

Recomaze AI Agent
Turn Your Store Into An AI Sales Agent. Recomaze scans your catalog, fixes what AI and search can’t understand, and powers a conversational AI agent that helps shoppers find and buy the right products.
Cost / License
- Subscription
- Proprietary
Platforms
- Online
- BigCommerce
- Shopify
- Software as a Service (SaaS)
- Wordpress




Recomaze AI Agent
Features
Tags
- conversational-ecommerce
- E-commerce
- conversion-optimization
- ai-e-commerce
- product-content-optimization
- agentic-commerce
Recomaze AI Agent News & Activities
Recent activities
Recomaze added Recomaze AI Agent as alternative to Nosto
Recomaze added Recomaze AI Agent as alternative to Algolia- Recomaze updated Recomaze AI Agent
- Recomaze updated Recomaze AI Agent
- Recomaze updated Recomaze AI Agent
- Recomaze updated Recomaze AI Agent
Recomaze AI Agent information
What is Recomaze AI Agent?
What Recomaze is
Recomaze turns an online store into an AI Sales Agent: AI Discoverability: Recomaze audits and upgrade product data so AI systems can correctly understand and recommend products On-site AI Concierge / Sales Agent: It is a shopper-facing assistant that answers product questions and guides shoppers to the right items using the store’s real catalog + policies Continuous monitoring: Recomaze keeps the catalog “AI-ready” as products and inventory change The problem Recomaze solves Stores lose sales because their catalog is not AI-readable: missing / inconsistent attributes and variants weak titles and descriptions for AI reasoning no structured Q&A knowledge (shipping, returns, sizing, materials, care) That causes wrong AI answers, weak product matching, and more drop-off. Partner-facing entry point (no plugin required) Recomaze provides an external AI Discoverability Audit that can be run for merchants: audit.recomaze.ai
In minutes it outputs an AI Readiness Score, key blockers, real examples of failures, and a prioritized fix plan. How Recomaze is different from similar tools Data-first, not chatbot-first: It fixes catalog structure so AI can be accurate (then the agent performs) Proof-driven: the audit shows concrete failures + what to fix first Operational at scale: bulk improvements + monitoring, not one-off “copy tweaks”
