CAMB.AI Partners Kompact AI to Bring Multilingual Voice AI to CPU-Based Enterprise Systems

CAMB.AI, an AI-powered multilingual voice translation and content localisation company, has announced a strategic partnership with Kompact AI by Ziroh Labs aimed at reducing the cost and complexity of deploying enterprise-grade AI.

The collaboration combines CAMB.AI’s multilingual voice synthesis capabilities with Kompact AI’s CPU-first runtime that enables large language models to run efficiently on standard processors without relying on costly GPU infrastructure.

By optimising LLM inference for CPUs, Kompact AI enables organizations to deploy high-performance AI workloads while maintaining output quality and throughput.

CAMB.AI has built its reputation around emotionally authentic multilingual voice translation, particularly in live sports and media.

Its technology has been used by organisations such as NASCAR, Major League Soccer, the Australian Open, FanCode and Comcast NBCUniversal. Kompact AI, meanwhile, has focused on challenging the GPU-centric AI model by demonstrating that optimised CPU-based systems can deliver comparable performance at significantly lower costs.

According to the companies, the joint solution can reduce AI inferencing costs by up to 50%, helping enterprises scale multilingual AI applications without resorting to model compromises such as quantisation or distillation.

“Just as we've democratised multilingual communication by making voice translation accessible across 150+ languages, this partnership with Kompact AI democratises access to powerful AI infrastructure. Enterprises no longer need to choose between performance and accessibility. They can now deploy our MARS7 and BOLI models on standard CPU infrastructure while achieving broadcast-quality results,” said Akshat Prakash, Co-Founder and CTO of CAMB.AI.

Speaking about the partnership Hrishikesh Dewan, Co-Founder & CEO at Ziroh Labs said, “CAMB.AI has a proven track record of delivering broadcast-quality voice synthesis at scale and combined with our CPU-first optimization runtime, this promises to be a gamechanger when deploying multilingual AI models across industries from sports to education to healthcare.”

The companies say the partnership will support multilingual AI deployment across sectors including media, education and healthcare, as enterprises seek scalable, cost-efficient alternatives to GPU-heavy AI infrastructure.