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Edge AI refers to the use of AI techniques embedded in IoT endpoints, gateways and edge servers, that can process and store data close to where it’s generated. While predominantly focused on AI inference, more sophisticated systems may include a local training capability to provide in-situ optimization of the AI models. This is done by constantly monitoring AI models and autoscaling them to match demands. Edge AI systems can reduce latency and data transport consumption, improve local processing capabilities thus find usage in applications ranging from autonomous vehicles to streaming analytics.
Edge Impulse, a Qualcomm company, is the trusted edge AI platform for developing edge AI solutions and deploying them to edge devices from vendors across the global hardware ecosystem. Our tools and technology enable developers and enterprise teams to streamline and accelerate the process of building, delivering, and optimizing embedded AI and machine learning solutions using real-world data.
Edge Impulse was acquired by Qualcomm Technologies Inc. as part of its ongoing strategic investment in IoT transformation and expansion of Qualcomm’s leadership in AI capabilities that power AI-enabled products and services across IoT. Edge Impulse customers have access to accelerated support and resources for key edge AI use cases on Qualcomm’s IoT hardware, and Qualcomm customers can seamlessly leverage Edge Impulse’s intuitive edge AI development workflows to help significantly accelerate deployment of AI in IoT solutions.
AWS Edge Services is a suite of software solutions that extend computing, storage, and networking capabilities closer to end users and devices. It enables processing of data at the edge of the network to reduce latency, improve performance, and enhance security for applications requiring real-time data analysis. The software supports content delivery, security enforcement, and connectivity for distributed applications across various industries. AWS Edge Services addresses business challenges such as optimizing application responsiveness, ensuring compliance with data residency requirements, and enabling seamless integration between cloud and on-premises environments. It is designed to support scalable and reliable operation in geographically dispersed locations.
NVIDIA EGX Platform is a software designed to enable real-time accelerated computing at the edge, supporting the deployment and management of AI workloads across various industries. The software utilizes GPU-optimized infrastructure to process and analyze data generated by sensors and devices locally, reducing latency and improving efficiency for applications such as machine learning, analytics, and autonomous systems. It offers integration with Kubernetes-based orchestration for scalable management of edge AI applications and allows enterprises to operate near real-time inference and analytics. By addressing the need for efficient edge computing, the software helps organizations streamline processes and gain actionable insights from data without relying on centralized cloud resources.
Edge AI Solutions is a software designed to enable artificial intelligence processing on edge devices, supporting real-time inferencing and analytics without dependence on cloud infrastructure. The software incorporates features such as computer vision, predictive maintenance, object detection, and sensor data processing for deployment across sectors like automotive, healthcare, media, and smart cities. It aims to solve business challenges related to latency, bandwidth usage, and data privacy by facilitating decision-making directly on local hardware. The software integrates with diverse device platforms and offers scalability for varying application needs, supporting seamless interoperability with existing systems and security options for enterprise environments.
LatentAI is a software designed to facilitate efficient deployment and optimization of artificial intelligence models for edge devices. The software provides tools for model compression, quantization, and adaptation, enabling neural networks to run with reduced resource requirements while maintaining accuracy. LatentAI software supports integration with existing workflows and offers compatibility with multiple hardware platforms, assisting organizations in simplifying the process of converting complex AI models into formats suitable for real-time inference at the edge. This software addresses the business problem of deploying AI solutions on resource-constrained devices by offering automated workflows, streamlined model packaging, and optimization capabilities for inference performance and scalability in distributed environments.
Advian Edge AI is a software designed to deploy artificial intelligence models on edge devices, enabling real-time data processing and analytics directly at the data source. The software facilitates various use cases such as predictive maintenance, quality control, and situational awareness by allowing AI models to operate independently of cloud or centralized computing resources. Advian Edge AI supports a range of edge environments, including sensors, cameras, and industrial equipment, and is used to optimize processes, improve operational efficiency, and reduce latency in data-driven decision making. The software includes tools for model training, deployment, and monitoring, and is compatible with existing IT and operational technology infrastructures.
Akira AI is a software designed to streamline knowledge management and information retrieval processes through the application of artificial intelligence. The software enables organizations to consolidate data from diverse sources, facilitating efficient document search and contextual understanding. Akira AI offers features such as natural language processing for querying, summarization tools that extract key insights from extensive content, and integration capabilities with commonly used enterprise platforms. The software supports teams in managing information overload, enhancing productivity by improving access to relevant data and reducing manual efforts in finding and understanding documentation. Akira AI addresses the challenge of transforming dispersed data into actionable knowledge within business environments.
Bosch Edge AI Services is a software that offers edge artificial intelligence capabilities for processing, analyzing, and managing data directly at the device or network edge. It is designed to support real-time decision-making by leveraging machine learning models deployed on edge devices. The software enables data-driven insights without reliance on centralized data centers, which can help organizations address challenges related to latency, bandwidth, privacy, and scalability. Bosch Edge AI Services is built to integrate with various hardware and software infrastructures, supporting applications such as predictive maintenance, visual inspection, and automation. It provides tools for model training, deployment, monitoring, and lifecycle management, facilitating operational efficiency and responsiveness in industrial and commercial environments.
ClearBlade IoT Edge Platform is a software that enables enterprises to manage, analyze, and act on data from connected devices at the edge of networks. The software provides features including device management, real time data processing, edge computing, and integration with existing enterprise systems. It supports secure communication, local analytics, and automation directly at deployment sites, reducing latency and supporting operational reliability. ClearBlade IoT Edge Platform addresses business challenges related to IoT deployment by offering tools for scalability, data orchestration, and remote monitoring, which help organizations optimize resource utilization and maintain efficient system performance.
Tredence Edge AI is a software designed to enable real-time analytics and artificial intelligence processing at the edge of networks, reducing latency and supporting on-site decision-making. The software integrates with various data sources and devices to process, analyze, and act on data locally rather than relying solely on centralized cloud infrastructure. It offers features such as data ingestion, model deployment, and management for AI and machine learning workloads, which can optimize operations across manufacturing, supply chain, and retail environments. The software aims to address business needs for faster insights, operational efficiencies, and enhanced automation by delivering intelligence closer to data generation points.
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