Dataeaze Systems

Dataeaze Systems successfully completed a project for a marketing strategy company. The task involved building a data crawler to extract information from various portals and generate insights from the raw data using AI libraries. The team used Python for the data crawling activity and MongoDB for storing the data. They also utilized UML tools to extract information and intelligence from the data. The project, which began in November 2019 and ended in June 2020, cost around $40,000. The client was satisfied with the team's strong technical expertise and their ability to adapt to working with a small to medium-sized company.

In another project, Dataeaze Systems was hired by a software analytics and automation firm to operationalize data processing functions during AI model building. The team, which consisted of 2-5 employees, developed data management activities including data versioning, cloud-based storage of heterogeneous datasets, and data automation. The client found Dataeaze Systems through a referral and selected them due to their recommendation. Communication was mainly through virtual meetings.

Dataeaze Systems also worked with a multinational system integration based in Japan. The project involved creating a data analytics and visualization system using AI and distributed computing tools. The goal was to seamlessly integrate AI technologies and automate most of the tasks. The team used technologies such as Ansible, Docker, Apache Spark, Apache Hadoop, Delta Lake, and MLflow, and the project involved everything from requirement gathering to development. The client chose Dataeaze Systems for their past experiences and willingness to try new things. The team consisted of 3 engineers and 2 senior executives.