Overview | ||||||
| Supplier Slogan | ||||||
| HQ Location | United States | United States | United States | United States | United States | India |
| Year Founded | 2015 | 1986 | 2017 | 2015 | 2007 | 2015 |
| Company Type | Private | Private | Private | Private | Private | Private |
| Stock Ticker | ||||||
| Revenue | < $10m | < $10m | < $10m | < $10m | $10-100m | < $10m |
| Employees | 11 - 50 | 11 - 50 | < 10 | 11 - 50 | 11 - 50 | < 10 |
| Website | Open website | Open website | Open website | Open website | Open website | Open website |
| Company Description | Instrumental is building software that enables assembly lines to autonomously operate, learn, and adapt parts and processes - saving billions of dollars in scrap and rework costs. Their customers use Instrumental to find and fix issues on their assembly lines, preventing development schedule slips and beginning production at higher yields. Their equipment and data service is deployed on multiple global assembly lines at top-tier manufacturers. Instrumental was founded by Anna-Katrina Shedletsky and Samuel Weiss, two former Apple engineers who, after spending hundreds of days in China on manufacturing lines, set out to revolutionize the manufacturing space. They are assembling a diverse team who sees inefficiencies as opportunities and want to develop a system that changes the manufacturing world for the better. | Develops Enterprise Asset Management (EAM) and Computerized Maintentance Management System/Software (CMMS) solutions | Buzz Solutions provides a software platform powered by Artificial Intelligence, Actionable Insights and Predictive Analytics for faults and Anomaly Detection for power line inspection process for power utilities. Our platform automates the process of storing and organizing visual data (captured in the field through drones and helicopters), analyzing for faults using our AI algorithms, mapping the data and providing heat maps as well as predictive insights for when, where and what kind of faults are happening on power line and assets. Using our solutions, power utilities save over 50% of cost and time to analyze data which makes condition based maintenance efforts easier and time efficient, thus, preventing wildfires, power outages and other climate change effects on the physical infrastructure of the grid. We are disrupting the electrical grid by making it much smarter and efficient using the power of AI and automation. | Relimetrics is a full stack computer vision and Machine Learning software providing audit-proof quality inspection and process control for Industry 4.0 Applications. We use real-time image processing and video analytics to automate and digitize visual inspections, making them easy, connected, and insightful. We are located in Sunnyvale, CA and Berlin, Germany. | SoftWear Automation is an Atlanta, Ga. based company with the sole focus of developing innovative core technologies and products for the apparel manufacturing and sewn products industries by harnessing its experience and expertise in machine vision, robotics, and computing. SoftWear expects its technology will lead the conversion of labor-intensive industries to ones that are capital intensive and economical. | CynLr is a visual object intelligence platform that enables industrial robotic arms to see, understand and manipulate any object in random unstructured environments |
| IoT Solutions | Streamline Development and Production
Our solution combines easy-to-deploy inspection stations with intelligent software that helps engineering and operations teams discover, fix, and monitor issues on the assembly line.
Typically deployed at EVT, Instrumental Dev is used by engineering teams to accelerate issue discovery, failure analysis, and corrective actions during the hardware development process.
Production is supposed to be "fixed" and "stable", but it's inherently not. Operators turn over, upstream vendors have quality shifts, whether we like it or not, production is a constant battle against quality regression. Instrumental MP is used by operations and manufacturing teams to save rework costs, prevent quality escapes, and accelerate responses to line down or field failure analysis. | Proteus CMMS
Cloud-hosted Next-Gen Computerized Maintenance management solution, offering all the features of a traditional solution, Preventive Maintenance scheduling, work orders and asset management combined with latest digital trends as Enterprise Resource Planning (ERP), Artificial Intelligence Integration, and IoT system connectivity. | We provide an AI platform for power line inspections. Our software optimizes transmission line inspections and prevents power cuts through Artificial Intelligence and Predictive Analytics. We make inspections faster, safer, and more cost-effective.
| Quality Audit Module
Automates and digitizes visual inspections in-line, creating full Traceability of quality in all stages of production. Integrates with existing infrastructure on the factory floor and enhances existing QA solutions with advanced Machine Learning.
Training Module
Allows customers with complex and diversified portfolio of products to develop in-house models, extending their detection capabilities to new parts and configurations. The models developed can be integrated with Quality Audit Module.
Process Control Module
Closes the loop in production by correlating machine and process data with digitized quality data. Integrates with SCADA and MES systems and can directly alert the system operator on how to change production parameters to bring quality back into spec. | The LOWRY SEWBOT is built to produce numerous types of sewn products in different industries and supports both local and global supply chains. It has been commercially deployedin the automated production of rugs, bath mats, automotive products, medical products, pillows, towels and more.
