Edge Impulse provides a platform for developing embedded machine learning models that run on various edge devices, including microcontrollers and gateways. This technology enables manufacturers to optimize sensor data processing, reduce bill of materials costs, and accelerate time to market for their products.
Funding
$54.4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Developing and deploying machine learning models on edge devices is challenging due to resource constraints, complex toolchains, and the need for specialized expertise. Optimizing sensor data processing, reducing bill of materials costs, and accelerating time to market for edge AI products requires a streamlined development platform.
Solution
Edge Impulse provides a comprehensive platform for developing and deploying embedded machine learning models on a variety of edge devices, from microcontrollers to gateways. The platform simplifies the process of building, deploying, and scaling embedded ML applications by offering tools for data ingestion, labeling, feature extraction, model training, and deployment. It enables developers to optimize sensor data processing, reduce BOM costs, and accelerate time to market for next-generation edge AI products and solutions.
Target Audience
The primary users are product leaders, AI practitioners, and embedded engineers looking to bring intelligence to edge devices across various industries, including manufacturing, operations, product development, and transportation.
Features
- End-to-end platform for data collection, labeling, feature extraction, model training, and deployment
- Support for a wide range of edge devices, including MCUs, NPUs, CPUs, GPUs, gateways, sensors, and cameras
- Tools for optimizing AI models for tiny devices, including the EON Tuner and EON Compiler
- Algorithms such as FOMO (Faster Objects, More Objects) and GMM Anomaly Detection
- Data Explorer for visualizing and analyzing sensor datasets
- Capability to generate synthetic datasets using GenAI
- Customizable performance settings to meet device constraints
- API access for integration with existing systems