Fewer GPUs, Lower Costs: Why NVIDIA Is Backing This Indian AI Startup

NVIDIA-backed Indian AI startup Simplismart is helping businesses tackle one of AI’s biggest challenges: the high cost of running models at scale. As companies deploy more AI applications, optimizing computing resources is becoming just as important as building powerful models.

NVIDIA Backs Simplismart With $14 Million

Bengaluru-based Simplismart has raised $14 million in Series B funding, led by Dallas Venture Capital, with participation from NVIDIA, Accel, Shastra VC and Micromax. Founded in 2022, the company builds software that helps businesses deploy, optimize and manage AI models.

Its platform aims to make AI infrastructure easier to operate while improving performance and reducing unnecessary computing expenses.

How Does Simplismart Reduce AI Costs?

Running AI models requires computing power, particularly GPUs. Poorly optimized workloads can waste resources and increase the cost of serving users.

Simplismart helps businesses optimize these deployments and get more value from their available infrastructure. The company says its technology helped AI video platform InVideo reduce GPU serving costs by 56%. Its customers also include HeyGen, Higgsfield and Ema. For businesses running AI applications at scale, such savings can make a meaningful difference to operating costs.

Why Is NVIDIA Investing?

NVIDIA-backed Indian AI startup Simplismart

NVIDIA is a leading supplier of AI chips, so backing software that helps companies use GPUs more efficiently may seem surprising.

However, cheaper AI operations could encourage more businesses to adopt AI, potentially expanding demand for computing infrastructure. NVIDIA’s involvement also includes technical collaboration with Simplismart. The investment highlights how the AI industry is expanding beyond chips and models into the infrastructure needed to deploy them efficiently.

What This Means for AI Startups

The NVIDIA-backed Indian AI startup represents a growing opportunity in AI infrastructure. Businesses need more than powerful models; they need affordable, reliable ways to run them in real-world environments.

For founders, the lesson is simple: solving the expensive problems behind AI adoption can be just as valuable as building the next AI application.

As AI usage grows, the companies that make it cheaper and easier to operate could become essential to the industry.

Follow Tepi AI for more updates on AI startups, funding and emerging technology.