Ximilar
Ximilar is a visual AI solution designed to cater to the needs of businesses across various industries. It offers tools for image recognition and visual search,...
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What is Ximilar?
Ximilar is a visual AI platform providing ready-to-use and custom image recognition, visual search, and processing solutions via REST API for businesses and developers. It enables automating image tagging, similarity search, object detection, and enhancement without coding, using a no-code app to build, test, and deploy models. Key features include pre-built solutions for fashion tagging, home decor classification, stock photo search, collectibles recognition like sports and trading cards, background removal, image upscaling, OCR, and modular flows combining multiple AI tools. It serves e-commerce sites for product recommendations, stock photo agencies for similarity matching, real estate for room classification, collectibles platforms for card grading, and any app needing visual insights. The platform processes billions of images securely in the EU under GDPR, with clients worldwide reporting increased click rates and workflow efficiency.
Ximilar pricing
Pricing model: Freemium
Monthly subscription plans with API credits optimized to traffic and needs; free sign-up to test App and upload images; paid plans include credit supply for recognition calls, with option to add extra packs; use credit calculator for estimation; upgrades and pre-trained model improvements at no extra cost.
Ximilar pros
- Ready-to-use fashion tagging and search
- Home decor and furniture detection
- Stock photo similarity search
- Collectibles recognition for cards and stamps
- Sports and TCG card grading
- No-code model building platform
- Custom AI tailored to specific data
- Modular flows combining multiple models
- REST API with Python, PHP, cURL support
- Image annotation for teams
- Background removal tool
- Image upscaling up to 8x
- OCR for text extraction
- GDPR compliant EU data storage
- Does not store processed images
- Ownership of trained models
- High-speed processing under 100ms
- Handles millions of images in collections
Ximilar cons
- Requires API credits for usage
- Monthly subscription model
- Custom solutions need consultation
- Limited to supported formats like JPG PNG
- GIF processes only first frame
- No on-premises by default
- Training data storage on their servers
- Admin access to data when needed
- Credit packs for traffic spikes
Frequently asked questions about Ximilar
How does image recognition work?
Image recognition uses convolutional neural networks to extract features from images and map them to categories, attributes, or numerical values learned from labelled training examples. Related tasks like OCR extract text, while localisation models identify and classify multiple regions in a single pass. Off-the-shelf solutions cover stock photos, home decor, fashion, and collectibles, with custom models trainable via the no-code platform and accessible via REST API.
What is Visual Search?
Visual search analyzes overall visual aesthetic or detected objects independent of metadata, understanding subjective similarity for relevant results like exact matches or similar items. It powers product recommendations, reverse image search, and image matching in e-commerce, fashion, and more, with examples like Search Fashion by Photo.
Which collectibles can AI Recognition of Collectibles recognize?
Detects stamps, coins, banknotes, comic books, trading cards, antique items with bounding boxes; identifies TCG like Pokémon, MTG, Yu-Gi-Oh!, sports cards for baseball, basketball etc., with features like signatures; recognizes over 1 million comic books by name, title, publisher, issue; customizable taxonomy.
How Ximilar streamlines image processing tasks and reduces costs?
Automates tagging, sorting, analysis to cut manual labor; uses pre-trained and new models efficiently; bills via API credits with customizable monthly plans and extra packs; continuous upgrades to models at no extra cost; optimizes for 24/7 content addition without metadata staff.
What are the typical Visual Search applications?
Includes search by photo from user-generated content, similarity for e-commerce recommendations, product matching to eliminate duplicates; used in industrial, research, security; detects multiple products per image for individual similarity like in Fashion or Home Decor Search.
Is Ximilar’s visual AI able to handle large datasets and complex images?
Handles millions to over 100 million images, processing each once during sync without storage, searches in hundreds of ms; processes complex multi-object images detecting fashion or homeware individually; custom training scales with dataset size from tens for simple to thousands for complex tasks.
How does Ximilar approach privacy and data protection issues?
Doesn’t store processed images, only agreed training data on EU S3 with time-links; shared IP rights to models, no use for others; GDPR compliant, ISO-certified Prague data center; NDAs available, customizable access, on-premises for large projects.
Which types of images and formats does Ximilar support?
Supports jpg, jpeg, png, webp, heic, bmp, tiff, jfif via _base64 or _url; GIF processes first frame only; contact for customizations; data export for sync in various formats.
How fast and efficient is the image recognition process?
Processes images in 5-100 ms depending on resolution and CDN; cached models eliminate cold-starts; optimized for high-throughput on dedicated hardware; asynchronous requests for scale.
Does Ximilar store my images?
Processed images are analyzed once and discarded, not stored; training datasets stored securely only if agreed, with time-limited access; full privacy focus under GDPR.