Simplismart raises $14M Series B to scale AI inference infrastructure globally

AI 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 new capital will support the development of its AI inference engine and orchestration platform, strengthen its cloud-provider network and accelerate expansion across North America and other international markets.

Founded in 2022 by Amritanshu Jain and Devansh Ghatak, Simplismart develops software that helps businesses deploy, manage and optimise AI models in production environments. Its platform focuses on the infrastructure layer between AI models and graphics processing units (GPUs), helping organisations balance performance, latency, computing costs and resource utilisation.

The funding comes as enterprises move beyond experimenting with AI models towards operating them reliably at scale. As applications involving generative AI, voice, video and multimodal systems become more widely deployed, the cost and complexity of running these workloads have become important considerations for businesses.

Entrackr reported that the latest round values Simplismart at approximately $100 million post-money. The company previously raised $7 million in a Series A round in October 2024.

Focusing on the economics of AI inference

Simplismart's platform is designed to optimise how AI models operate once they are deployed. Its inference engine helps determine suitable configurations for different workloads, while its orchestration capabilities support deployment, scaling and management across cloud and on-premises environments.

Rather than building AI models itself, the company focuses on the software infrastructure required to run them efficiently. This can help organisations manage the trade-offs between response times, throughput, reliability and computing expenditure.

The distinction is increasingly relevant as businesses deploy AI applications to serve customers and support internal operations. Model performance alone does not determine commercial viability; the cost of generating each response and the ability to maintain service quality under growing demand also matter.

Simplismart says its annualised revenue run rate increased 14-fold over the six months preceding the announcement. Its customers include HeyGen, Higgsfield, InVideo, Shiprocket, Apna and Ema, which use its platform for production workloads spanning video, voice, multimodal and enterprise AI applications.

The reported growth points to increasing demand for infrastructure that helps businesses operationalise AI, although annualised revenue run rate is not the same as recognised revenue.

Enabling cloud providers to offer AI services

Simplismart also works with cloud providers seeking to turn existing GPU infrastructure into managed AI services. Its software layer allows providers to offer AI inference capabilities to enterprise customers without having to build the entire deployment and orchestration stack themselves.

This approach differs from business models centred on purchasing or reserving GPU capacity and reselling it. Simplismart instead focuses on the software that helps third-party infrastructure support production AI workloads.

One example is Yotta, where Simplismart's technology powers the serverless inference layer of Shakti Studio. This enables customers to run AI models without having to manage the underlying infrastructure directly.

The company is also working with cloud providers and sovereign AI programmes across India, North America, the Middle East, Australia and East Asia. These relationships could provide opportunities to serve organisations seeking AI infrastructure that aligns with their operational, geographic and compliance requirements.

Funding to support global expansion and GPU scheduling

Simplismart plans to invest the new capital in further developing its inference and orchestration platform, expanding its cloud-provider ecosystem and growing its international presence.

Another priority is the development of a dynamic GPU scheduling layer that could match AI workloads with available computing capacity across regions, time zones and cloud environments.

The broader objective is to make distributed computing resources more flexible, allowing workloads to be directed towards infrastructure that best meets their cost, performance and operational requirements.

If developed successfully, this approach could help cloud providers improve utilisation of their GPU fleets while giving enterprises more options for deploying AI applications across different environments.

The funding therefore supports both product development and the partnerships needed to connect AI workloads with computing capacity at scale.

Competing in the AI infrastructure market

Simplismart's latest round reflects investor interest in the infrastructure required to make AI commercially practical. While advances in models continue to attract attention, businesses also need systems that can deploy those models efficiently, control costs and maintain reliable performance in production.

For enterprise AI providers and cloud operators, inference optimisation is becoming an important part of that equation. Simplismart is positioning its platform around this operational challenge, with a focus on software, orchestration and GPU utilisation rather than ownership of computing hardware.

With backing from Dallas Venture Capital, NVIDIA and its other investors, the company plans to deepen its technology offering and expand its reach across global markets.

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About Simplismart

Simplismart is an AI infrastructure company founded in 2022 by Amritanshu Jain and Devansh Ghatak. Its platform helps enterprises and AI-native companies deploy, optimise, manage and scale AI models in production. The company also provides software that enables cloud providers to offer managed AI inference services using GPU infrastructure.

Source: Simplismart Official Blog