primary financing, joined by Accel, Shastra VC and Micromax. The round values the four-year-old company at about $100 million, including the new capital.
Simplismart positions its platform between AI models and the computing infrastructure on which they run. It adjusts deployment and management choices to match a customer’s requirements for response time, request throughput and computing consumption. The company says this can help organisations obtain more from their existing GPU estate rather than manually managing complex model configurations.
Inference tuning rather than a single performance target
Amritanshu Jain, Simplismart’s co-founder and chief executive, said customers do not necessarily need the fastest or the cheapest inference. They need speeds and costs appropriate to a particular application. That distinction matters as businesses spend heavily on GPUs while trying to operate AI workloads reliably and economically at scale.
The startup offers deployment through its own platform or inside a customer’s existing cloud and on-premises environment. Its software also includes tools for model fine-tuning, automatic scaling as demand changes and performance monitoring. Cloud providers can use the technology to build and operate their own AI inference services on GPU infrastructure.
Simplismart says AI video-generation platform InVideo cut GPU serving costs by 56% with its software. Its customers also include AI video companies HeyGen and Higgsfield, enterprise AI startup Ema, and Indian cloud provider Yotta. Yotta uses the technology to power the serverless AI inference service within its Shakti Studio platform.
Nvidia collaboration and a crowded market
Alongside the investment, Nvidia has worked with Simplismart on technical integrations, including Nvidia Dynamo inference software. Jain said Simplismart engineers are collaborating with Nvidia solutions architects, and Nvidia has introduced the startup to potential customers and partners.
The investment creates an apparent tension: Nvidia is the dominant AI-chip supplier, while Simplismart’s software can allow some workloads to run with fewer GPUs. Jain argued that more efficient inference can still support wider adoption of AI applications and make Nvidia hardware more attractive to customers.
Simplismart competes for inference workloads with Nvidia’s own offerings, major cloud providers including Amazon Web Services, Google Cloud and Microsoft Azure, and a growing group of startups. Jain said the company tends to win where customers have stringent service-level agreements and tight total-cost-of-ownership requirements, rather than where they select a preset option for speed or price.
Growth and use of the new funding
Founded in 2022 by former Oracle engineer Jain and former Google engineer Devansh Ghatak, Simplismart employs 58 people. Jain said its annualized revenue run rate grew 14-fold in the past six months to an eight-figure sum. The figure reflects recent customer usage, not contracted recurring revenue, and excludes revenue passed through to infrastructure providers. More than half of revenue comes from the United States, despite the company having more customers in India.
Simplismart plans to use the funding to expand in the United States, hire more staff and continue developing its inference software. For businesses operating AI applications, the practical implication is to evaluate inference platforms against workload-specific latency, throughput, service-level and cost requirements rather than treating GPU capacity alone as the deployment decision.