Taiwan-based startup Profet AI has raised $5.6 million to help manufacturers improve their productivity using artificial intelligence and machine learning solutions.
Manufacturers can transform their big data into AI models and applications. According to Profet AI, the process takes less than a week, as opposed to the usual months. The startup said it was possible because the AI/ML solutions were specifically designed for manufacturers.
Common data solutions are usually developed by data scientists who are not aware of the specific characteristics and challenges in the manufacturing environment. Profet AI has worked with multiple Taiwanese factories, including Foxconn, to develop its products.
Currently, the startup offers two standard solutions. The first one is the Virtual Data Scientist Platform, an AutoML-powered no-code development platform. Its second product, the Ready To Go Applications, provides a plug-and-play experience for its users.
Profet AI’s products are suitable for deployment on-premises and public cloud. Once the user has developed an AI model using the Virtual Data Scientist Platform, which can be within a cloud, they can deploy the model to PCs connected to the manufacturer’s system. The startup also offers a Restful API to help manufacturers integrate with external systems.
Darwin Ventures led Profet AI’s most recent funding round. Other participants in the Series A funding included Hive Ventures, Harbinger Venture Capital and Jensen-Capital Management. Profet AI has devised an expansion plan and will use the new fund to execute it.
As of 2022, Profet AI served more than 100 manufacturers across different industries in Taiwan. The company said its revenues had doubled last year due to the business growth.
Founder and CEO Jerry Huang said its domestic success had increased the company’s confidence to expand to other regions. Its expansion will start in Japan, China and select countries in Southeast Asia.
“We will be looking at establishing joint ventures with strong partners in overseas markets to ensure the right product/market fit for each location, and we look forward to supporting more companies in leveraging the power of machine learning in the coming year,” Huang added.
