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Simplismart has raised $14 Mn in a Series B round led by Dallas Venture Capital, with participation from NVIDIA, Accel, Shastra VC, Micromax, and angel investors. The funding will help Simplismart expand globally to serve enterprises and cloud providers seeking to lower the cost of running AI applications at scale. The funding will support platform development, cloud-provider and sovereign AI partnerships, and expansion across North America and other global markets. AI infrastructure startup Simplismart has raised $14 Mn (around ₹133 Cr) in a Series B funding round led by Dallas Venture Capital, with participation from NVIDIA, Accel, Shastra VC, Micromax, and angel investors. Dallas Venture Capital invested close to $5 Mn in the round, cofounder and CEO Amritanshu Jain told Inc42. Simplismart plans to use the fresh capital to further develop its AI inference platform, deepen partnerships with cloud providers and sovereign AI players, and expand across North America and other global markets. AI inference is the process of running trained models to generate responses or predictions. Founded in 2022 by Jain and Devansh Ghatak, Simplismart builds the software layer between AI models and GPU infrastructure. Its inference engine lets businesses configure how models run based on their speed, cost, and performance requirements, while its orchestration platform manages deployment and scaling across cloud and on-premises infrastructure. “We have spent four years building the software layer between the model and the GPU, helping customers optimise how their workloads are deployed and operated. This funding will allow us to take that platform to more enterprises and cloud providers globally,” Jain said. The funding will also support the development of a dynamic GPU scheduling layer to match AI workloads with available computing capacity across regions and time zones, cofounder and CTO Ghatak said. How Simplismart Makes Money Jain said Simplismart offers three deployment and pricing models: shared endpoints, dedicated endpoints, and bring-your-own-compute deployments. Under the shared endpoint model, customers pay based on token consumption, without a minimum fee. Dedicated endpoints allow customers to rent GPU infrastructure along with Simplismart’s optimisation software, with charges linked to GPU usage and runtime. The bring-your-own-compute model caters to businesses that want to run workloads on their own infrastructure to meet data and regulatory requirements, particularly in sectors such as banking, financial services, and insurance. For its cloud-provider offering, Simplismart works with NVIDIA to help providers deploy and manage AI infrastructure at scale. The startup does not own the computing infrastructure. Instead, its software enables cloud providers to offer managed AI services under their own brands using their existing GPUs. The startup said this offering is already being used by Yotta, with Simplismart powering the serverless inference layer of its Shakti Studio platform. This allows customers to run AI models without managing the underlying inference infrastructure themselves. Around 55% of Simplismart’s revenue comes from the US, with the remainder generated in India, Jain said. Its customers include HeyGen, Higgsfield, InVideo, Shiprocket, Apna, and Ema, which use its platform to run video, voice, multimodal, and enterprise AI workloads. Simplismart said its annualised revenue run rate grew 14X over the past six months. Prior to this round, Simplismart raised $7 Mn in a Series A round led by Accel in October 2024. The fundraise comes amid growing investment in India’s AI infrastructure ecosystem. Tata Communications yesterday announced plans to invest $400 Mn to $450 Mn to build 10,000 km of AI-ready connectivity infrastructure across India. The proposed network will connect major data centres and AI hubs to support demand for high-speed, low-latency connectivity.
document fetched 2026-10-28 02:53 · canonical https://inc42.com/buzz/simplismart-bags-14-mn-to-expand-ai-inference-platform