WRS AI Sales Agent

An AI sales agent for online stores that knows your catalog and guides customers to the right choice

An AI sales agent for online stores is a new generation of sales software that understands everyday customer language, uses real product data and supports selection, comparison and the next step toward purchase.

Product searchContextual conversationComparisonsCatalog intelligenceCommerce Assistance
WRS AI Sales AgentProduct consultant
Online
I’m looking for a universal trunk liner, not a cabin mat.
Got it. I’ll exclude the cabin products and look for suitable trunk options.
Relevant product from the catalogUse: trunkStatus: confirmed by the storeCurrent price and availability
Show me a cheaper option.
I’ll compare only compatible options with a genuinely lower current price.
AI
Direct answer

What is an AI sales agent for an online store?

An AI sales agent for an online store is an intelligent sales consultant that uses the store’s real products, categories, prices, stock levels and rules to help customers find the right product and move on to purchase.

Unlike a standard chatbot, it doesn’t rely only on pre-written answers. Its job is to understand intent, find relevant options, explain the differences and keep the context.

The problem

When customers don’t know the exact word, standard search often falls short

Real shoppers don’t think in categories, filters and attributes. They describe what they need, change their criteria and expect someone to understand what they mean.

01

They don’t know the exact term

Customers search in everyday words, while the product name in the store may be different.

02

They get too many results

Dozens of similar items don’t help if nobody explains the difference and what each one is for.

03

There’s no one to ask

A standard filter can’t ask about size, budget, compatibility or how the product will be used.

04

The conversation starts over

“Not this one,” “cheaper” and “another size” lose their meaning when the system doesn’t keep the context.

The essential difference

Not every AI chat is a sales agent

The difference isn’t just in how it talks, but in the data, context and actions the system can use.

Standard chatbot

Answers within pre-defined scenarios

  • ×Limited questions and canned answers
  • ×Doesn’t reliably know the full product catalog
  • ×Loses the meaning of follow-up clarifications
  • ×Doesn’t compare real product specifications
  • ×Doesn’t confirm current price and availability
WRS AI Sales Agent

Advises through the real catalog and context

  • ✓Understands natural customer language and intent
  • ✓Works with products, categories, SKUs, models and attributes
  • ✓Handles negations, corrections and rejected products
  • ✓Compares options and suggests alternatives
  • ✓Uses live data confirmed by the store
How It Works

From an everyday customer question to a verifiable product recommendation

Behind the natural conversation is a consistent process that turns each request into clear intent, conditions and real results.

01

Understands the question

Recognizes terms, typos, sizes, budget, features and intended use.

02

Identifies intent

Tells apart a new search, a refinement, a rejection, a comparison and a request for something cheaper.

03

Searches the catalog

Works from structured product data, not general guesses.

04

Applies the conditions

Filters by category, use, price, size, color and availability.

05

Ranks the results

Exact names, SKUs and models take priority over broader matches.

06

Verifies the data

Price, stock, URL, currency and variant come from the live store.

07

Keeps the context

Understands follow-up changes without the customer repeating the whole request.

08

Supports the next action

Depending on the setup, it can open a product, the cart or the next step.

Natural Language

Customers shouldn’t have to think like a search engine

People describe a problem, a use case or a preference. The AI sales agent translates that language into the real structure of your catalog.

  • ✓Exact product name, SKU or model
  • ✓Category, brand, feature and intended use
  • ✓Singular and plural, synonyms and related words
  • ✓Budget, availability, size, color and style
  • ✓Negations and corrections in a follow-up message
NATURAL LANGUAGE SEARCHCatalog connected
Search in your customers’ own words“I’m looking for a universal trunk mat, not for the cabin.”
Catalog Intelligence

Product information becomes an active knowledge base for consultation

Names, categories and descriptions are no longer just page content. They work together as product knowledge.

  • ✓Product names, models, SKUs and brands
  • ✓Categories, subcategories and intended use
  • ✓Attributes, spec tables, sizes, options and variants
  • ✓Price, special price, stock and orderability
  • ✓Policies, contacts, shipping, returns and warranty
CATALOG INTELLIGENCELive data
ID

Identity

Name, SKU, model, brand and product page.

C

Classification

Category, intended use and product group.

One shared product foundationThe catalog becomes a working source for search, comparison and consultation.
Context and Corrections

A conversation that keeps moving forward

Customers can change their mind, exclude suggestions and refine a single criterion without starting over.

