Key Takeaways
- • Simplismart, a Bengaluru-based AI inference infrastructure company, raised $14 million in a Series B round led by Dallas Venture Capital, according to a company announcement.
- • Participants in the round included NVIDIA, Accel, Shastra VC and Micromax.
- • The company says its annualised revenue run rate has grown 14-fold over the past six months.
- • Proceeds will fund development of its inference platform, expansion of cloud-provider and sovereign AI partnerships, and growth in North America and other global markets.
- • Customers cited by the company include HeyGen, Higgsfield, InVideo, Shiprocket, Apna and Ema.
Summary
Simplismart, an AI inference infrastructure company headquartered in Bengaluru, has raised $14 million in a Series B funding round led by Dallas Venture Capital, according to a company announcement. NVIDIA, Accel, Shastra VC and Micromax also participated in the round.
The company sells software that helps businesses run and scale AI models on GPU infrastructure, with the aim of optimising performance, speed and cost. Its modular inference engine lets companies customise how models run, while its orchestration platform manages deployment and scaling across cloud and on-premises environments. According to the company, the new capital will be used to further develop this platform, help enterprises run AI applications more efficiently, and enable cloud providers to turn their GPU infrastructure into managed AI services for their own customers.
The funds will also support expansion of cloud-provider and sovereign AI partnerships, as well as growth across North America and other global markets. Co-founder and CEO Amritanshu Jain said that with frontier-class open models now widely available, competitive advantage is shifting toward how models are run, including cost per interaction, response speed and reliability as demand grows. He said the company has spent four years building the software layer between the model and the GPU.
The company claims its annualised revenue run rate has grown 14-fold over the past six months. Customers it names include HeyGen, Higgsfield, InVideo, Shiprocket, Apna and Ema, which use the platform for production workloads spanning video, voice, multimodal and enterprise AI applications. These figures are company-reported and have not been independently verified.
The company sells software that helps businesses run and scale AI models on GPU infrastructure, with the aim of optimising performance, speed and cost. Its modular inference engine lets companies customise how models run, while its orchestration platform manages deployment and scaling across cloud and on-premises environments. According to the company, the new capital will be used to further develop this platform, help enterprises run AI applications more efficiently, and enable cloud providers to turn their GPU infrastructure into managed AI services for their own customers.
The funds will also support expansion of cloud-provider and sovereign AI partnerships, as well as growth across North America and other global markets. Co-founder and CEO Amritanshu Jain said that with frontier-class open models now widely available, competitive advantage is shifting toward how models are run, including cost per interaction, response speed and reliability as demand grows. He said the company has spent four years building the software layer between the model and the GPU.
The company claims its annualised revenue run rate has grown 14-fold over the past six months. Customers it names include HeyGen, Higgsfield, InVideo, Shiprocket, Apna and Ema, which use the platform for production workloads spanning video, voice, multimodal and enterprise AI applications. These figures are company-reported and have not been independently verified.
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