Simplismart Funding: Raises $14 Million in Series B Led by Dallas Venture Capital
- Simplismart has raised $14 million in Series B funding, led by Dallas Venture Capital with participation from NVIDIA, Accel, Shastra VC and Micromax Informatics.
- DVC invested $5 million in the round, which will support AI inference technology, cloud partnerships and international expansion.
- Simplismart reported a 14x increase in annualised revenue run rate over six months, while the US accounts for about 55% of revenue, according to the company.
Bengaluru-based AI infrastructure startup Simplismart has raised $14 million in Series B funding in a round led by Dallas Venture Capital (DVC), with participation from NVIDIA, Accel, Shastra VC and Micromax Informatics.
DVC invested $5 million in the round, while the company did not disclose the individual contributions of the other investors.
The fresh capital will be used to deepen Simplismart’s AI inference engine and orchestration platform, expand partnerships with cloud providers and support international growth, with North America identified as a priority market. The company is also working with partners on sovereign AI infrastructure in India.
Founded in 2022 by Amritanshu Jain and Devansh Ghatak, Simplismart develops software that helps enterprises deploy, optimise and operate AI models in production. Its platform is designed to manage factors such as inference cost, latency, performance and computing resources across cloud and on-premises infrastructure.
About Simplismart
Simplismart focuses on AI inference, the stage at which trained AI models generate outputs such as text, speech, images or video. Its software provides tools for deploying, fine-tuning, monitoring and optimising models, while also helping cloud providers convert GPU capacity into managed AI services under their own brands.
The company describes its approach as cloud-agnostic, allowing enterprises to choose how and where their models run while managing the associated cost and performance requirements. Its platform includes an inference engine and an orchestration layer for deploying and scaling AI workloads.
Simplismart works with companies including HeyGen, Higgsfield, InVideo, Shiprocket, Apna and Ema, which use its software for production workloads spanning video, voice, multimodal and enterprise AI applications. Indian cloud provider Yotta also uses Simplismart’s technology for the serverless inference layer of its Shakti Studio platform.
The startup has also worked directly with NVIDIA on inference technologies. According to DVC, Simplismart is an early member of the NVIDIA Inception programme and has worked on integration involving NVIDIA Inference Microservices (NIM).
Simplismart reported that its annualised revenue run rate grew 14-fold over the six months preceding the Series B announcement, reaching an eight-figure annualised figure. The company has not disclosed the exact amount. CEO Amritanshu Jain also said that approximately 55% of the company’s revenue comes from the US, despite having more customers in India. These are company-reported figures, and the annualised run rate is an estimate based on recent customer activity rather than audited annual revenue.
Before the Series B, Simplismart raised $7 million in Series A funding in October 2024, led by Accel, with participation from Shastra VC, Titan Capital, DVC and angel investors.
What’s Next for Simplismart?
Simplismart plans to use the new funding to further develop its inference engine and orchestration capabilities, while expanding relationships with cloud providers and reaching more enterprise customers globally. North America will be a key focus as the company expands its international business.
The company is also building a dynamic GPU-scheduling layer designed to match AI workloads with suitable computing capacity across regions and time zones. The system is intended to account for factors such as application performance requirements, data residency and compliance boundaries when deciding where workloads should run.
Simplismart is also working towards sovereign AI infrastructure in India, where enterprises and government organisations can retain greater control over where models and data are deployed. Its software is designed to work across private environments and cloud infrastructure rather than requiring customers to rely on a single provider.
The company said the next phase will focus on making AI inference more efficient while expanding the infrastructure layer available to both enterprises and cloud providers.