Before shipping a product, manufacturing facilities or factories add value to raw materials through unit operations. Now, this procedure needs to adhere to a recipe. For items like cars, several instructions include a list of parameter values, a specified temperature for melting iron, a specific pressure for casting molds, and so on.
These factories, for instance, those in the automobile industry, do all in-line and end-of-line quality inspections to ensure the cars are in good shape; if not, they are trashed or modified, costing the factories capacity and labor. These manufacturers also rely on software to assess their experiences, modify parameters as necessary, and guarantee that the car reaches the end of the line as high quality as possible because even the employees engaged in keeping these processes in check might make mistakes.
The South African company DataProphet claims to offer software for artificial intelligence (AI) as a service to the industrial industry. In order to prevent manufacturing the flaws that force manufacturers’ products to be destroyed or redone, the company offers prescriptive guidance and suggests improvements to manufacturers’ recipes. According to the business, its lead artificial intelligence product, PRESCRIBE, has helped clients have a significant and valuable influence on the manufacturing floor, lowering the cost of non-quality by an average of 40%.
Manufacturers can supposedly employ DataProphet at various stages of their digitization processes; the collection and centralization of data are essential to get them going. DataProphet’s CONNECT, the first product in its stack, claims to enable manufacturers to upgrade their data infrastructure and move data from where it has been used for compliance in the manufacturing sector to a point where it can be optimized. The company presently ingests around 100 million unique data points on its platform daily. PRESCRIBE can use this information to advise decisions that will decrease flaws, waste, or subpar procedures and increase manufacturing yield.
The chief executive further noted that, in contrast to competing companies, DataProphet does not rely on its customers to have personnel skilled in data science, which defeats the objective of offering an AI-as-a-service platform that thrives on managing data infrastructure itself. The 50-person team primarily works with clients in the automotive, semiconductor, rubber, and foundry industries, deploying its solution to factories in South Africa, the United States, Japan, China, and India.
According to Cronje, DataProphet takes a hands-on approach, regularly monitoring data streams and pushing recommendations and comments to the operational floor to ensure that its customers implement them. Additionally, the business interacts with customers to understand their problems in situations where they don’t heed the advice DataProphet offers.
Recently, the startup revealed that it raised $10 million in the Series A funding round. The funding would give DataProphet the resources it needs to continue making improvements to its industrial AI product suite while enabling focused expansion in particular manufacturing industries and geographical areas. In addition to the Americas, Europe, and Asia, the company’s customer base has grown, and with new capital, its expansion is expected to be much faster.
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Amreen Bawa is a consulting intern at MarktechPost. Along with pursuing BA Hons in Social Sciences from Panjab University, Chandigarh, she is also a keen learner and writer, having special interest in the application and scope of artificial intelligence in various facets of life.