ℹDemonstration scenario. An example of a possible implementation, not a completed client project of Neural2B.

Unified Assistant for Catalog, Smart Search, and Customer Support

Demonstration scenario: we organize specifications, write clear English descriptions from verified data, show current availability, and pass leads to CRM.

Business situation overview

In online stores with 10,000+ items from various suppliers, specifications are filled in haphazardly. Different units of measurement, missing key parameters, copy-paste descriptions. Regular search for live customer queries yields zero results. And support searches for products manually.

Data flow and architecture diagram

1CMS: Shopify or OpenCart as candidates for API integration

2Attribute normalization module: consolidates units of measurement (mm, cm, inches, kg, grams) into a single format

3Vector index for semantic search: searches by synonyms, purpose, and indirect descriptions

4Integration with CRM (HubSpot): customer inquiries and carts are automatically recorded

The human role in the loop (Human-in-the-loop)

Before mass synchronizing updated cards with the main site, the content manager reviews a sample.

Synthetic test data

Example input and system response

User input request:

"I need a slow submersible pump for a well 12 meters deep, enough for watering a garden and a house for 3 people"

Generated response / system action:

"Found 2 suitable models for a depth of 12 meters with a working pressure of 3.5 bar and dry run protection: 1) AquaSilent 750 (power 750 W, flow rate 45 l/min) — $100; 2) DeepWell Flow 1000 (power 1000 W) — $125. Both models have a 24-month warranty and are in stock. Would you like to compare them in more detail?"

Limits of the demo scenario

✕The assistant relies only on parameters from the manufacturer's technical passport
✕If there is insufficient data on specifications, the system honestly states so, rather than making assumptions
✕Prices and availability are pulled directly from the store's accounting database

What to measure during pilot testing

✓Share of search queries with no results (goal: minus 70%)
✓How complete and uniformly filled the product specifications are
✓How accurately the consultant responds — according to support managers

Relevant company service

Marketing and Content Automation

Service overview →

Interested in a similar architecture?

We’ll adapt the logic of this scenario to your internal software, database structure, and operating rules.

Discuss adaptation

Other scenarios

Scenario adaptation: Unified Assistant for Catalog, Search, and Support

Describe the process that’s eating up your team’s time. We’ll suggest what can be automated, what data is needed, and where to start.