Customer Service Automation
Sarvam AI needed to train and serve multilingual foundation models for India at national scale, but unreliable GPU clusters, slow preprocessing of noisy code-mixed text and speech data, and long deployment cycles kept real-time sovereign AI services out of reach.
Reported impact
Sarvam reduced time-to-first production inference from weeks to minutes, achieved near-linear scaling across 4,096+ H100 GPUs, delivered multilingual voice feedback and fraud alerts for Aadhaar, and created a reusable sovereign AI platform for public and enterprise services across India.
Sarvam built a sovereign AI factory on NVIDIA accelerated computing so it could train, align, and serve models for India's languages and dialects. The stack combines H100 GPUs, NVIDIA Quantum InfiniBand networking, Nemotron datasets, NeMo libraries, NIM microservices, Base Command Platform, TensorRT, and Cloud Functions. During training, the company uses large-scale GPU clusters with Megatron-LM 6D parallelism to keep 100B-plus parameter mixture-of-expert models running efficiently across more than 4,096 GPUs on Yotta. Cloud Functions compress production deployment from weeks to minutes, while NIM and TensorRT support low-latency inference for voice-agentic flows that combine speech recognition, LLM reasoning, and text-to-speech. That unified architecture gives Sarvam a single platform for public-sector deployments such as Aadhaar feedback and for enterprise automation across India.
Noisy multilingual text and speech corpora are preprocessed into training datasets, large MoE models are trained across thousands of H100 GPUs, optimized services are deployed through Cloud Functions, and NIM plus TensorRT power low-latency voice-agentic applications for Aadhaar and enterprise users.
Near-linear GPU scaling was achieved across 4,096+ NVIDIA H100 GPUs.
Sarvam set out to train, align, and serve foundation models for a nation of 1.4 billion people speaking dozens of languages and hundreds of dialects.
Time-to-first-inference for production scale was reduced from weeks to minutes using NVIDIA Cloud Functions.
UIDAI uses Sarvam's AI for Aadhaar, India's national digital identity program, to deliver near-real-time, voice-based feedback and fraud alerts to India's entire population in their native languages.
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The Organization JSON-LD on Built In lists numberOfEmployees value 50 for Sarvam.
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