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value | image_bytes unknown | file_size_bytes int64 35k 10.2M |
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1.fig | 1.fig | .fig | "ZmlnLWtpd2kKAAAA5CMAALV8fYAkSVVnRlZVf0zPzH5/sCAiIiKi7i7L7oKIZH115XRVZW1mVffMuFJUV2V15059UZnVM70iArc(...TRUNCATED) | 1,977,093 |
2.fig | 2.fig | .fig | "ZmlnLWtpd2kPAAAAdiYAALV8aZxkWVXnuy8it8qq6n2hQURERETtbhpoEJEXW8arjK3fi8isaluCyIwXmY+KjXgRWV0tIpuK7Ju(...TRUNCATED) | 376,093 |
3.fig | 3.fig | .fig | "ZmlnLWtpd2kEAAAAZiAAALV8fYAkSVVnRlb11/R87SfLioiIiIg6uyy7CyKS9dWV01WVtZlV3TMjUmR3ZXXnTlVlUVnVM70i6h7(...TRUNCATED) | 5,120,524 |
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InfoBay.AI Figma Design Dataset
Overview
The InfoBay.AI Figma Design Dataset is a comprehensive collection of more than 4000+ figma design assets. The collection has been prepared for Artificial Intelligence, Machine Learning, Computer Vision, Design Automation, Multimodal Foundation Models, Enterprise Search, Retrieval Systems, UI/UX Research, and Generative AI applications.
To improve storage efficiency, enable streaming, and simplify large-scale distribution, all original files have been serialized into Apache Parquet while preserving their original filenames, directory structures, file extensions, and binary contents. The original assets can be reconstructed exactly from the provided Parquet files.
This dataset serves as a valuable resource for researchers, enterprises, and developers building next-generation creative AI systems.
Dataset Statistics
| Catalogue | Asset Type | Total Assets |
|---|---|---|
| Figma Dataset Catalogue | FIG | 4,781 |
Total Assets
4,781 Figma Design Assets
Figma Dataset Catalogue
Native Figma interface projects covering modern UI/UX workflows.
Key Categories
- UI Kits
- Design Systems
- Mobile Applications
- Websites
- Landing Pages
- FigJam Boards
- Icons
- Illustrations
Primary Applications
- UI Generation
- UX Research
- Layout Understanding
- Interface Generation
- Marketing Automation
- Component Detection
Storage Format
The original assets have been converted into Apache Parquet.
Each record preserves the complete binary representation of the original file.
Typical schema:
| Column | Description |
|---|---|
| relative_path | Original relative path |
| filename | Original filename |
| extension | Original file extension |
| size | Original file size (bytes) |
| content | Binary file content |
The original directory structure and files can be restored programmatically from the Parquet dataset.
AI & Machine Learning Applications
This dataset is suitable for:
- Large Multimodal Models (LMMs)
- Vision Language Models (VLMs)
- Computer Vision
- Retrieval-Augmented Generation (RAG)
- UI Understanding
- Layout Detection
- Design Similarity Search
- Vector Retrieval
- Image Embeddings
- Design Recommendation Systems
- Frontend Code Generation
- Creative AI
- 3D Foundation Models
- CAD Understanding
- Design Quality Assessment
- Human-Computer Interaction Research
- Digital Asset Retrieval
Enterprise Applications
- Product Design
- UI / UX Design
- Design Automation
- Creative Asset Management
- Enterprise Search
- Marketing Automation
- Knowledge Management
- Search Engines
- Visual Recommendation Systems
- Brand Asset Management
- Digital Twin Platforms
- AI-assisted Content Creation
Citation
If you use this dataset in research, publications, or commercial products, please cite:
@dataset{infobay_design_assets_2026,
title = {InfoBay.AI Design Assets Dataset Collection},
author = {InfoBay.AI},
year = {2026},
publisher = {InfoBay.AI},
license = {CC BY 4.0}
}
Data Creation
Procured through formal agreements and generated in the ordinary course of business.
Considerations
This dataset is provided for research and educational purposes only. It contains only sample data. For access to the full dataset and enterprise licensing options, please visit our website InfoBay.AI or contact us directly.
-Ph: +91 9236398619
-Email: datareq@infobay.ai
Acknowledgements
The InfoBay.AI Figma Design Dataset has been curated to support research and development in Artificial Intelligence, Computer Vision, Design Automation, Human-Computer Interaction, Multimodal Learning, Vision-Language Models, Generative AI, and Enterprise Software Systems.
We hope this collection accelerates innovation in the next generation of intelligent design technologies.
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