Nvidia Invests $14M in Simplismart, AI Inference Software

The GPU designer participated in the $14 million Series B funding round of Simplismart, a Bangalore-based publisher whose software adjusts the execution of models on existing infrastructure. The investment comes with technical integrations, while the startup claims quantified customer cases and accelerated revenue growth.
A Competitive Market and a Bet that Disrupts GPU Usage
Simplismart operates in a segment where it faces offerings from Nvidia, as well as those from AWS, Google Cloud, and Microsoft Azure. Numerous startups are also developing tools aimed at executing AI models faster and at a lower cost, driven by the rise in usage and the need to optimize expensive GPU resources. The investment may seem paradoxical, as Simplismart's software sometimes allows for the use of fewer GPUs. However, Amritanshu Jain argues that more efficient inference can make Nvidia hardware more attractive and encourage the adoption of AI applications. According to him, the publisher excels when SLA and TCO requirements are particularly stringent. Rather than offering predefined profiles for speed or cost, the company seeks to find a balance tailored to each client.
$14M Round Led by DVC and Valuation Around $100M
Simplismart raised $14 million in a primary Series B round led by Dallas Venture Capital. Nvidia participated in the round, alongside Accel, Shastra VC, and Micromax. This funding values the company at approximately $100 million, including the new financing.
Technical Agreement with Nvidia Around Dynamo and Networking
Beyond the investment, Nvidia is collaborating with Simplismart on technical integrations, particularly around the Dynamo inference software. This cooperation involves engineers from Simplismart and solution architects from Nvidia. Nvidia has also introduced the startup to potential clients and partners.
Adjustable Inference Platform, Integrable On-Premises or in the Cloud
Simplismart's software sits between AI models and the underlying infrastructure to adjust deployment and management. The publisher claims to optimize latency, query throughput, and compute consumption to better utilize existing GPU farms. The solution can be used via Simplismart's platform or integrated into clients' cloud and on-premises environments. It includes fine-tuning tools, automatic resource adjustment based on demand, and monitoring. Cloud providers can also build and operate their own GPU inference services with this software. Amritanshu Jain emphasizes that companies do not need the fastest or cheapest inference, but rather speed and cost levels that are relevant for each application.
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InVideo Claims −56% GPU Costs, Other Clients, and an Indian Cloud
According to Simplismart, the video generation platform InVideo has reduced its GPU service costs by 56% thanks to the software. The startup is also partnering with HeyGen, Higgsfield, and Ema. In India, the cloud company Yotta relies on this technology to offer a serverless AI inference service integrated with Shakti Studio.
Quantified Traction, American Anchor, and Revenue Pipeline
Annualized revenue has increased 14-fold over the past six months to reach an eight-figure level, says Amritanshu Jain. This amount is calculated based on recent customer usage and excludes revenue shared with infrastructure providers, with no exact figure disclosed. More than half of the revenue comes from the United States, although the company has more clients in India.
Roadmap, Team, and Capital Context
Simplismart plans to expand its presence in the United States, strengthen its workforce, and invest in the development of its inference software, with the U.S. remaining a key market. The company was founded in 2022 by Amritanshu Jain, a former Oracle employee, and Devansh Ghatak, who previously worked at Google, who met at BITS Pilani. It has 58 employees and is based in Bangalore. A media report indicated that the startup was discussing a raise of $40 to $50 million for a valuation of $300 to $400 million; Amritanshu Jain declined to comment, stating that the company is not actively seeking to raise funds, and clarified that the Series B was closed and would not be extended. Meanwhile, companies continue to allocate significant budgets to GPUs as reliable and cost-effective execution of models at scale remains challenging, with trade-offs between speed, costs, and performance and complex adjustments. Simplismart claims to automate some of these tasks and notes that the company has four years of experience. The software also claims the ability to help execute certain workloads with fewer GPUs.
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