Simplismart Raises $14 Million in Series B Funding to Expand AI Inference Platform

NOIDA, India, Oct. 27, 2026 –

Bengaluru-based 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 fresh capital will support the development of its AI inference platform, strengthen partnerships with cloud providers and sovereign AI infrastructure companies, and accelerate expansion across North America and other international markets.

The funding comes as businesses increasingly focus on the cost and efficiency of running artificial intelligence applications at scale. While access to powerful AI models has become more widespread, deploying those models reliably in production remains a significant technical and financial challenge for enterprises.

Simplismart aims to address this challenge by providing software that helps companies optimise the speed, cost and performance of AI inference across different computing environments.

Simplismart Reports 14-Fold Growth in Annualised Revenue Run Rate

Alongside its latest funding announcement, Simplismart said its annualised revenue run rate increased 14-fold over the preceding six months.

The company serves customers across several AI-driven industries, including HeyGen, Higgsfield, InVideo, Shiprocket, Apna and Ema. According to Simplismart, these businesses use its platform to operate production workloads involving video generation, voice technology, multimodal AI and enterprise applications.

The reported revenue growth points to increasing demand for infrastructure that can support AI applications beyond experimentation and into everyday business operations.

As enterprises deploy generative AI for customer engagement, content production, automation and internal workflows, the underlying infrastructure must be capable of handling growing workloads while keeping computing costs under control.

Simplismart plans to use its new funding to strengthen its technology offering and expand its reach among enterprises and cloud infrastructure providers.

What Does Simplismart Do?

Simplismart develops software that operates between AI models and the GPU infrastructure used to run them. Its platform helps businesses deploy and manage AI inference workloads while optimising computing resources and application performance.

AI inference refers to the process through which a trained AI model generates predictions, responses, images, videos or other outputs when given new input.

Although model development attracts significant attention, inference can become a substantial operational expense once an AI application begins serving large numbers of users.

Simplismart’s platform is designed to help organisations improve inference efficiency through configurable infrastructure and workload optimisation.

Its capabilities include support for different inference frameworks, quantisation and caching techniques. These tools can help businesses tailor deployments to the needs of specific AI models and applications.

The platform also supports deployments across major cloud environments, sovereign cloud infrastructure and on-premises systems, giving customers flexibility in how they operate AI workloads.

Why AI Inference Optimisation Is Becoming Important

The economics of AI deployment are changing as businesses gain access to a wider range of open-weight models and other AI technologies.

Companies no longer compete solely on which model they use. They must also determine how efficiently that model runs, how quickly it responds and how reliably it performs under increasing demand.

Amritanshu Jain, Co-founder and Chief Executive Officer of Simplismart, said access to advanced open models is no longer sufficient to differentiate a business.

He highlighted the importance of managing the cost of each interaction, application response times and system reliability as AI workloads grow.

This challenge is particularly relevant for businesses operating AI-powered video generation, voice assistants, enterprise automation and multimodal applications, where inference demand can fluctuate significantly.

By allowing customers to configure inference frameworks, quantisation and caching according to workload requirements, Simplismart aims to help them improve the operational efficiency of their AI deployments.

Simplismart Helps Cloud Providers Offer Managed AI Services

Beyond serving enterprise customers directly, Simplismart provides infrastructure software that enables cloud providers to offer AI inference services under their own brands.

Rather than purchasing or reserving GPU capacity to resell computing services, Simplismart focuses on the software layer. Its customers can use their existing GPU infrastructure to deliver managed AI services without having to build the entire inference software stack themselves.

This model could help cloud providers expand their AI offerings while reducing the engineering effort required to deploy and manage inference workloads.

The company also works with NVIDIA to support the deployment and management of AI infrastructure at scale.

As demand for AI computing grows, cloud providers are looking for ways to improve GPU utilisation, simplify model deployment and offer specialised services to enterprise customers.

Simplismart’s approach positions it within the infrastructure software segment of the AI market, where performance optimisation and resource management are becoming increasingly important.

Yotta Data Services Uses Simplismart for Serverless AI Inference

Simplismart’s platform is also being used by Yotta Data Services to power the serverless inference layer of Shakti Studio.

The service allows customers to run AI models without having to manage the underlying inference infrastructure themselves.

Serverless inference can simplify AI deployment by abstracting much of the infrastructure management from the application developer. Depending on the implementation, this can make it easier to launch AI workloads without directly managing the allocation and operation of computing resources.

The integration illustrates how inference infrastructure providers can support broader AI ecosystems by helping cloud platforms deliver model-serving capabilities to customers.

Simplismart said it is also developing a dynamic GPU scheduling layer designed to match AI workloads with available computing capacity across different regions and time zones.

The planned capability is intended to help cloud providers use their GPU resources more efficiently by aligning workloads with available infrastructure.

Investors Back Simplismart’s AI Infrastructure Strategy

Dallas Venture Capital led the $14 million Series B round, which also included participation from NVIDIA, Accel, Shastra VC and Micromax.

Dayakar Puskoor, Managing Partner at Dallas Venture Capital, described inference as an important factor in the economics of AI.

He highlighted Simplismart’s approach to helping enterprises run AI workloads more efficiently while enabling cloud providers to convert existing GPU capacity into AI services.

The participation of established investors and technology companies provides Simplismart with additional capital to develop its platform and pursue international expansion.

The company plans to strengthen partnerships with cloud providers and sovereign AI players while growing its presence in North America and other global markets.

Its expansion strategy comes amid growing interest in AI infrastructure that can support enterprise workloads while meeting varying requirements for performance, cost, data governance and deployment flexibility.

Simplismart’s Position in the Growing AI Infrastructure Market

The AI infrastructure market is evolving beyond the development of increasingly capable models. Businesses now need systems that can deploy those models efficiently, integrate them into existing applications and maintain reliable performance as usage increases.

Open-weight models have expanded the range of deployment options available to enterprises. However, running these models in production can require careful decisions about hardware allocation, model optimisation, caching and serving frameworks.

Infrastructure software providers such as Simplismart aim to address these challenges without requiring every enterprise or cloud provider to build its own complete inference stack.

The company’s ability to grow will depend on factors including its technology performance, customer adoption, cloud partnerships and ability to deliver measurable efficiency improvements across diverse workloads.

Its reported 14-fold increase in annualised revenue run rate over six months suggests growing commercial traction, although the company has not disclosed the absolute revenue figure in the information provided.

What Lies Ahead for Simplismart?

With $14 million in fresh funding, Simplismart plans to expand its AI inference platform, deepen its relationships with cloud providers and sovereign AI infrastructure companies, and enter additional international markets.

The development of its dynamic GPU scheduling technology could also strengthen its offering if it helps customers improve utilisation of existing computing resources.

As enterprise adoption of AI continues, infrastructure efficiency is likely to remain an important consideration for companies moving from AI pilots to large-scale production deployments.

For Simplismart, the opportunity lies in helping enterprises and cloud providers run AI applications more efficiently without requiring them to build and maintain every component of the inference stack themselves.

The company’s next phase of growth will show how effectively it can translate investor backing and reported revenue momentum into wider adoption across the global AI infrastructure market.

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