Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into Industry 4.0. This time, you get to discover five hand-picked machine learning startups impacting Industry 4.0.
Out of 486, the Global Startup Heat Map highlights 5 Top Machine Learning Startups impacting Industry 4.0
The insights of this data-driven analysis are derived from the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering 2 093 000+ startups & scaleups globally. The platform gives you an exhaustive overview of emerging technologies & relevant startups within a specific field in just a few clicks.
The Global Startup Heat Map below reveals the distribution of the 486 exemplary startups & scaleups we analyzed for this research. Further, it highlights five Industry 4.0 startups that we hand-picked based on criteria such as founding year, location, funding raised, and more. You get to explore the solutions of these five startups & scaleups in this report. For insights on the other 481 machine learning solutions for Industry 4.0, get in touch with us.
Rejig Digital provides Predictive Analytics
Founding Year: 2020
Location: Ahmedabad, India
Use this solution for Industrial Data Analysis
Indian Startup Rejig Digital builds custom industrial machine learning (ML) solutions to advance the fourth industrial revolution. The startup’s Data Analytics solution leverages big data and ML algorithms to analyze data collected from the business’ enterprise resource planning (ERP) software, industrial sensors, and connected devices. The Data Analytics solution provides real-time predictive analytics to address industrial concerns such as cost overruns, equipment maintenance, and production efficiency. The startup’s solution enables cost savings for data-driven industries such as electronics, manufacturing, energy, utilities, and financial services.
Siali Tech advances Process Optimization
Founding Year: 2018
Location: Santander, Spain
Partner for Process Automation
Spanish startup Siali Tech advances end-to-end process optimization using computer vision and deep learning. The startup’s deep learning platform Inspector learns visual tasks in any industrial environment and provides actionable improvement insights to bring efficiency. Inspector enables inventory control, product anomaly detection, equipment, and workforce monitoring, as well as optimizes packing and logistics processes. The startup customizes its platform capabilities for industries such as manufacturing, food, automotive, construction, consumer electronics, and logistics.
Nexocraft enables Predictive Maintenance
Founding Year: 2016
Location: Bonn, Germany
Reach out for Equipment Health Evaluation
German startup Nexocraft develops Graphicx.io, an ML-powered web platform for industrial equipment health evaluation and predictive maintenance. Graphicx.io’s Visualization and Evaluation tool monitors industrial equipment and provides Industrial Health Scoring by learning the optimal running conditions of all systems. It aggregates all connected sensor data and automatically evaluates changes in operating levels by comparing them with the past data. Businesses select ML models specific to performance indicators relevant to their industrial processes, as well as reduce machine downtime by using Nexocraft’s solutions.
mSense facilitates Fault Detection
Founding Year: 2018
Location: Milpitas, US
Innovate with mSense for Quality Management
US-based startup mSense develops an in-process verification platform for continuous process and product improvement in industrial operations. The startup’s ASDL platform uses acoustics, vibration, and vision ML algorithms and industrial internet of things (IIoT) sensors to determine and improve defects in equipment and parts. The platform enables real-time on-site fault detection, reduces data load on the cloud, and is ready to be deployed using pre-developed hardware. ASDL platform provides application-specific AcousticDL, TactileDL, and VisionDL modules that empower manufacturing and logistical capabilities of healthcare, automotive, utility, and insurance industries.
Tignis accelerates Process Simulations
Founding Year: 2017
Location: Seattle, US
Use for Technical Process Optimization
US-based startup Tignis provides PAICe Maker, a physics-driven advanced AI and ML software solution. It simulates different manufacturing scenarios by selecting various control parameters for designing and optimizing industrial parts and operations. The platform employs AI algorithms on the edge to control process parameters and reduce feedback latency in the manufacturing process. PAICe Maker enables process engineers and manufacturers to continuously improve physical assets and processes across multiple industries. Further, it reduces the time to run multiple simulations and increases quality and plant output using real data.
Discover more Industry 4.0 Startups
Industry 4.0 startups such as the examples highlighted in this report focus on condition monitoring, quality inspection, and preventive analytics. While all of these technologies play a major role in advancing the industry, they only represent the tip of the iceberg. To explore industrial technologies in more detail, simply let us look into your areas of interest. For a more general overview, download our free Industry 4.0 Innovation Report to save your time and improve strategic decision-making.
