Yotta Data Services, a leading provider of sovereign AI, cloud infrastructure, and platform services in India, has launched Shakti Studio, an enterprise-grade AI cloud platform designed to accelerate AI adoption by eliminating infrastructure complexities.
The platform offers on-demand serverless GPUs, fine-tuning, and production-ready AI endpoints for large language models (LLMs), vision, and speech, enabling developers, data scientists, and enterprises to quickly build, deploy, and scale AI models without managing infrastructure.
As part of Yotta’s Shakti Cloud, Shakti Studio balances accessibility with enterprise-grade performance. It features an intuitive self-service portal for beginners and students, while providing SLA-backed reliability and secure, compliance-ready environments for large organisations. The unified platform supports training, deployment, scaling, and monitoring, reducing time-to-market for enterprises.
Commenting on the launch, Sunil Gupta, Co-Founder, MD and CEO of Yotta Data Services, said, “The Indian ecosystem is in perfect alignment to allow for widespread AI adoption and deployment. Shakti Studio is a major step forward in democratising enterprise AI adoption and the fastest path for an enterprise from model to market. With a sharp focus on enabling innovation and delivering value, Shakti Studio is specifically designed to help India accelerate its vision of becoming the AI garage of the world.”
Shakti Studio’s serverless design removes infrastructure concerns while ensuring speed, security, and cost efficiency through optimised GPU usage and flexible hardware. With built-in SLAs, compliance, and monitoring, the platform runs on both owned infrastructure and Yotta’s managed environment.
Bhavesh Adhia, Chief AI Officer and Chief Strategy Officer at Yotta, added, “With Shakti Studio, enterprises, data scientists, and developers can push the boundaries of what AI can achieve. It is our MLOps platform, empowering users throughout the AI journey: from discovering and consuming open-source models to fine-tuning them for specific use cases, ensuring peak performance and results aligned with your vision.”
Key Capabilities of Shakti Studio:
- Shakti Serverless GPUs: On-demand, elastic GPU compute for training, fine-tuning, and deploying AI models without managing physical infrastructure.
- Shakti AI Endpoints: Ready-to-use LLMs, vision, and speech models for integrating AI into applications without building models from scratch.
- Shakti Fine-Tuning: Customisation of models like Llama and Qwen for specific tasks, domains, or languages in secure, distributed GPU environments.
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