The Edge AI Platform

Edge Impulse empowers ML teams to run AI at peak performance on any edge hardware, with unmatched ease and speed.

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# Quick integration for any Python script
import edgeimpulse as ei

# 1. Set API key from Edge Impulse project
ei.API_KEY = "ei_dae2..."
# 2. Profile model performance on target device
results = ei.model.profile(model="/path/to/model",
                            device="cortex-m4f-80mhz")
# 3. View profiling results
results.summary()
# 4. Optimize model and convert to C++ library
from ei.model.output_type import Classification
ei.model.deploy(model="/path/to/model",
                 model_output_type=Classification(),
                 output_directory="/library")

Integrate with your existing workflows and development tools

Native Python integrations with the Python SDK

Extensive Python and Node.js API bindings

NVIDIA Pretrained Models

Enterprise level Admin APIs available

AICPA SOC 2 Compliant

Edge Impulse adheres to the strictest security and privacy standards. Learn more about our security standards here.

Feature engineering for sensor data

Optimize for on-device performance

Anomaly detection

Leverage state-of-the-art anomaly detection algorithms and choose the method that best suits your data and application.

Uncover unexpected signals

Detect anomalies in all sensor modalities with models trained solely on normal data, capable of identifying suspicious signals and indicating when an anomaly is detected, directly on device.

Detect and filter anomalous inputs

Combine anomaly detection and classification models to increase the robustness of your algorithms and ensure that you are always able to detect and filter out unexpected data inputs.

Detect visual anomalies

Build optimized models to detect anomalies in highly dimensional data such as video and image data. Leverage state-of-the-art models built to run efficiently on device.

Object detection on microcontrollers

FOMO (Faster Objects More Objects) is a ground-breaking algorithm that brings real-time object detection, tracking and counting to microcontrollers for the first time. Count objects, find the location of objects in an image, and track multiple objects in real-time.