NVIDIA competitor Groq expands to India, appoints Mehul Gupta to lead GTM efforts

Gupta’s role involves leading go-to-market efforts, building strategic partnerships, and supporting the company's long-term growth in the region.

Jun 3, 2025 - 15:01
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NVIDIA competitor Groq expands to India, appoints Mehul Gupta to lead GTM efforts

US-based AI infrastructure company Groq is foraying into the Indian market, appointing Mehul Gupta as its first employee and founding member of the India Sales team to establish and drive its go-to-market (GTM) strategy in the country.

“Excited to share that I have joined Groq to establish and drive our Go-To-Market strategy in India! Groq is redefining AI inference with its ultra-fast, energy-efficient platform, delivering high performance at low cost, without compromise. Our custom LPU and cloud infrastructure power today’s most advanced open AI models, enabling over 1.5 million developers (since our Feb 2024 launch) to build and scale confidently on Groqcloud,” read Gupta’s post on LinkedIn. 

Gupta’s role involves leading go-to-market efforts, building strategic partnerships, and supporting the company's long-term growth in the region.

“India is Groq’s second-largest market by developer adoption, and I’m honored to be the first employee and founding member of the India Sales team. My mission is to help organizations unlock the transformative power of AI to drive real business outcomes across industries,” he added. 

The eight-year-old startup, which competes directly with Nvidia in the AI computing space, has carved out a distinct position in the AI chip market. It was valued at $2.8 billion at its $640 million Series D round in August last year. 

Unlike traditional approaches that require programming chips, Groq's custom Language Processing Units (LPUs) and cloud infrastructure are designed for energy-efficient AI processing.

These chips are purpose-built for AI inference, the process where trained models make predictions or generate outcomes, by offering a huge advantage over traditional GPUs in terms of speed and costs.


Edited by Jyoti Narayan