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Compression.ai
Compress images without compromising on quality or resolution using AI.

Compression.ai
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What is Compression.ai?

Compression.ai offers advanced image compression technology powered by machine learning (ML) and deep learning neural networks. Trained on millions of images, its algorithms intelligently assign different bitrates to various parts of an image, achieving superior compression compared to standard methods like JPEG. This approach adaptively compresses images, preserving original quality and resolution while significantly reducing file sizes.

Beyond standard JPEG and PNG compression, Compression.ai introduces its proprietary *.mlvx filetype, leveraging state-of-the-art ML for even greater compression rates, often below 1 bit-per-pixel. The platform's core technology is versatile, capable of compressing various spectral data types, including LIDAR and Radio Frequency bands. By reducing image sizes, Compression.ai helps speed up websites and applications, lowers storage and bandwidth costs, improves Search Engine Optimization (SEO) rankings, and ultimately increases conversions.

Features

  • AI-Powered Compression: Employs Machine Learning (ML) and neural networks for adaptive image compression.
  • Quality Preservation: Reduces file size without compromising visual quality or resolution.
  • Multiple Format Support: Compresses images to JPEG, PNG, and a proprietary ML-based format (*.mlvx).
  • Spectral Data Compression: Capable of compressing LIDAR and Radio Frequency band data.
  • Website Performance Boost: Speeds up websites and applications through smaller image files.
  • SEO Enhancement: Contributes to higher search engine rankings via faster page loads.
  • Cost Reduction: Lowers storage and bandwidth expenses.

Use Cases

  • Optimizing website images for faster load times.
  • Reducing bandwidth consumption for image delivery.
  • Lowering cloud storage costs for image assets.
  • Improving SEO performance through enhanced page speed.
  • Compressing technical spectral data (e.g., LIDAR) for efficient storage or transmission.
  • Enhancing user experience in applications with faster image loading.

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