The LOWRY has the ability to produce a variety of products regardless of the size, shape or material it is. Designed with a modular base frame, the LOWRY is fully configurable and adaptable to your unique product specifications and process. | 3D Bin-Picking solutions available in the market perform basic pattern-matching algorithms on sparse 3D depth-map data. Therefore they work only when object geometries are simple, with no occlusion or entanglement, with atleast one part fully visible in the viewing angle trained for, and can only approximately pick and drop objects.
The purpose of picking an object during a manual task is almost always to place in a desired orientation, hence approximate picks and drops finds very limited use-cases. |
| Key Customers | Chicago Airport | - | - | - | ||
| Subsidiary | ||||||
| Parent Company | ||||||
IoT Snapshot | ||||||
| Technologies | Functional ApplicationsSensors | Analytics & Modeling | Automation & Control | Analytics & Modeling | Analytics & ModelingRobots | |
| Industries | AutomotiveCities & MunicipalitiesEducationFood & BeverageHealthcare & HospitalsPharmaceuticalsRetail | AerospaceAutomotiveConstruction & InfrastructureElectronicsPlastics | Apparel | |||
| Use Cases | Computer VisionVisual Quality Detection | Machine Condition MonitoringVisual Quality DetectionChatbotsEnergy Management System | Predictive Quality AnalyticsVisual Quality DetectionTrack & Trace of Assets | Visual Quality DetectionProcess Control & Optimization | Computer VisionCollaborative Robotics | Computer Vision |
| Functions | Facility ManagementProcess Manufacturing | |||||
| Services | ||||||
Technology Stack | ||||||
| Infrastructure as a Service (IaaS) | None | None | None | None | None | None |
| Platform as a Service (PaaS) | None | None | None | None | None | None |
| Application Infrastructure & Middleware | None | None | None | None | None | None |
| Analytics & Modeling | None | None | Moderate | None | Minor | Minor |
| Functional Applications | None | Minor | None | None | None | None |
| Cybersecurity & Privacy | None | None | None | None | None | None |
| Networks & Connectivity | None | None | None | None | None | None |
| Processors & Edge Intelligence | None | None | None | None | None | None |
| Sensors | None | Minor | None | None | None | None |
| Automation & Control | None | None | None | Minor | None | None |
| Robots | None | None | None | None | None | Minor |
| Drones | None | None | None | None | None | None |
| Wearables | None | None | None | None | None | None |
| Actuators | None | None | None | None | None | None |
| Other | None | None | None | None | None | None |
Similar Suppliers | ||||||
| Similar Suppliers | ||||||
Partners | ||||||
| Partners |
Overview | ||||||
| Supplier Slogan | ||||||
| HQ Location | United States | United States | United States | United States | United States | India |
| Year Founded | 2015 | 1986 | 2017 | 2015 | 2007 | 2015 |
| Company Type | Private | Private | Private | Private | Private | Private |
| Stock Ticker | ||||||
| Revenue | < $10m | < $10m | < $10m | < $10m | $10-100m | < $10m |
| Employees | 11 - 50 | 11 - 50 | < 10 | 11 - 50 | 11 - 50 | < 10 |
| Website | Open website | Open website | Open website | Open website | Open website | Open website |
| Company Description | Instrumental is building software that enables assembly lines to autonomously operate, learn, and adapt parts and processes - saving billions of dollars in scrap and rework costs. Their customers use Instrumental to find and fix issues on their assembly lines, preventing development schedule slips and beginning production at higher yields. Their equipment and data service is deployed on multiple global assembly lines at top-tier manufacturers. Instrumental was founded by Anna-Katrina Shedletsky and Samuel Weiss, two former Apple engineers who, after spending hundreds of days in China on manufacturing lines, set out to revolutionize the manufacturing space. They are assembling a diverse team who sees inefficiencies as opportunities and want to develop a system that changes the manufacturing world for the better. | Develops Enterprise Asset Management (EAM) and Computerized Maintentance Management System/Software (CMMS) solutions | Buzz Solutions provides a software platform powered by Artificial Intelligence, Actionable Insights and Predictive Analytics for faults and Anomaly Detection for power line inspection process for power utilities. Our platform automates the process of storing and organizing visual data (captured in the field through drones and helicopters), analyzing for faults using our AI algorithms, mapping the data and providing heat maps as well as predictive insights for when, where and what kind of faults are happening on power line and assets. Using our solutions, power utilities save over 50% of cost and time to analyze data which makes condition based maintenance efforts easier and time efficient, thus, preventing wildfires, power outages and other climate change effects on the physical infrastructure of the grid. We are disrupting the electrical grid by making it much smarter and efficient using the power of AI and automation. | Relimetrics is a full stack computer vision and Machine Learning software providing audit-proof quality inspection and process control for Industry 4.0 Applications. We use real-time image processing and video analytics to automate and digitize visual inspections, making them easy, connected, and insightful. We are located in Sunnyvale, CA and Berlin, Germany. | SoftWear Automation is an Atlanta, Ga. based company with the sole focus of developing innovative core technologies and products for the apparel manufacturing and sewn products industries by harnessing its experience and expertise in machine vision, robotics, and computing. SoftWear expects its technology will lead the conversion of labor-intensive industries to ones that are capital intensive and economical. | CynLr is a visual object intelligence platform that enables industrial robotic arms to see, understand and manipulate any object in random unstructured environments |
| IoT Solutions | Streamline Development and Production
Our solution combines easy-to-deploy inspection stations with intelligent software that helps engineering and operations teams discover, fix, and monitor issues on the assembly line.
