Give a gift of sight to your online commerce
Delight your customers with search capabilities and recommendations that can see and understand fashion, style and decor. Let shoppers find products they’re looking for in a snap - even the things they can’t name. Convert your lifestyle images into showrooms. Take control of your products’ metadata. The opportunities are limitless with AI-powered image recognition.
They snap it. They find it. They buy it
Hard to describe it? No problem! Let your customers just point and shoot the things they like to instantly find them in your catalog, along with products of a similar style and design.
Our bespoke AI models that power the visual search technology capabilities work across fashion, furniture, dinnerware, fine art, home decor and many other domains.
Find a needle in a haystack
Need to find exactly the right thing among thousands that are similar?
Whenever you’re building a fast product reorder system, or part recognition system, our visual search AI models can distinguish the most subtle features and find exactly what the customer is looking for.
Capture every sale with “more like this“ recommendations
Sometimes the right dress doesn’t come in the right size, or the otherwise perfect armchair has that annoying cushion... So when searching for exactly the right product, customers often want to explore and compare similar products.
With “more like this” recommendations, your customers can easily find similar products with respect to fashion or artistic style. Customers can even look for “dress with similar hem” or “a vase with similar pattern” to focus on product-specific features.
Convert your lifestyle images into showrooms
Find and tag your products within lifestyle, runway, magazine, and social media pins and influencer images. Allow your customers to seamlessly move from browsing to shopping.
Your customers deserve rich and accurate product attributes. Your curators deserve great tools
Richly attributed catalog data makes the search and browsing experience of your customers magical.
However, how often do you see miss-attributed products? Or products with key attributes missing?
Verify and enrich your catalog with hundreds of style, fashion, and decor tags and attributes. Our image recognition algorithms can automatically tag products and verify existing attributes based on product images. Improve the productivity of your curators with AI assistance.
Our clients
How our visual search technology works
Find similar images by similar vectors
Visual search AI models represent or “embed” images with their “fingerprints” - series of numbers called vectors that capture the most essential features of an image. Those fingerprint vectors are created in such a way that similar images have similar fingerprints and are geometrically clustered together. This embedding trick allows the search engine to quickly find similar images by their vector representation.
Full-fledged image recognition pipelines
Our computer vision models perform all tasks required for successful visual search - from object detection, to segmentation, to vector representation and vector search of the target image.
Best tools for the job
Our visual search technology utilizes the most recent advancements in computer vision powered by deep learning algorithms. We custom-select, modify, ensemble, train, and fine-tune state-of-the-art visual models for a particular task.
Collect and organize domain specific data
We train our models on all available data related to the task - both customer-specific and publicly available. We perform data cleaning and labeling using advanced unsupervised and semi-supervised techniques to build large scale datasets to achieve the best search results.
Accelerate implementation with our visual search blueprint
- Accurate results - up to 98 percent item identification accuracy.
- Advanced similarity - the AI model takes into account fashion, decor, and artistic style.
- High throughput - battle-tested architecture handling thousands of parallel searches.
- Low latency - low latency with optimized vectorizers and fast approximate nearest neighbor search.
- Highly scalable and robust - share-nothing microservices architecture ensures high scalability and resilience.
- Integrations - data consumption from message queues, databases, or file dumps and REST APIs ensure seamless integration with the rest of the ecosystem.
- Infrastructure -AWS, GCP, or Microsoft Azure are supported. On-prem solution is available as well.
- Deep learning: A choice ofTensorFlow or Pytorch
- Vector/ANN index: Milvus or Elasticsearch, as well as embedded implementations
- Data platform: A choice of Apache Spark, Apache Flink, or Apache Beam are the primary choices along with their cloud wrappers.
- Feature store: Feast is one option, yet many non-specialized databases and EDW solutions will work
- Infrastructure -AWS, GCP, or Microsoft Azure are supported. On-prem solution is available as well.
- Deep learning: A choice ofTensorFlow or Pytorch
- Vector/ANN index: Milvus or Elasticsearch, as well as embedded implementations
- Data platform: A choice of Apache Spark, Apache Flink, or Apache Beam are the primary choices along with their cloud wrappers.
- Feature store: Feast is one option, yet many non-specialized databases and EDW solutions will work
Read more about our visual search case studies
Get started with visual search
More Search solutions
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