Overview
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QBurst |
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Australia | |
2004 | |
Private | |
$10-100m | |
201 - 1,000 | |
Open website |
IoT Snapshot
Technology Stack
Case Studies
Number of Case Studies6
AI-Based Robot Calibration
The client was in the process of developing a smart table tennis robot that can be controlled by a mobile app. The app can be used by players to configure or choose from a list of pre-programmed drills. The robot plays the drills and programs as per user configuration; however, performance reduces over time due to aspects such as the wear and tear of machine parts. Additionally, faulty installation, errors in table dimensions, and alignment changes caused during shipping impact accuracy.QBurst was tasked with improving firmware performance. The project would focus on enhancements to the calibration mechanism of robots leading to improved gameplay and user satisfaction. The client wanted the calibration mechanism to be easy to use and repeatable. |
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Web Portal Development for a Security Solutions Company
The client, a security service provider, required a web portal that could manage different user roles and integrate with Customer Premise Equipment (CPE) to manage various services. The portal was expected to offer service desk functionalities and integrate with third-party systems for implementing SMS functionality. The client's customers are organizations that have one or more CPEs and avail different services from the client. The client's business solution is a combination of hardware and software components providing security services and the ability to manage service configurations. The service subscription and service delivery of all office security service-related reports/analysis is controlled from the client’s cloud infrastructure. |
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RPA Solution for Shipment Tracking: A Case Study
The client, a leading service provider to the international engineering industry, was facing significant challenges in tracking and managing the status of shipments. The existing legacy systems and manual processes were cumbersome, time-consuming, and prone to errors, leading to inaccuracies and productivity losses. The client required a solution that could improve visibility, efficiency, quality of service, and profitability by tracking the lifecycle of shipments. The need was for a solution that could provide real-time tracking of worldwide shipment details, and could be maintained within the SharePoint environment for reporting and analytics. |
Similar Suppliers
Number of Similar Suppliers4
Altizon Systems
Altizon empowers Industrial Digital Revolutions globally by helping enterprises use Machine Data to drive business decisions. With a global footprint of over 100 enterprise users, Altizon is a leading Industrial IoT platform provider as recognized by Gartner, Forrester, BCG, Frost & Sullivan, and others. |
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Altair
Altair is a leading provider of enterprise-class engineering software enabling innovation, reduced development times, and lower costs through the entire product lifecycle from concept design to in-service operation. Our simulation-driven approach to innovation is powered by our integrated suite of software which optimizes design performance across multiple disciplines encompassing structures, motion, fluids, thermal management, electromagnetics, system modeling and embedded systems, while also providing data analytics and true-to-life visualization and rendering. |
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Petasense
Petasense is an Industrial Internet of Things startup based in Silicon Valley. They make learning wireless sensors that connect to the cloud to democratize Predictive Maintenance for industrial customers. The vision of the company is to connect, collect and predict for the industrial world to improve operational efficiency and reduce costs. |
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DataRobot
DataRobot offers a Machine Learning platform for data scientists of all skill levels to build and deploy accurate predictive models in a fraction of the time it used to take. The technology addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics.The DataRobot platform uses massively parallel processing to train and evaluate 1000's of models in R, Python, Spark MLlib, H2O and other open-source libraries. It searches through millions of possible combinations of algorithms, pre-processing steps, features, transformations, and tuning parameters to deliver the best models for your dataset and prediction target. The DataRobot platform evaluates hundreds of cutting-edge Machine Learning algorithms to discover, deploy, and customize the best Machine Learning models for every situation. It also delivers the most accurate insights at scale, providing the fastest path to Data Science success for organizations of all sizes. DataRobot was founded in June 2012 and is headquartered in Boston, Massachusetts, USA. |