Customer clarity
Users get a clearer path from question to decision.
AI personal shopper
Build an AI Shopping Assistant That Helps Customers Buy
Create a catalogue-aware shopping experience that understands what customers need, compares relevant options and explains why a product fits — without forcing shoppers through a filter maze.
Outcome
From product overload to confident purchase decisions.
Guide product discovery with catalogue-aware recommendations, comparisons and buying confidence. The product is designed around a specific decision journey, not a generic chatbot pattern.
Business handoff
Intent, context and next steps connect to your workflow.
Trust controls
Boundaries, logs and human escalation are designed from the start.
From browse to buy
A shopper says what they need. The assistant turns it into the right basket.
No technical map, no confusing filter maze. The experience feels like a helpful store expert who asks the right questions, compares options and moves the customer toward checkout.
They describe the moment
Budget, style, size, use case or gift goal: the shopper can speak naturally instead of guessing filters.
The store narrows the choice
Products are matched to real needs, stock and rules, so the customer sees a small useful set.
They understand the pick
Clear reasons, comparisons and bundles help the customer feel confident before buying.
The next step is ready
Add to cart, save, ask support or complete a bundle. The handoff is part of the flow.
Working underneathCatalogue matchingBundle rulesMerchant controlsConversion analytics
Trust & Control Layer
Useful AI with visible boundaries.
Every Lumethica solution includes a practical trust layer: transparent reasons, approved claims, inventory awareness, fallbacks for missing data, support handoff, recommendation logs.
Delivery model
From product sprint to MVP and optimization.
Product Sprint
Map the decision journey, UX flow, AI behavior and trust boundaries.
MVP Build
Build the assistant, knowledge layer, handoff and measurement loop.
Optimization
Improve prompts, flows, analytics, content and business outcomes.
Related solutions
Explore adjacent AI product patterns.
AI Customer ConciergeGuide customers through complex products, plans and services with explainable recommendations.AI Finance & Insurance CompanionHelp customers understand financial products, policy documents, risk scenarios and next steps.AI Health & Wellness NavigatorGive patients and members a safer way to organize, understand and prepare health-related information.
AI Customer Concierge
AI Finance & Insurance Companion
AI Health & Wellness NavigatorBeyond ecommerce search
Search finds products. A shopping assistant helps customers decide.
Filters and search work well when a shopper knows the category or specification. A shopping assistant can begin with intent, ask a useful clarifying question, narrow the catalogue to a small relevant set, compare tradeoffs and explain the fit. The next action can be a PDP, add-to-cart, checkout path or a handoff to a person when the decision needs more support.
Built around your catalogue and commerce rules.
Catalogue-aware matching
Retrieve approved catalogue information, product attributes and pricing context. Check availability and compatibility before recommending a product.
Merchant control
Apply merchant rules, bundle relationships and permitted customer context. Keep inventory awareness and trust boundaries visible when information is incomplete.
Buying confidence and handoff
Explain recommendations, compare options and prepare the next action: add-to-cart, support or sales handoff with useful business context.
Works with the commerce stack you already have.
The architecture can connect to Shopify, commerce APIs, PIM, ERP, inventory services, product feeds, CRM and analytics. Scope access and data freshness around the shopping journey. Integration choices depend on your systems and available permissions; a product sprint can validate those assumptions before build.
Related
Explore related solutions.
FAQ
Common questions
How is an AI shopping assistant different from search?
Search retrieves products matching a query. A shopping assistant can clarify intent, compare a small relevant set, explain the fit and help the customer take the next action.
Can it respect inventory and merchant rules?
Yes. Catalogue retrieval, availability checks, compatibility constraints and merchant rules can govern which products are eligible and how they are presented.
Can it connect to our existing commerce stack?
The architecture can connect to Shopify, APIs, PIM, ERP, product feeds and other approved systems. The integration scope is assessed against your data and permissions.