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Bengaluru AI Startup Simplismart Raises $14 Mn in NVIDIA-Backed Round
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Bengaluru AI Startup Simplismart Raises $14 Mn in NVIDIA-Backed Round

The company will use the funds to develop its AI inference platform, expand partnerships with cloud providers and sovereign AI players.

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Key takeaways

  • Bengaluru-based startup Simplismart raised $14 million in a Series B funding round led by Dallas Venture Capital.
  • The funds will enhance its AI inference platform and expand partnerships with cloud providers and sovereign AI players.
  • Simplismart's revenue has increased 14 times in six months, highlighting strong demand for its AI optimisation services.
  • The company's platform helps enterprises optimise costs and performance while running AI applications across various use cases.
  • As open-weight models gain traction, enterprises are focusing on cost-effective production solutions for AI applications.
5 min

Bengaluru-based AI inference infrastructure startup Simplismart has raised $14 million in a Series B funding round led by Dallas Venture Capital, with participation from NVIDIA, Accel, Shastra VC and Micromax.

The company will use the funds to develop its AI inference platform, expand partnerships with cloud providers and sovereign AI players, and grow its presence in North America and other global markets.

Simplismart said its annualised revenue run rate grew 14 times over the past six months. Its customers include HeyGen, Higgsfield, InVideo, Shiprocket, Apna and Ema, which use its platform to run production workloads across video, voice, multimodal and enterprise AI applications.

Simplismart builds software that sits between AI models and GPU infrastructure, helping enterprises optimise the cost, speed and performance of running AI applications. Its platform also allows cloud providers to offer managed AI services using their existing GPU infrastructure.

“With frontier-class open models now readily available, access alone is no longer enough to set a business apart. The advantage comes from how you run them: what each interaction costs, how quickly the application responds, and whether it stays reliable as demand grows,” said Amritanshu Jain, Co-founder and CEO of Simplismart.

The funding comes as enterprises look to control the cost of running AI applications in production, particularly as open-weight models provide alternatives to proprietary models accessed through APIs.

Simplismart lets customers configure inference frameworks, quantisation and caching based on the requirements of individual workloads.

“Running AI models in production involves much more than choosing a model and a GPU. Decisions around inference frameworks, quantisation and caching directly affect how quickly an application responds and what it costs to run,” said Devansh Ghatak, Co-founder and CTO of Simplismart.

Simplismart also provides infrastructure software to cloud providers, allowing them to offer AI inference services under their own brands without developing the underlying software stack.

Simplismart works with NVIDIA to help cloud providers deploy and manage AI infrastructure at scale. Unlike inference providers that purchase or reserve GPU capacity for resale, Simplismart does not own computing infrastructure. Instead, it provides the software layer that allows cloud providers to offer AI inference services using their existing GPU infrastructure.

The platform is being used by Yotta Data Services to power the serverless inference layer of Shakti Studio. The service allows customers to run AI models without managing the underlying inference infrastructure.

Simplismart said it is also working on a dynamic GPU scheduling layer that would match AI workloads with available computing capacity across regions and time zones. The system is intended to help cloud providers improve GPU utilisation.

“Inferencing is emerging as one of the biggest game changers in AI economics,” said Dayakar Puskoor, Managing Partner at Dallas Venture Capital. He added that Simplismart was helping enterprises run AI workloads more efficiently while allowing cloud providers to turn GPU capacity into services.

The company’s platform supports deployment across AWS, Microsoft Azure, Google Cloud, sovereign and other cloud providers, as well as on-premises infrastructure.