en.Wedoany.com Reported - Nvidia is in advanced talks to lead a new funding round for Indian generative AI company Simplismart, with the total round expected to reach $20 million. Upon completion of the deal, Simplismart's valuation will climb to $100 million. This valuation represents a fourfold jump from its level of approximately $25 million in October 2024 in just 18 months, reflecting the rapid heating up of the AI infrastructure sector in India.
Simplismart was co-founded in 2022 by former Oracle engineer Amritanshu Jain and former Google engineer Devansh Ghatak, with offices in Bangalore, India, and San Francisco, USA. Its core product is an enterprise-grade MLOps workflow orchestration platform, focusing on the capability to "build production-grade AI systems with zero code," covering workloads including large language models, small language models, vision language models, speech recognition and synthesis, as well as text-to-image and text-to-video generation. Enterprise customers can complete the full lifecycle management from model selection, fine-tuning, inference deployment, to operational monitoring through the platform. Currently, the platform serves multiple enterprises including Indian online pharmacy Tata 1mg, sales enablement platform Mindtickle, AI video creation tool InVideo, and comic platform Dashtoon.
The technological alignment between Nvidia and Simplismart has already preceded the capital partnership. Simplismart has previously clarified that its AI inference platform will be deeply deployed on Nvidia infrastructure, with both parties continuously collaborating around Nvidia Inference Microservices (NIM). NIM can deliver containerized AI models as managed production endpoints, offering enhanced governance and cost control features. Domestically in India, Simplismart formed a strategic partnership with Nvidia cloud partner Yotta in October 2025, embedding its inference-first platform into the serverless inference layer of Yotta's Shakti Studio, leveraging Yotta's GPU cloud infrastructure to provide low-latency, localized generative AI services for Indian enterprises and government agencies.
The shareholder composition of this funding round further reflects the capital market's confidence in Simplismart. In October 2024, the company completed a $7 million funding round at a valuation of approximately $25 million, led by Accel, with participation from Shastra VC, Titan Capital, and angel investors including Notion co-founder Akshay Kothari. Existing shareholder Accel is expected to follow on in this round, while at least one new institution is likely to join.
Nvidia's lead investment this time is part of its systematic layout in India's AI ecosystem. In February 2026, Nvidia announced partnerships with Indian domestic venture capital firms Peak XV, Elevation Capital, Nexus Venture, and Accel India to jointly identify and fund startups building AI solutions for domestic and global markets. During the same period, Yotta announced an investment of over $2 billion to purchase Nvidia's latest chips, building an AI computing hub outside the Delhi National Capital Region, and committed to allocating over 10,000 B300 GPUs to India's National AI Mission. Senior Nvidia officials also publicly called during the same period for India to significantly increase its AI infrastructure investment from the current level of about $1.2 billion to match the scale of global competition.
The acceleration of Simplismart's funding round is a microcosm of the financing boom in India's AI infrastructure sector. Industry data shows that approximately 22% to 24% of venture capital deals in India flowed to AI and machine learning startups in fiscal year 2026. During the same period, AI security company Emergent completed a $70 million funding round, and large language model company Sarvam AI is also in negotiations for a $300 million to $350 million funding round at a valuation of about $1.5 billion. Nvidia's choice to enter during Simplismart's valuation upswing targets precisely its long-term architectural value as an intermediate layer for model training and inference deployment—a link that is becoming a critical control point for enterprise AI implementation.
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