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We are a team of data experts with a vision of improving manufacturing systems by providing customer specific database for the training of the AI system at their end. With our team’s expertise in data science and data analytics, we structure a redundant system and closely monitor the data acquisition processes in accordance with the requirements of the customer. We deliver ready-to-use, robust data sets that contribute to the goal of building an AI-based manufacturing application. With our solution, end customers can take their manufacturing facilities to the next level of industry.


INDAAQ (acronym for Industrial Data Acquisition) provides an industry database for manufacturing / analysis companies to accelerate the process of AI implementation in industry. This involves creating data on a parallel system at a different location. A parallel system is the reproduction of a process of one machine on another machine using non-proprietary parameters, with the goal of collecting machine and tool behavior data. This generated data is stored in a secure database, processed and sold as data sets for multiple AI implementations (by training in ML algorithms).


The use of the datasets produced by INDAAQ will eliminate the time, cost and effort of data collection, data processing and data maintenance for its customers, as most customers do not have the necessary know-how, sensors and machine resources.  INDAAQ creates datasets for the training of the ML algorithms as well as DL applications of the customers. The solution removes the need for companies involved in AI data research to collect data. As a result, time is saved on data implementation. By implementing a parallel physical system, the disruption to current machine function is reduced.


Customers using INDAAQ's services can focus on implementing intelligent systems while saving time and money by providing the data sets. INDAAQ estimates an 8% saving in cost and 20% in time to implement intelligent systems.