Apulis Technology (Shenzhen)
Heterogeneous AI platform for end-to-end model development.
| Date | Investors | Amount | Round |
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| investor | €0.0 | round | |
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* | CNY20.0m Valuation: CNY500m | Early VC | |
| Total Funding | 000k | ||
Apulis Technology, also known as 依瞳科技 (Yitong Technology), is an artificial intelligence platform and solution provider established in Shenzhen, China, in 2019. The company was founded by CEO Wei Guo, a Tsinghua University graduate who previously led the design team for the Microsoft Surface Book. Apulis focuses on providing end-to-end AI development services for enterprise clients across various sectors, including industrial manufacturing, autonomous driving, education, and energy.
The company's core offering is the Apulis AI Platform, an open-source, integrated environment for machine learning and deep learning. This platform manages the entire AI development lifecycle, from data source management, annotation, and processing to model training, deployment, and monitoring. A key technical feature is its heterogeneous architecture, making it the first commercially available platform to support both NVIDIA GPUs and Huawei's Ascend NPUs. The platform is designed to handle petabyte-scale data and offers flexible deployment options, including public cloud, private cloud, and all-in-one hardware solutions to meet different computing power needs.
Apulis generates revenue by providing its data-centric AI platform and related solution services. The business model caters to enterprises seeking to implement AI by offering low-code/no-code modeling and automated model optimization. The company has secured multiple rounds of funding, including a Series A round in April 2024, with investors such as CITIC Capital, GP Capital, and Haier. This funding is aimed at advancing the platform's technology and accelerating its application in various vertical markets.
Keywords: artificial intelligence platform, machine learning, deep learning, MLOps, heterogeneous computing, data processing, autonomous driving solutions, industrial AI, model training, AI development lifecycle, open-source AI, intelligent manufacturing, data annotation, cloud-side-end synergy, large language models, AI solutions, private cloud AI, computer vision, data management, AI infrastructure