πŸ—‚οΈ Navigation

Imagimob

End-to-End AI for the Intelligent Edge.

Visit Website β†’

Overview

Imagimob provides an end-to-end development platform for TinyML applications. The platform covers the entire ML lifecycle, from data collection and labeling to model development, optimization, and deployment on small, low-power microcontrollers. It is designed for creating production-grade AI solutions for wearables, industrial sensors, and other embedded systems.

✨ Key Features

  • End-to-end TinyML development workflow
  • Data collection and management tools
  • Graphical user interface for model building
  • Model optimization for embedded devices
  • Support for Arm Cortex-M microcontrollers

🎯 Key Differentiators

  • Focus on production-grade TinyML applications
  • Strong expertise in sensor data processing
  • End-to-end solution from data to deployed C-code

Unique Value: Provides a complete, end-to-end solution for developing and deploying production-ready machine learning on tiny, low-power edge devices.

🎯 Use Cases (4)

Wearable technology (gesture recognition, activity monitoring) Predictive maintenance (anomaly detection in sound and vibration) Audio and voice recognition Smart industrial sensors

βœ… Best For

  • Fall detection in personal safety devices
  • Gesture control for headphones
  • Predictive maintenance for industrial pumps

πŸ’‘ Check With Vendor

Verify these considerations match your specific requirements:

  • High-performance computer vision on powerful edge devices
  • Cloud-based AI applications

πŸ† Alternatives

Edge Impulse SensiML Neuton.AI

Offers a more focused and in-depth toolchain for professional embedded developers compared to more general-purpose platforms.

πŸ’» Platforms

Desktop

βœ… Offline Mode Available

πŸ”Œ Integrations

STMicroelectronics Renesas Syntiant

πŸ›Ÿ Support Options

  • βœ“ Email Support
  • βœ“ Dedicated Support (Enterprise tier)

πŸ”’ Compliance & Security

βœ“ GDPR

πŸ’° Pricing

Contact for pricing

βœ“ 14-day free trial

Visit Imagimob Website β†’