Typically deployed at EVT, Instrumental Dev is used by engineering teams to accelerate issue discovery, failure analysis, and corrective actions during the hardware development process.
Production is supposed to be "fixed" and "stable", but it's inherently not. Operators turn over, upstream vendors have quality shifts, whether we like it or not, production is a constant battle against quality regression. Instrumental MP is used by operations and manufacturing teams to save rework costs, prevent quality escapes, and accelerate responses to line down or field failure analysis. | Proteus CMMS
Cloud-hosted Next-Gen Computerized Maintenance management solution, offering all the features of a traditional solution, Preventive Maintenance scheduling, work orders and asset management combined with latest digital trends as Enterprise Resource Planning (ERP), Artificial Intelligence Integration, and IoT system connectivity. | We provide an AI platform for power line inspections. Our software optimizes transmission line inspections and prevents power cuts through Artificial Intelligence and Predictive Analytics. We make inspections faster, safer, and more cost-effective.
| Quality Audit Module
Automates and digitizes visual inspections in-line, creating full Traceability of quality in all stages of production. Integrates with existing infrastructure on the factory floor and enhances existing QA solutions with advanced Machine Learning.
Training Module
Allows customers with complex and diversified portfolio of products to develop in-house models, extending their detection capabilities to new parts and configurations. The models developed can be integrated with Quality Audit Module.
Process Control Module
Closes the loop in production by correlating machine and process data with digitized quality data. Integrates with SCADA and MES systems and can directly alert the system operator on how to change production parameters to bring quality back into spec. | The LOWRY SEWBOT is built to produce numerous types of sewn products in different industries and supports both local and global supply chains. It has been commercially deployedin the automated production of rugs, bath mats, automotive products, medical products, pillows, towels and more.
The LOWRY has the ability to produce a variety of products regardless of the size, shape or material it is. Designed with a modular base frame, the LOWRY is fully configurable and adaptable to your unique product specifications and process. | 3D Bin-Picking solutions available in the market perform basic pattern-matching algorithms on sparse 3D depth-map data. Therefore they work only when object geometries are simple, with no occlusion or entanglement, with atleast one part fully visible in the viewing angle trained for, and can only approximately pick and drop objects.
The purpose of picking an object during a manual task is almost always to place in a desired orientation, hence approximate picks and drops finds very limited use-cases. |
| Key Customers | Chicago Airport | - | - | - | ||
| Subsidiary | ||||||
| Parent Company | ||||||
IoT Snapshot | ||||||
| Technologies | Functional ApplicationsSensors | Analytics & Modeling | Automation & Control | Analytics & Modeling | Analytics & ModelingRobots | |
| Industries | AutomotiveCities & MunicipalitiesEducationFood & BeverageHealthcare & HospitalsPharmaceuticalsRetail | AerospaceAutomotiveConstruction & InfrastructureElectronicsPlastics | Apparel | |||
| Use Cases | Computer VisionVisual Quality Detection | Machine Condition MonitoringVisual Quality DetectionChatbotsEnergy Management System | Predictive Quality AnalyticsVisual Quality DetectionTrack & Trace of Assets | Visual Quality DetectionProcess Control & Optimization | Computer VisionCollaborative Robotics | Computer Vision |
| Functions | Facility ManagementProcess Manufacturing | |||||
| Services | ||||||
Technology Stack | ||||||
| Infrastructure as a Service (IaaS) | None | None | None | None | None | None |
| Platform as a Service (PaaS) | None | None | None | None | None | None |
| Application Infrastructure & Middleware | None | None | None | None | None | None |
| Analytics & Modeling | None | None | Moderate | None | Minor | Minor |
| Functional Applications | None | Minor | None | None | None | None |
| Cybersecurity & Privacy | None | None | None | None | None | None |
| Networks & Connectivity | None | None | None | None | None | None |
| Processors & Edge Intelligence | None | None | None | None | None | None |
| Sensors | None | Minor | None | None | None | None |
| Automation & Control | None | None | None | Minor | None | None |
| Robots | None | None | None | None | None | Minor |
| Drones | None | None | None | None | None | None |
| Wearables | None | None | None | None | None | None |
| Actuators | None | None | None | None | None | None |
| Other | None | None | None | None | None | None |
Similar Suppliers | ||||||
| Similar Suppliers | ||||||
Partners | ||||||
| Partners |