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What is Satim?

Satim delivers a remarkable AI-powered software solution that excels in identifying, categorizing, and recognizing objects by utilizing Synthetic Aperture Radar (SAR) satellite imagery. The firm has created an advanced simulator that can produce synthetic SAR signatures, allowing for the generation of signatures for any object and any SAR system. This groundbreaking simulator enables us to introduce various new object types for training our AI models, achieving impressive classification accuracy rates of 90% within just a few days. Thanks to our innovative SAR data simulator, the models can swiftly adapt to recognize and classify newly emerging objects, providing essential flexibility to tackle the ever-evolving challenges encountered by military, government, and commercial sectors. Our collaborations with leading SAR sensor manufacturers help us combine state-of-the-art technology with unparalleled expertise in the field. Moreover, our vast international network of partners is committed to driving progress in the space and defense sectors, ensuring that we stay ahead of the curve in innovation. By working together, we aspire to continuously redefine the possibilities within object detection and classification, ultimately enhancing operational effectiveness and safety across various industries. This collaborative effort reinforces our mission to lead the charge in advancing cutting-edge solutions for the future.

What is AlphaEarth Foundations?

AlphaEarth Foundations, an advanced AI model launched by DeepMind, operates as a "virtual satellite" by integrating a wide array of Earth observation data, including optical and radar imagery, 3D laser mapping, and climate simulations, into a cohesive and compact embedding for every 10x10 meter segment of land and coastal areas. This state-of-the-art method enables rapid, on-demand mapping of global landscapes while significantly minimizing storage needs compared to previous systems. By combining diverse data sources, it effectively tackles the challenges of data overload and inconsistencies, resulting in summaries that are 16 times more compact than those produced by conventional approaches, while also achieving an impressive 24% reduction in errors for various tasks, even when faced with limited labeled data. The embeddings, compiled annually, are released as the Satellite Embedding dataset on Google Earth Engine, and they have already been leveraged by numerous organizations to identify previously uncharted ecosystems and to track agricultural and environmental changes, demonstrating the real-world utility of this innovative technology. Furthermore, this model not only deepens our comprehension of Earth's intricate dynamics but also sets the stage for upcoming improvements in environmental oversight and conservation initiatives, highlighting its transformative potential in the field.

Media

Media

Integrations Supported

AlphaCode
Gemini
Gemini Enterprise
Google Earth Engine

Integrations Supported

AlphaCode
Gemini
Gemini Enterprise
Google Earth Engine

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Satim

Date Founded

2012

Company Location

Poland

Company Website

satim.co

Company Facts

Organization Name

Google DeepMind

Date Founded

2010

Company Location

United States

Company Website

deepmind.google/discover/blog/alphaearth-foundations-helps-map-our-planet-in-unprecedented-detail/

Categories and Features

Categories and Features

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