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Nityo Infotech Picks Airigo to Build Custom AI Infrastructure

Time:05 Dec 2024


As part of the collaboration, Airigo will build advanced GPU computing to address Nityo Infotech’s need to reduce time-to-value for its enterprise AI initiatives. This move reflects the growing demand for high-performance compute in AI development.

Airigo, an IT infrastructure provider, has been selected by global technology AI solutions provider, Nityo Infotech Corporation to deliver AI infrastructure solutions. This venture will enable Nityo Corp to address its demand for high-performance compute by leveraging advanced GPU computing technologies to provide AI solutions.

 

The venture combines Airigo’s system integration expertise with Nityo Corp’s experience in AI solution development. Airigo’s purpose-built AI infrastructure will enable Nityo Corp, a provider with deep expertise in artificial intelligence solutions, to develop innovative AI solutions that are optimised for its Indian customers. The company will gain access to high-performance compute powered by latest-generation GPUs for distributed AI training, with pre-configured development environments featuring advanced computing toolkits and acceleration libraries, MLOps-ready servers with advanced monitoring and orchestration, and AI software stack integration for PyTorch, TensorFlow, and JAX frameworks.

“By combining forces with Nityo Corp, we’re creating a powerhouse in AI infrastructure. Our solutions will leverage complete accelerated computing stack, from hardware to optimized frameworks, enabling Indian enterprises to fast-track their AI initiatives,” said Pradyumn Dalmia, CEO, Airigo.

According to a NASSCOM-EY report, the Indian AI market is worth $7-10 billion at present and is expected to rise to $22 billion, with a CAGR of 25-35% by 2027. “India stands at the cusp of an AI revolution, and purpose-built infrastructure is the key to unlocking this potential,” said Naveen Kumar, CEO, Nityo Corp. “Together, we will create purpose-built AI solutions that will significantly reduce time-to-value for enterprise AI initiatives.”