Simplismart가 Series B 라운드에서 1,400만 달러를 조달했다. 이번 투자금은 AI 모델과 GPU 역량을 기업이 바로 활용할 수 있는 추론(inference) 서비스로 전환하는 데 쓰일 예정이다.

Simplismart, an AI inference infrastructure company, today announced it has raised $14 million in Series B funding led by Dallas Venture Capital, with participation from NVIDIA, Accel, Shastra VC and Micromax. The funding will accelerate development of Simplismart's inference engine and orchestration platform, expand its cloud-provider ecosystem and support growth across North America and other global markets.

Simplismart builds the software between AI models and GPUs, managing deployment, scaling, and operation to meet customers' performance and cost requirements. Its modular inference engine adapts serving configurations to each workload's latency, throughput, quality, and cost needs.

Over the past six months, Simplismart's annualized revenue run rate has grown 14x. HeyGen, Higgsfield, InVideo, Shiprocket, Apna, and Ema are among the companies running production workloads through Simplismart across video, voice, multimodal, and enterprise AI.

"The industry has spent years pushing the limits of what AI models can do. 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. "We've spent four years building the software between the model and the GPU, bringing workload optimization, deployment, and ongoing operations into one platform. Enterprises use it to run AI applications; cloud providers use it to turn GPU fleets into services they can sell. We've built the infrastructure that makes model capability commercially usable."

"Inferencing is emerging as one of the biggest game changers in AI economics," said Dayakar Puskoor, Managing Partner at Dallas Venture Capital. "Simplismart is rapidly emerging as a global player helping enterprises run AI workloads more efficiently, while enabling cloud providers to turn GPU capacity into scalable services. We are backing this fast-growing company because of its proven technical prowess in addressing a critical need in the AI infrastructure ecosystem globally, as well as the strong execution capabilities of its founding team."

For Simplismart customer Ema, an enterprise AI company, the target was roughly 200 ms latency at about 9 cents per million tokens. Simplismart's optimization search surfaced configurations at 5 cents per million tokens at 350 ms and 12 cents per million tokens at 100 ms, then delivered a production configuration at 7 cents per million tokens and 180 ms, meeting both Ema's cost and latency requirements.

The same approach extends beyond individual deployments. Simplismart provides a unified control plane across clouds, regions, and on-premises infrastructure, allowing teams to apply the same SLA, cost, security, and compliance requirements wherever a workload runs. Instead of managing each GPU environment separately, customers can treat their entire infrastructure as one programmable pool and continuously route workloads to the configuration that best fits their requirements.

Simplismart works with NVIDIA to make AI infrastructure easier to deploy and operate at scale. Rather than buying or reserving GPU capacity to resell, it provides software that turns third-party GPU fleets into production AI infrastructure. Cloud providers can offer managed AI services under their own brands. At Yotta, Simplismart underpins the serverless inference layer of Shakti Studio.

Simplismart is now working across cloud providers and sovereign AI programs, alongside a cloud collaboration pipeline spanning India, North America, the Middle East, Australia and East Asia.

Simplismart is building toward a dynamic GPU scheduling layer to match demand with available capacity across regions, time zones, workloads, and compliance requirements. Idle capacity in one region could eventually serve demand elsewhere when timing and requirements align. The new funding will support the cloud and sovereign AI partnerships needed to make this network possible.