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Six Atomic
AI Solutions for Real-Time Fashion

What is Six Atomic?

Six Atomic leverages artificial intelligence to revolutionize the apparel industry's supply chain. Its technology facilitates the creation of unique garments tailored to individuals by utilizing AI for trend analysis, design proposal, and automated pattern creation and grading within seconds. The platform aims to make fashion manufacturing highly automated, flexible, and scalable, similar to modern cloud computing infrastructure.

By implementing Six Atomic's solutions, fashion brands can significantly reduce product-to-market times, keeping pace with real-time trends. The platform enables launching new products with substantially lower costs and risks, supporting personalization through modular design libraries and accurate body measurement prediction. This approach aims to fit 100% of the population, reduce returns due to poor fit, and eliminate inventory risks by enabling on-demand production immediately after a sale.

Features

  • AI Pattern Grading: Automatically grade patterns in seconds to standard sizes or custom fit based on body measurements.
  • Modular Design Libraries: Create millions of designs in minutes using pre-built modules (e.g., shirts, t-shirts).
  • AI Body Measurement Prediction (Inference): Accurately predict over 50 body measurements from height, weight, and optional body shape questions.
  • Customer Measurement Collection: Share online questionnaires to easily obtain customer measurements for custom fits.
  • Pattern Export: Export generated patterns to industry-standard formats like DXF (standard, AAMA, ASTM), PDF, and PLT.
  • Real-time Production Enablement: Technology designed to integrate with and support on-demand manufacturing workflows.

Use Cases

  • Accelerating fashion product design and launch cycles.
  • Implementing mass personalization for apparel.
  • Automating pattern grading for diverse size ranges.
  • Reducing costs associated with new product launches.
  • Enabling on-demand apparel manufacturing models.
  • Improving online fit accuracy and reducing returns.
  • Minimizing inventory risk for fashion businesses.
  • Streamlining the process of obtaining customer measurements for custom orders.

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