Ango Hub
Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality.
Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset.
Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.
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HiveMQ
The HiveMQ Platform provides a scalable, reliable data backbone with an event-driven MQTT architecture. Here are a few highlights:
1. MQTT Broker: At the heart of the HiveMQ platform is a fully MQTT-compliant broker purpose-built for fast, reliable, bi-directional data movement between IoT devices and enterprise systems.
2. Edge Data Integration: HiveMQ Edge seamlessly integrates edge data by converting industrial protocols into standardized MQTT, enabling an interoperable IIoT infrastructure.
3. IoT Streaming Governance: Data Hub transforms data in flight, passing only the most relevant, contextualized data to cloud and enterprise systems.
4. UNS & IT/OT convergence Enabler: Commonly used as the backbone for Unified Namespace architectures and seamlessly connects OT devices with IT systems for full visibility and interoperability.
5. Distributed Data Intelligence: HiveMQ Pulse unifies and contextualizes data across the enterprise for smarter decisions exactly where they matter most.
6. Maximum Interoperability: Runs anywhere on-premises or in public or private clouds. Efficiently connects to streaming applications, databases and data lakes with a Java SDK to build your own
7. Scalability to Support Growth: Elastic scaling with automatic data balancing and smart message distribution. Proven benchmark of up to 200M active clients with 1.8B messages/hour
8. Business Critical Reliability: Zero message loss with persistence to disk and offline queuing. No single point of failure due to masterless cluster architecture and zero downtime upgrades
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Eyeris
At Eyeris, we are motivated by a commitment to excellence and inspired by individuals from all walks of life, including the dedicated night-shift worker, the nurturing parent, and the ambitious entrepreneur. Our technology is designed with every driver in mind, aiming to ensure a safer and more improved driving experience for everyone. In-cabin cameras serve as the primary sensors for monitoring both drivers and passengers, while Eyeris AI Software intelligently analyzes the complete interior environment captured by these cameras. This system enhances the capability to gather data from various sensor types, ensuring high accuracy through redundant information. Ongoing advancements in hardware are enabling us to run sophisticated AI software more efficiently and at greater speeds. Our state-of-the-art vision-based neural networks deliver a comprehensive array of insights. By utilizing cutting-edge image sensors, our pre-trained vision AI models are equipped to comprehend the full in-cabin environment across a diverse spectrum of lighting conditions. As we continue to innovate, we strive to set new standards in safety and comfort for all road users.
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Embiot
Embiot®, a compact, high-performance IoT analytics software agent that can be used for smart sensor and IoT gateway applications, is available. This edge computing application can be integrated directly into devices, smart sensor and gateways but is powerful enough to calculate complex analytics using large amounts of raw data at high speeds.
Embiot internally uses a stream processing model in order to process sensor data that arrives at different times and in different order. It is easy to use with its intuitive configuration language, rich in math, stats, and AI functions. This makes it quick and easy to solve any analytics problems.
Embiot supports many input methods, including MODBUS and MQTT, REST/XML and REST/JSON. Name/Value, CSV, and REST/XML are all supported. Embiot can send output reports to multiple destinations simultaneously in REST, custom text and MQTT formats. Embiot supports TLS on select input streams, HTTP, and MQTT authentication for security.
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