EdgeImpulse Inc. Unclaimed
San Diego, California, United States
Edge Impulse provides an edge AI platform and ecosystem enabling developers to build, deploy, and scale machine learning on embedded devices.
Edge Impulse provides an edge AI platform and ecosystem that enables developers, product teams, and organizations to build, train, deploy, and manage machine learning-enabled solutions on embedded and edge devices. It serves a broad audience across industries such as IoT and consumer electronics, offering end-to-end capabilities for data collection, model development, optimization, and deployment, along with a network of partners and resources to accelerate edge AI adoption. The company emphasizes accessibility, security, and scalability, aiming to empower customers to bring intelligent, connected devices to market quickly and reliably.
To empower developers and organizations to create intelligent edge solutions through an accessible, secure, end-to-end platform and partner network.
What we offer
Edge Impulse platform
Accelerate the development and deployment of edge AI solutions with Edge Impulse platform.
www.edgeimpulse.com/productWho do we serve
IoT Product Teams And Edge AI Programs
Global product teams building edge AI devices for IoT and consumer electronics.
OEM Partners And Hardware Manufacturers
Global OEMs integrating edge AI into devices.
Hardware Startups And Edge AI Innovators
Global hardware startups building edge-enabled devices.
Market segments
Edge ML development platforms
End-to-end platforms that enable data collection, feature engineering, model training, and deployment of machine learning models to embedded and edge devices.
On-device computer vision
Capabilities to build, optimize, and run computer vision models on resource-constrained cameras and edge devices for real-time inference.
Model optimization for constrained devices
Techniques and tooling for model quantization, pruning, and runtime optimization to meet latency, memory, and power constraints on embedded hardware.
Sensor data acquisition and management for edge ML
Capabilities for capturing, labeling, and managing sensor datasets (audio, IMU, image, environmental) to train and validate reliable on-device models.
OEM device enablement and hardware integration
Integrations and workflows that help OEMs and embedded engineers integrate ML models with hardware platforms (Arduino, NVIDIA, Qualcomm) and ship production devices.
More information about our offering
Edge Impulse platform
Edge Impulse platform is an end-to-end edge AI platform that enables developers to collect data, train, optimize, and deploy machine learning models to embedded and edge devices. It provides sensor datasets, feature engineering, model optimization, and a library of algorithms with computer vision capabilities, designed for product leaders, AI practitioners, embedded engineers, and OEMs. The platform supports production-grade workflows and integrations with hardware ecosystems to accelerate edge AI adoption.
- End-to-End WorkflowsFacilitate seamless model development and deployment through intuitive workflows designed for AI practitioners.
- Access Diverse AlgorithmsUtilize various machine learning algorithms tailored for edge devices to enhance performance and capabilities.
- Optimize for Resource ConstraintsFocus on efficient deployment techniques specifically designed for embedded engineers working with limited resources.
- Prepare Data EffectivelyStreamline data preparation with advanced tools for optimal training and deployment of ML models.
- Optimize Model PerformanceEnhance model performance and efficiency for edge deployment through robust optimization techniques.
- Manage Sensor DataEasily manage sensor datasets to facilitate the training and deployment of machine learning models.
- Integrate Seamlessly with ArduinoLeverage Arduino integrations to build and deploy efficient edge applications effortlessly.
- Empower OEM IntegrationStreamline the process for OEMs to develop and deliver edge AI solutions efficiently.
- Implement Computer VisionUtilize state-of-the-art computer vision tools to deploy visual inspection and real-time analysis applications.
- Leverage NVIDIA HardwareIntegrate NVIDIA solutions for optimized performance in edge AI workloads.
- Utilize Qualcomm PlatformsMake use of Qualcomm technologies for enhanced performance and scalability in edge applications.