Advantages
AI/ML-enabled IIoT-powered predictive maintenance platform
Feature Selection for Data Pre-Processing System
Real-time Alerts
AI/ML Model-based Approach
Who We Are
At EQUIPai, we are transforming the manufacturing industry by shifting from costly reactive maintenance to efficient predictive maintenance. Our cloud-based platform harnesses the power of Machine Learning, AI, IIoT, and Big Data to autonomously forecast machine faults and minimize downtime without manual intervention. By connecting to existing assets, we enable real-time monitoring, provide alerts for abnormal conditions, and generate crucial insights through advanced data analysis tools. Our mission is to enhance asset utilization, reduce capital costs, and streamline operations, ultimately transforming how manufacturers maintain their equipment and ensuring consistent, high-quality output.
Vision
To make industrial operations more agile and resilient through an integrated digital platform that helps increase the monitoring of equipment health and maintenance through real-time data monitoring and streamlined decision-making processes.
Mission
To assist industrial professionals with smart tools, enabling them to gain insights from connected and real-time data sources to accurately optimize and maintain equipment and prevent downtime.
Problems To Solve
Our Solution
EQUIPai provides an IoT-powered predictive maintenance platform that accurately forecasts equipment failures by autonomously organizing data and generating alerts. Our machine learning model, which learns from historical data, automates failure detection and recommendations without the complexity of deep learning models. The platform delivers real-time alerts for operational deviations, eliminating the need for manual SCADA systems and enhancing task automation, thus improving decision-making and reducing production costs.
Our Product
AI/ML-enabled IIoT-powered Predictive Maintenance Platform
The company has developed an automated and efficient IIoT-powered predictive maintenance platform that predicts maintenance needs and potential failures, improves overall manufacturing efficiency, optimizes production, and predicts demand. The platform has acted as a tool that companies can use to extend the life of their equipment while preventing unanticipated downtime by utilizing more advanced maintenance services and solutions and getting closer to the data for real-time edge processing. Additionally, the platform has made use of AI & ML and Big Data capabilities to enable root cause investigation and failure prediction, bringing about customer happiness. The technology has enabled greater product efficiency and maintenance cost optimization through continuous real-time monitoring.
Target Market
Manufacturers
Supply Chain Operators
Original Equipment Manufacturers
Testimonials
Meet The Team
Xiaodong Sheng
Chief Executive Officer
Mr. Xiaodong Sheng has over 25 years of experience and holds a master’s in Project Management from the University of Management and Technology and a college degree in Mechanical Engineering from the University of Shanghai for Science and Technology. His career includes roles such as Sales Manager, Vice President, and General Manager at various companies, and also as a CEO/Shareholder. As Chief Executive Officer Mr. Sheng will use his extensive experience and strategic vision to drive innovation and growth in the predictive maintenance industry in Canada.
Yan Gong
Chief Commercial Officer
Mrs. Yan Gong has over 20 years of experience and a bachelor’s degree in Sociology & International Trade from Jiangnan University. She began her career as an Underwriting Office Manager where she excelled in administrative management and policy formulation. As Chief Commercial Officer she will lead commercial strategy and execution, focusing on market analysis, partnership development, and strategic marketing to establish the company in Canada’s predictive maintenance sector.
Ying Huang
Chief Finance Officer
Mrs. Ying Huang brings 15 years of experience in financial strategy, investment analysis, and market research. With a master’s in business from the University of Newcastle and a college degree in Secretarial Studies from Guangzhou University, she has held key roles as a Sales Planner, Bidding Project Manager, Head of Resort Project Operations & Director of the Finance Department and an Individual Investor. As Chief Financial Officer she will manage financial strategy, planning, and risk, leveraging her extensive experience to drive the company’s success in Canada’s predictive maintenance sector.
Xiaorong Zou
Chief Administrative Officer
Mrs. Xiaorong Zou has over 30 years in educational management and international exchange. She holds a master’s in Leadership and Management in Education from the University of Newcastle and a bachelor’s in English Education from Anhui Anging Normal University. Her career includes roles at Hefei Normal University and the Anhui Provincial Department of Education, focusing on international relations and project management. As Chief Administrative Officer Mrs. Zou will utilize her expertise to oversee administrative functions, streamline operations, and enhance inter-departmental communication.