Lily AI
Lily AI / lily.ai
AI product intelligence platform that enriches retail product data with consumer-language attributes, improving search relevance, recommendation accuracy, and conversion for fashion, home, and beauty retailers.
Pricing
Free
Free plan
No
Category
Marketing
Platforms
2
Free plan
No
API access
No
Open source
No
Platforms
2
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What is Lily AI?
Lily AI is a retail AI company that specialises in product data enrichment — using computer vision and natural language AI to tag retail products with the consumer-language attributes that shoppers actually use when searching, rather than the supplier-language attributes that product data often contains.
The core insight is that there's a mismatch between how retailers tag products (supplier-centric, brand-specific language) and how shoppers search for them (consumer-centric, emotion and occasion language). A dress tagged as 'midi length floral print' may be searched as 'spring wedding guest dress' — Lily AI bridges this gap by enriching product data with consumer-language attributes.
Computer vision analyses product images to extract detailed visual attributes — colour palette, pattern, silhouette, material texture, styling details — at scale across large product catalogues that manual tagging cannot cover comprehensively. These visual attributes feed into search and recommendation systems.
Consumer attribute enrichment adds occasion, mood, lifestyle, and consumer-language attributes beyond visual features — 'business casual', 'resort wear', 'gift for mum', 'under $100' — that match actual shopper intent language in search queries and browsing behaviour.
The downstream impact is measured in search relevance (more products returned for consumer-language queries), recommendation accuracy (better complementary and similar product matching), and conversion rates from product detail pages with richer attribute information.
Key customers include Express, Bloomingdale's, and ThredUp, validating across both new and resale fashion retail.
How Lily AI works
Lily AI runs as computer vision software built around image and text workflows. Users typically start with a prompt, upload, or connected data source, and the underlying model handles the heavy lifting before returning a result you can refine or export. It's available on web and api.
Watch Lily AI in action
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What makes it worth shortlisting
The capabilities that matter most for teams evaluating Lily AI.
Consumer-language enrichment
Adds occasion, mood, and lifestyle attributes using the language shoppers search in, bridging the gap between supplier product tagging and consumer search intent.
Computer vision at scale
Extracts detailed visual attributes from product images across large catalogues eliminating manual tagging bottleneck for comprehensive product attribute coverage.
Search relevance improvement
Consumer-language attributes improve search result relevance for shopper-intent queries that standard product data attributes do not match, increasing search-to-purchase conversion.
Best use cases
Who should use it
Pros
- Consumer-language attribute enrichment directly addresses the gap between supplier tagging and shopper search language
- Computer vision at scale eliminates the manual tagging bottleneck for large catalogues
- Express, Bloomingdale's, and ThredUp references validate across traditional and resale fashion
- Occasion and lifestyle tags match shopper intent language that standard attribute tagging misses
Cons
- Enterprise-only pricing and retail specialisation limits market to mid-size and large retailers
- Value measurement requires connecting enrichment to search and conversion metrics — requires analytics maturity
- Resale and unique-item catalogues change too frequently for enrichment ROI to accumulate
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Is it worth the price?
Enterprise licensing to retailers. Contact for pricing. 30-day pilot available.
Model
Enterprise
Starting price
Free
Free trial
Yes
Tools like Lily AI
Constructor.io (covered) provides AI search and recommendations using enriched product data. Nosto (covered, rank 426) provides personalisation using product signals. Syte.ai (covered, rank 427) provides visual search. Searchspring provides retail search with attribute filtering.
Lily AI vs Constructor.io AI
A side-by-side look at the closest alternative in this category.
Lily AI
Lily AI
Constructor.io AI
Constructor
Enterprise licensing to retailers. Contact for pricing. 30-day pilot available.
Enterprise only. Custom pricing based on query volume. No public pricing. 30-day free trial.
SOC 2 Type II. GDPR compliant. Retail product data handling agreements.
SOC 2 Type II. ISO 27001. GDPR compliant. CCPA compliant. Enterprise data handling agreements.
Review Lily AI's data handling policy. Product images and data processed on Lily's infrastructure under enterprise agreements.
Review Constructor's data handling policy. Shopper behavioural data and transaction history processed on Constructor's infrastructure under enterprise agreements.
- Consumer-language attribute enrichment directly addresses the gap between supplier tagging and shopper search language
- Computer vision at scale eliminates the manual tagging bottleneck for large catalogues
- Express, Bloomingdale's, and ThredUp references validate across traditional and resale fashion
- Occasion and lifestyle tags match shopper intent language that standard attribute tagging misses
- Individual shopper personalisation trained on the retailer's own transaction data produces relevant-for-your-store results
- Self-learning models improve continuously with each new transaction without manual retraining
- API-first architecture integrates into any e-commerce platform without storefront limitations
- Sephora, Ulta, and Petco references validate for major retail-scale deployments
- Enterprise-only pricing and retail specialisation limits market to mid-size and large retailers
- Value measurement requires connecting enrichment to search and conversion metrics — requires analytics maturity
- Resale and unique-item catalogues change too frequently for enrichment ROI to accumulate
- Enterprise-only pricing — not accessible for small or mid-market e-commerce
- Effectiveness requires sufficient transaction volume for personalisation models to train on
- Implementation requires engineering resources for API integration and platform configuration
Technical & deployment info
Key facts about model providers, platforms, and team support.
Model Provider
Lily AI
Platforms
Web, API
Deployment
SaaS, API
Integrations
Shopify, Salesforce Commerce, SAP, Magento, API
Team Collaboration
No
Launch Year
2022
Security & privacy
Compliance signals and data-handling notes as reported by the vendor.
SOC 2 Type II. GDPR compliant. Retail product data handling agreements.
Review Lily AI's data handling policy. Product images and data processed on Lily's infrastructure under enterprise agreements.
What users are saying
Verified reviews from signed-in users, stored in the backend and averaged into this tool's rating.
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Common questions about Lily AI
Editorial Verdict
Should you use Lily AI?
Lily AI is the best product intelligence platform for fashion, home, and beauty retailers who want to enrich product catalogues with consumer-language attributes for improved search relevance and recommendation accuracy.
Last verified July 24, 2026.