01

“Not this one”

The rejected suggestion is excluded and another relevant option is found.

02

“Show me something cheaper”

A specific product is used as the reference to find genuinely cheaper options.

03

“In a different size”

The core product type stays the same while the size or another attribute is updated.

04

“Not for the cabin”

The unsuitable use is excluded without losing the rest of the context.

Comparisons and Recommendations

More than a list of products

Customers rarely look for just an item. They want to know which option fits their situation best.

01

Comparison

Differences in features, intended use, price and practical use.

02

Cheaper options

Only relevant suggestions with a genuinely lower price in the current store.

03

Alternative when out of stock

A suitable substitute when the original product can’t be ordered.

04

Upsell and cross-sell

A higher-tier or related product only when there is a clear, useful reason.

A recommendation should be relevant and well-founded, not automatic sales pressure.
Commerce Assistance

From product consultation to the next step in the purchase

With the right integration, the AI sales manager can keep assisting the customer after the product is chosen, while the store stays in full control of the actual order.

01

Cart

Adds a specific product after confirmation and a check of the live data.

02

Options and variants

Size, color, configuration or any other required product option.

03

Quantity

Changes that respect stock, minimum quantities and limits.

04

Quick Order

Prepares a quick order according to the rules and capabilities of the integration.

05

Checkout handoff

Clear guidance into the store’s standard checkout process.

06

Live revalidation

Re-checks price, stock and terms before the actual action.

07

Shipping and returns

Answers based on the real policies, delivery times and shipping methods.

08

Warranty and contacts

Warranty terms, physical stores, opening hours and ways to get in touch.

The specific commerce features depend on the platform, its version, the catalog and the chosen level of integration.
Admin Control

AI functionality shouldn’t be a black box

WRS AI Sales Agent is built with control over the catalog, design, test modes, rules and gradual rollout.

  • ✓Design, placement, colors and branding
  • ✓Catalog index and Catalog Health
  • ✓Catalog profile, rules and synonyms
  • ✓Test Bench and an isolated tester session
  • ✓Feature flags, roles, store and language scope
WRS AI Sales AgentTester mode
OverviewCatalogSearchConversationsRulesDesign
CatalogSynced and indexed
SearchTest environment active
ContextStore and language scope
VisibilityControlled rollout
Catalog intelligenceReady
Test searchActive
Rules and synonymsManageable
Public activationControlled
Configurations

Start with what matters most and scale up in control

Not every online store needs the same level of automation. The product line can be rolled out in clear functional stages.

Level 01

Product Discovery

Product search, categories, models, SKUs, product cards and links.

Level 02

Sales Assistance

Context, refinements, comparisons, alternatives and policy answers.

Level 03

Commerce Assistance

Cart, options, quantity, Quick Order and checkout handoff.

Level 04

Enterprise / Custom

Multistore, multiple languages, B2B, CRM, ERP, API and custom rules.

Platform Product Line

One sales logic, adapted to different eCommerce environments

The functional scope is defined by the platform’s real API capabilities, the store version and the chosen integration.

In active development

OpenCart

The first core integration environment for catalog, admin control, search and commerce flows.

Planned integration

WooCommerce

A product direction for WordPress and WooCommerce stores.

Planned integration

Shopify

An integration model based on the Shopify API and its permitted commerce actions.

Planned integration

Magento

A direction for larger catalogs, customer groups and complex processes.

Custom eCommerce and B2B platforms can be connected through a project-specific API or middleware integration.
Different Catalogs

From car accessories to jewelry, furniture and technical products

The shared core stays stable, while terminology, synonyms and rules are enriched for each specific product domain.

A

Car accessories

Model, size, position, intended use, compatibility and product group.

T

Tools and machinery

Power, power source, kit contents, size and how it’s used.

H

Furniture and home

Dimensions, material, color, style, room, assembly and delivery.

J

Jewelry and fashion

Material, fineness, size, style, occasion, collection and product variants.

E

Electronics

Technical specs, interfaces, capacity, compatibility and model.

B

B2B Catalogs

Customer groups, quantities, negotiated terms and repeat orders.

C

Cosmetics

Skin type, ingredients, line, purpose, texture and use.

P

Spare parts

Part number, compatibility, manufacturer and alternative component.

