AI Product Advisor for your website
WebChatAgent learns your product catalog and advises visitors 24/7, with German primary hosting, a DPA and transparent data flows.
- Recommends only real products from your catalog
- Guided self-service instead of a long implementation project
- DPA and primary hosting in Germany
- From €19/month, free tier to test
- DPA & privacy controls
- Hosted in Germany
- Ready in a few steps
Turn questions into purchases
Most shoppers leave when they can't find the right product fast enough. A real AI product advisor asks the right questions, understands the need, and recommends the matching product from your catalog – not a generic chatbot guess. WebChatAgent reads your products, variants, availability and documents, then guides visitors to the right choice on your website, WhatsApp, and everywhere else.
Try it yourself
This is the inline widget, embedded right here on the page. It uses the current page as context — try asking "tell me about this feature".
Ask it, for example:
- „Tell me about this feature"
- „What does it cost?"
- „Does this work for my shop?"
Features
What makes it a real product advisor
Recommends real products only
The AI uses your catalog and documents as its basis. It recommends products you actually sell and stays with traceable details – accurate and brand-safe.
Trained on your catalog
Learns your products, variants, availability, prices and FAQs from your website, feed, PDFs and docs – automatically kept in sync.
More than advice
Advice, support, lead capture and appointment booking in one widget. The advisor also handles delivery, returns and availability questions.
Guided setup
Self-service setup: add your URL or feed, drop in the widget, done. No four-week onboarding project, no developer needed.
Connects to your shop
One-click for Shopify and WooCommerce; REST API, webhooks and CRM connectors for everything else.
Provides multilingual advice
Detects each visitor's language and recommends fluently – sell across borders without extra setup.
Use Cases
Where the AI product advisor pays off
Product search via chat
Many don't realise it: WebChatAgent also replaces your search. Instead of clicking through filters, visitors ask in natural language – for example for waterproof hiking boots under €100 – and the bot instantly finds and recommends the matching products. Search and advice in one.
Complex & explainable products
For technical or configurable products: the advisor asks the qualifying questions a good salesperson would and narrows down to the right fit.
Advice plus support
One assistant for product questions and after-sales: availability, shipping, returns and order status – with human takeover when needed.
Lead qualification & booking
Capture and qualify leads, then book the appointment directly via Google Calendar – straight from the conversation.
Explore more
- AI product advisor guideHow an AI advisor guides visitors to the right product.
- AI Product Advisor ComparisonSeven product advisor tools compared on price and scope.
- PricingFind the right plan for your business. See all features side by side.
- FeaturesAnswer recurring questions, capture leads, and book appointments. Your team can take over complex requests.
FAQ
Frequently asked questions
WebChatAgent provides German primary hosting, a DPA and selectable EU models. Lawfulness of a product-adviser setup depends on its data, integrations, legal basis and configuration.
Yes. One-click integration for WordPress/WooCommerce and Shopify, plus REST API and webhooks for custom shops.
Minutes, not weeks. Enter your URL or product feed, the AI indexes your catalog, place the widget and you're live.
Yes. There's a free tier to test and paid plans from €19/month – no sales call required to start.
No. The advisor answers strictly from your indexed catalog and documents, so it recommends only products you actually sell.
Free to start, Basic €19/month, Standard €35/month (recommended for most shops), Premium €85/month. Transparent pricing, no setup fee.
Give your shop a real product advisor
Start free, connect your product data, review the recommendations, then publish the advisor.