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EdgeImpulse Inc.

Unclaimed
AI Platformswww.edgeimpulse.comSan Diego, California, United StatesUpdated

Edge Impulse provides an edge AI platform and ecosystem enabling developers to build, deploy, and scale machine learning on embedded devices.

Overview

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.

Mission statement

To empower developers and organizations to create intelligent edge solutions through an accessible, secure, end-to-end platform and partner network.

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What we offer

Edge Impulse platform

Accelerate the development and deployment of edge AI solutions with Edge Impulse platform.

edgeimpulse.com →

Who do we serve

IoT Product Teams And Edge AI Programs

Global product teams building edge AI devices for IoT and consumer electronics.

IoTConsumer ElectronicsEmbedded Systems

Geography: Global

How we help: A platform enabling end-to-end edge ML development for connected devices, reducing time-to-market and enabling scalable, secure deployments across hardware ecosystems.

OEM Partners And Hardware Manufacturers

Global OEMs integrating edge AI into devices.

Consumer ElectronicsIndustrialAutomotive

Geography: Global

How we help: End-to-end workflow for device manufacturers to deploy secure edge AI across product lines at scale.

Hardware Startups And Edge AI Innovators

Global hardware startups building edge-enabled devices.

TechnologyIoTConsumer Electronics

Geography: Global

How we help: Affordable, end-to-end edge ML tooling that enables rapid prototyping, testing, and deployment for hardware startups.

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.

Products: Edge Impulse platform

On-device computer vision

Capabilities to build, optimize, and run computer vision models on resource-constrained cameras and edge devices for real-time inference.

Products: Edge Impulse platform

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.

Products: Edge Impulse platform

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.

Products: Edge Impulse platform

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.

Products: Edge Impulse platform

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 Workflows
    Facilitate seamless model development and deployment through intuitive workflows designed for AI practitioners.
  • Access Diverse Algorithms
    Utilize various machine learning algorithms tailored for edge devices to enhance performance and capabilities.
  • Optimize for Resource Constraints
    Focus on efficient deployment techniques specifically designed for embedded engineers working with limited resources.
  • Prepare Data Effectively
    Streamline data preparation with advanced tools for optimal training and deployment of ML models.
  • Optimize Model Performance
    Enhance model performance and efficiency for edge deployment through robust optimization techniques.
  • Manage Sensor Data
    Easily manage sensor datasets to facilitate the training and deployment of machine learning models.
  • Integrate Seamlessly with Arduino
    Leverage Arduino integrations to build and deploy efficient edge applications effortlessly.
  • Empower OEM Integration
    Streamline the process for OEMs to develop and deliver edge AI solutions efficiently.
  • Implement Computer Vision
    Utilize state-of-the-art computer vision tools to deploy visual inspection and real-time analysis applications.
  • Leverage NVIDIA Hardware
    Integrate NVIDIA solutions for optimized performance in edge AI workloads.
  • Utilize Qualcomm Platforms
    Make use of Qualcomm technologies for enhanced performance and scalability in edge applications.

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