Overview | |
Supplier Slogan | |
HQ Location | Israel |
Year Founded | 2016 |
Company Type | Private |
Stock Ticker | |
Revenue | < $10m |
Employees | 11 - 50 |
Website | Open website |
Company Description | Siraj was founded in 2016 by hi-tech entrepreneurs and academics who shared a vision to streamline the painstaking process of onboarding IIoT edge devices to cloud platforms leveraging AI/DL. Our proprietary deep learning algorithms automatically recognize and standardize data collected from diverse edge devices, creating a clean and unified Data Stream that brings IIoT to its full potential. With expertise in industrial edge onboarding, Siraj provides end to end services covering every phase in the onboarding process, from site mapping to complete site connectivity. Designed to increase industrial productivity and safety, our solutions focus on multiple interconnected layers including embedded, sensor data, network connectivity, IoT gateways design & implementation, and IoT platform interfaces. |
IoT Solutions | Our Automatic Connectivity Generator (ACG) leverages AI to extract meaningful time-series data from any incoming Data Stream, both previously observed and unobserved, comprising different data formats and communication protocols. The collected data is normalized into a unified format thereby enabling running advanced AI that automates the process efficiently and effectively. any cloud platform and application can seamlessly process and understand. Using Deep Learning, extracted data is automatically organized into a standard unified format suited for any destination, regardless of the original data format and categorized by source. Automatic recognition of time series data extracted from a variety of devices such as temperature, pressure, flow, level, vibration, ultrasonic, voltage, and more. |
Key Customers | NETAFIM, ICL, HAMLET, RAD, GE |
Subsidiary | |
Parent Company | |
IoT Snapshot | |
Technologies | |
Industries | |
Use Cases | |
Functions | |
Services | |
Technology Stack | |
Infrastructure as a Service (IaaS) | None |
Platform as a Service (PaaS) | None |
Application Infrastructure & Middleware | None |
Analytics & Modeling | None |
Functional Applications | None |
Cybersecurity & Privacy | None |
Networks & Connectivity | None |
Processors & Edge Intelligence | None |
Sensors | None |
Automation & Control | None |
Robots | None |
Drones | None |
Wearables | None |
Actuators | None |
Other | None |
Similar Suppliers | |
Similar Suppliers | |
Partners | |
Partners |
Overview | |
Supplier Slogan | |
HQ Location | Israel |
Year Founded | 2016 |
Company Type | Private |
Stock Ticker | |
Revenue | < $10m |
Employees | 11 - 50 |
Website | Open website |
Company Description | Siraj was founded in 2016 by hi-tech entrepreneurs and academics who shared a vision to streamline the painstaking process of onboarding IIoT edge devices to cloud platforms leveraging AI/DL. Our proprietary deep learning algorithms automatically recognize and standardize data collected from diverse edge devices, creating a clean and unified Data Stream that brings IIoT to its full potential. With expertise in industrial edge onboarding, Siraj provides end to end services covering every phase in the onboarding process, from site mapping to complete site connectivity. Designed to increase industrial productivity and safety, our solutions focus on multiple interconnected layers including embedded, sensor data, network connectivity, IoT gateways design & implementation, and IoT platform interfaces. |
IoT Solutions | Our Automatic Connectivity Generator (ACG) leverages AI to extract meaningful time-series data from any incoming Data Stream, both previously observed and unobserved, comprising different data formats and communication protocols. The collected data is normalized into a unified format thereby enabling running advanced AI that automates the process efficiently and effectively. any cloud platform and application can seamlessly process and understand. Using Deep Learning, extracted data is automatically organized into a standard unified format suited for any destination, regardless of the original data format and categorized by source. Automatic recognition of time series data extracted from a variety of devices such as temperature, pressure, flow, level, vibration, ultrasonic, voltage, and more. |
Key Customers | NETAFIM, ICL, HAMLET, RAD, GE |
Subsidiary | |
Parent Company | |
IoT Snapshot | |
Technologies | |
Industries | |
Use Cases | |
Functions | |
Services | |
Technology Stack | |
Infrastructure as a Service (IaaS) | None |
Platform as a Service (PaaS) | None |
Application Infrastructure & Middleware | None |
Analytics & Modeling | None |
Functional Applications | None |
Cybersecurity & Privacy | None |
Networks & Connectivity | None |
Processors & Edge Intelligence | None |
Sensors | None |
Automation & Control | None |
Robots | None |
Drones | None |
Wearables | None |
Actuators | None |
Other | None |
Similar Suppliers | |
Similar Suppliers | |
Partners | |
Partners |