Nvidia Backs Simplismart's $14M Series B to Cut GPU Inference Costs

Executive Overview

Simplismart, a Bengaluru-based AI inference optimization startup founded in 2022, announced on October 27, 2026, that it closed a $14 million Series B round led by Dallas Venture Capital, with participation from Nvidia, Accel, Shastra VC, and Micromax. The round values the company at approximately $100 million. Simplismart operates as an optimization layer between AI models and compute infrastructure, automating deployment and management to reduce GPU consumption. The company reports a 56% reduction in GPU serving costs for InVideo and 14x annualized revenue growth over six months to an eight-figure run rate, with more than half of revenue coming from the United States.

Deep-Dive Features & Architecture

Simplismart functions as an intermediary layer between AI models and compute infrastructure, automating how models are deployed and managed rather than leaving manual configuration to customers. Its capabilities include optimizing model latency, request throughput, and compute power consumption, alongside fine-tuning tools, automatic resource scaling, and performance monitoring. The company was founded in 2022 by Amritanshu Jain (former Oracle engineer) and Devansh Ghatak (former Google engineer) and employs 58 people.

The most prominent confirmed operational figure is the 56% reduction in GPU serving costs for InVideo. Simplismart also serves customers including HeyGen, Higgsfield, and Ema, and cloud provider Yotta uses its technology for serverless inference within Shakti Studio. The company's annualized revenue grew 14x over six months to an eight-figure number—a metric based on recent customer usage rather than contracted recurring revenue, and excluding pass-through revenue for infrastructure providers.

Benchmark & Competitive Performance

Simplismart competes with offerings from Nvidia itself and major cloud providers Amazon Web Services, Google Cloud, and Microsoft Azure, as well as startups specializing in accelerating and reducing the cost of running models. The company says its competitive advantage is most evident among customers with strict service-level agreements (SLAs) and total cost of ownership (TCO) requirements, as it offers a customized balance per customer rather than ready-made "faster" or "cheaper" options. The 56% GPU cost saving at InVideo is the most prominent quantitative benchmark available for comparison, while the source did not disclose direct comparison figures with competitors.

Industry Impact & Enterprise Adoption

Simplismart's model of optimizing GPU consumption directly matters to emerging teams in the Gulf, Egypt, and Morocco that pay high dollar-denominated cloud costs. Because the platform is an optimization layer rather than a language model itself, Arabic token efficiency depends on the model being run (such as multilingual models) rather than on Simplismart—meaning the gain for Arabic developers comes from lower operating costs rather than from language-specific optimization. The company's technical integration with Nvidia Dynamo and its use by Yotta's Shakti Studio signal growing enterprise adoption of inference optimization as a cost-control lever.

Conclusion

Simplismart's $14 million Series B at a $100 million valuation, backed by Nvidia, positions the startup as a notable player in the AI inference optimization market. With a confirmed 56% GPU cost reduction for InVideo and 14x revenue growth in six months, the company addresses a critical enterprise pain point: the high cost of running AI models at scale. While it does not offer explicit Arabic-language support or regional availability, its cost-reduction value proposition is directly relevant to developers and enterprises across emerging markets facing dollar-denominated cloud expenses.

Media Source: TechCrunch AI | Fact Verification & Analysis: AI Tools Oasis