Security and Control

AI functionality without losing control of your store

A good sales agent should never perform sensitive actions without confirmation, invent critical data or mix up context.

01

Server-authoritative

Critical data and actions are confirmed by the eCommerce system.

02

Confirmation

Cart, Quick Order and checkout can require an explicit action from the customer.

03

Store isolation

Products and context stay within the correct store.

04

Language isolation

The conversation and results use the correct language context.

05

Privacy and masking

Sensitive data can be restricted and masked by role.

06

Audit trail

Critical operations and admin actions can be fully traceable.

07

Tester mode

New functionality is tested in isolation before public activation.

08

Rollback

Rollout is planned with the option of a controlled rollback.

Implementation Process

Clear stages instead of a one-off switch-on

A reliable AI sales consultant is built on the real catalog, real business rules and measurable acceptance criteria.

01

Store analysis

Platform, checkout, languages, stores, integrations and customer questions.

02

Catalog analysis

Products, categories, SKUs, models, attributes and data quality.

03

Sales scenarios

Priority questions, product paths and permitted actions.

04

Integration

Connecting to the catalog, the admin panel and the commerce features.

05

Indexing

Preparing a product knowledge base for search and consultation.

06

Test session

Isolated use without switching it on for all visitors.

07

Acceptance

Testing with real products, browsers, and store and language boundaries.

08

Controlled growth

Activation, monitoring and improvements based on real requests.

Business Value

What an AI sales agent can change in day-to-day operations

The value doesn’t come from simply having a chat. It comes from making better use of the catalog and a clearer path from question to decision.

01

Faster discovery

Customers describe what they need instead of having to know how the store is structured.

02

A shorter path

Less aimless clicking between categories, filters and products.

03

Fewer repeat questions

Your team can focus on more complex customer cases.

04

Help after hours

Visitors get product guidance at the very moment they’re interested.

Real business results depend on traffic, the catalog, integration quality and the chosen scenarios. We don’t use generic, unverified percentages.
WRS
Why Web R Solution

An AI product built by a team with real eCommerce experience

An AI agent isn’t an isolated widget. It has to understand the product structure, the checkout process, the integrations, the SEO foundation and the business logic behind the store.

Web R Solution works with online stores, custom development, OpenCart, WordPress and WooCommerce, B2B platforms, CRM and ERP integrations, couriers, payments, SEO, AEO and digital marketing.

Frequently Asked Questions

WRS AI Sales Agent FAQ

The key questions about the product, integration, catalog, security and implementation.

What is WRS AI Sales Agent?
It’s an AI sales agent for online stores that uses your product catalog and managed business information to support search, product choice and the next step toward purchase.
How is it different from a standard chatbot?
A standard chatbot usually works with canned answers. WRS AI Sales Agent is designed to work with real products, categories, context, comparisons and controlled actions.
Can it find a product by SKU or model?
Yes. When the SKU and model are available and recorded correctly, they can be used as exact product identifiers.
Does it understand everyday customer language?
That’s one of the core product goals. The agent is being developed to recognize synonyms, word forms, refinements, negations and context.
Can it compare products?
Yes. With well-structured product data, it can compare features, intended use, price and other relevant criteria.
Can it suggest a cheaper option?
Yes. With the right sales flow, it can use a specific product as a reference and look for relevant suggestions with a genuinely lower current price.
Does it only work with OpenCart?
No. The first core integration versions target OpenCart, and the product roadmap includes WooCommerce, Shopify, Magento and custom eCommerce integrations.
Can it work with the cart?
In Commerce Assistance configurations, it can help with adding a product, options, quantity, Quick Order and checkout handoff. The scope depends on the platform.
Does it use real prices and stock levels?
Critical commercial data should be confirmed by the eCommerce system for the specific store, language, currency, customer group and product.
Can it be tested before going public?
Yes. An isolated tester mode and controlled activation are a key part of the implementation approach.
Is it suitable for a large catalog?
The architecture is designed for controlled indexing at different scales, but the actual scope is qualified based on the number of products, languages and stores.
How do we get started?
Send us details about your platform, the approximate number of products, your languages and the most common customer questions. Based on that, we’ll propose the right first stage.
Next Step

Turn your product catalog into an active sales consultant

The first step is an analysis of your platform, your catalog and the way your customers search. Then we define the right level of integration, real test criteria and a development plan.