Direct answer
What is Lily AI?
Lily AI (Lily Max) is an enterprise product intelligence platform that enriches e-commerce catalog attributes and schema to maximize performance across paid ads, onsite search, and AI discovery engines.
Lily AI operates as an agentic product intelligence engine designed to bridge the gap between raw catalog data and the machine-readable requirements of modern commerce surfaces. Running under the Lily Max engine, the system deploys goal-based AI agents to audit product detail pages and existing product feeds, identifying missing attributes, thin copy, and gaps in search relevance. The platform enriches product titles, consumer descriptions, facet attributes, and schema markup without requiring retailers to overhaul their existing catalog stack or feed management software. Lily AI enriches feeds for multi-channel distribution, supporting Google Shopping, Meta Advantage+ catalog ads, onsite search systems, and conversational AI surfaces such as Gemini and ChatGPT. To substantiate performance claims, the platform incorporates matched-spend A/B testing and holdout analysis to benchmark incremental revenue and return on ad spend against un-enriched controls before scaling changes across the entire catalog.
Unlike standard feed management tools that merely syndicate existing data, Lily AI enriches catalog attributes with consumer-intent language and validates lift using controlled, matched-spend A/B experiments.
Product capabilities
Key features
Agentic PDP & Feed Enrichment
Audits product detail pages and catalog feeds to enrich missing attributes, conversational terms, and structured schema markup.
Google Shopping Optimization
Injects high-demand search phrases into titles and descriptions to lift impression share and product visibility in Google Merchant Center.
Meta Catalog Ad Copy
Generates ad-ready, quality-checked copy variants tailored for Meta Advantage+ placements and dynamic product retargeting.
AI Discovery & Agentic Payload
Structures product metadata into schema-validated payloads that conversational shopping assistants and LLMs can parse and recommend.
Matched-Spend A/B Testing
Runs controlled experiments with holdout groups to quantify incremental revenue and ROAS changes against un-enriched feeds.
Item Setup & Classification
Automates category mapping and structured attribute population for new products introduced into the catalog.
Practical fit
Who should use Lily AI?
Paid Advertising Lift
Enriching Google Merchant Center and Meta feeds with granular attributes to capture high-intent long-tail traffic and lift ROAS.
AI Engine Discoverability
Formatting product feeds into machine-readable data structures so shopping agents and answer engines cite and display products.
Onsite Search Expansion
Enhancing storefront search filters and descriptive attributes to lower zero-search-result queries and increase conversion.
Editorial assessment
Pros and limitations
Where it is strong
- Integrates alongside existing feed managers and commerce stacks without replatforming.
- Validates attribute performance through matched-spend A/B testing and holdout groups.
- Provides a free feed audit and a 30-day pilot for up to 500 catalog items.
- Enriches data specifically for answer engines and AI-mediated shopping surfaces.
Where to be careful
- Does not publish public pricing tiers, requiring a scoped sales engagement.
- Provides little utility for small retailers with low SKU counts and minimal ad spend.
- Does not guarantee absolute placement or citations inside third-party LLM tools.
Commercial context
Lily AI pricing
As of September 2026, Lily AI does not publish fixed rate cards. Pricing is scoped by catalog size (SKU count), use-case complexity, and active geographic markets. A free feed audit and 30-day pilot for up to 500 products are offered to evaluate performance lift.
Pricing, limits, taxes, model access, and regional availability can change. Verify the purchase-critical details on the official pricing page linked under Sources.
Transparent ranking
Why Lily AI scores 74.7
Each factor is scored on a 100-point scale, then combined using the public ToolsRank weights. Engagement and momentum stay at a neutral baseline until measured signals exist, so no tool can gain or lose position from numbers nobody recorded.
Compatibility
Languages, platforms, and integrations
Languages
- English
Platforms
- Web
Integrations & surfaces
- Google Ads
- Google Merchant Center
- Meta Ads
- Amazon
Community
Reviews and questions
No approved member reviews yet. Editorial factors above are the only rating on this page.
Reviews and questions come from Google-signed members and are checked by an editor before they appear.
Frequently asked
Lily AI FAQ
Does Lily AI replace my existing catalog management or feed distribution tools?+
No. Lily AI optimizes and enriches the product intelligence distributed by existing feed managers and commerce systems, meaning no platform migration is required.
How does Lily AI validate performance improvements?+
Lily AI measures impact using matched-spend A/B tests, holdout groups, and difference-in-differences analysis to isolate lift against a baseline control before widespread deployment.
Does Lily AI guarantee ranking on AI platforms like ChatGPT and Gemini?+
No. The system makes products legible to AI agents by optimizing feeds, schema, and bot-facing content, but it does not guarantee specific placement, citations, or rankings.
What is included in a pilot or trial?+
Prospective clients can run a free 30-day trial on 500 catalog products, during which the system audits catalog data gaps and evaluates where enrichment creates measurable performance lift.
