Lily AI
E-commerce personalization software
E-commerce software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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Large
- Retail and wholesale
- Accommodation and food services
- Arts, entertainment, and recreation
What is Lily AI
Lily AI is an AI-based product discovery and personalization platform for retail and e-commerce teams. It focuses on enriching product data with customer-friendly attributes (e.g., style, occasion, fit, and other descriptive signals) and using those attributes to improve site search, navigation, recommendations, and merchandising. The product is typically used by digital commerce, merchandising, and data teams to increase findability and relevance across catalogs, especially where product data is inconsistent or sparse.
Attribute enrichment for catalogs
Lily AI centers on generating and normalizing product attributes that are often missing from standard PIM or ERP data. This can improve consistency across large catalogs and reduce manual tagging work for merchandising teams. The enriched attributes can be used to power downstream experiences such as search filters, browse paths, and recommendation logic.
Improves on-site product discovery
The platform is designed to connect shopper intent to products using more descriptive, customer-oriented language than basic SKU metadata. This supports use cases like better search relevance, more meaningful facets, and improved navigation for long-tail queries. It is particularly relevant for retailers with complex assortments where shoppers search by use case or style rather than exact product names.
Merchandising-oriented personalization inputs
By producing structured signals (attributes and taxonomy) that merchandising teams can understand, the system can make personalization and recommendations easier to govern. This can help align automated ranking with business rules and category strategy. It also provides a foundation for consistent experiences across channels that rely on the same product understanding.
Not a full commerce platform
Lily AI addresses product understanding and personalization inputs rather than end-to-end e-commerce operations. Organizations still need separate systems for storefront, checkout, order management, and broader marketing automation. Buyers evaluating it as an all-in-one e-commerce suite may find functional gaps outside discovery and personalization.
Integration and data readiness effort
Value depends on connecting to product catalogs, feeds, and the systems that execute search, recommendations, and merchandising changes. Implementation typically requires data mapping, taxonomy alignment, and ongoing governance to keep attributes accurate as assortments change. Teams with limited data engineering or merchandising operations capacity may face longer time-to-value.
Best fit for retail verticals
The strongest use cases are in consumer retail categories where descriptive attributes (style, occasion, fit, material) drive discovery. Businesses with highly standardized catalogs or B2B parts-style data may see less incremental benefit. Some organizations may prefer simpler rule-based approaches if their catalog and search needs are straightforward.
Seller details
Lily AI, Inc.
Mountain View, CA, USA
2015
Private
https://www.lily.ai/
https://x.com/lily_ai
https://www.linkedin.com/company/lily-ai/
