AI Shopping Assistant Development for a Safety Footwear Manufacturer
HAIX customers with very specific needs, from firefighting to tactical and outdoor work, needed help finding the right footwear online. Acquaint Softtech built a conversational AI shopping assistant embedded in the website, connected to the product catalog and kept within real inventory and product data. Customers now browse more actively, ask more questions, and send fewer support inquiries about choosing a product.
1948
YEAR HAIX WAS FOUNDED IN BAVARIA2,300
HAIX EMPLOYEES WORLDWIDE1.88M
PAIRS OF SHOES MADE IN 2023
CLIENT STORY
HAIX is a German manufacturer of functional and safety footwear, founded in 1948 in Mainburg, Bavaria. It is a recognised brand for firefighters, police and task forces worldwide, and is also established in workwear, forestry and outdoor markets. HAIX employs about 2,300 people and manufactured about 1.88 million pairs of shoes in 2023.
HAIX products are technical and not always easy to explain in plain terms. New online visitors did not always fully understand its product categories or features, and the company wanted to recreate the in-store expertise its customers are used to. HAIX partnered with Acquaint Softtech to build an AI shopping assistant that guides shoppers by intent, not just clicks.
Country
Germany
Industry
Safety & Functional Footwear
Team Size
6-10 Professionals
Hours Invested
1,224 Hours
Technology
AI
Project Background
HAIX wanted every online visitor to get the kind of guidance they would receive from an expert in a store. Rather than focusing only on a UI redesign, Acquaint Softtech proposed a conversational assistant that understands what a shopper actually needs.
Faster Product Finding: Help customers with specific use cases, like firefighting, tactical operations, or outdoor work, find the right footwear quickly.
Less Friction in Discovery: Make technical categories and features easy to navigate for first-time visitors.
Guided Shopping Online: Replicate the in-store expertise HAIX customers are used to.
Our products aren’t easy to explain in plain terms, but we managed to build a system that made recommendations feel natural and understandable, even for someone unfamiliar with safety footwear.
Research & Ideation
Acquaint Softtech approached the problem differently than HAIX expected. Instead of redesigning screens, the team focused on guiding shoppers by intent, combining AI integration with targeted frontend adjustments.
Intent Over Clicks
Designing an assistant that responds to what a shopper is trying to do, not only where they click.
Accuracy Above All
Keeping every recommendation within the boundaries of real product and inventory data, with no guessing.
Context Awareness
Adapting responses depending on whether a user is browsing, comparing or ready to purchase.
Creative Design
Design here meant guidance without interruption. The AI shopping assistant is embedded into the website and supported by UI enhancements that enable assisted browsing without breaking the shopping flow. Shoppers get suggestions in one place instead of jumping between pages, which gives complex buying decisions a clearer structure.
Project Challenges
Highly Specific Use Cases
Firefighters, tactical teams, and outdoor workers each need very different footwear, and the right choice is not always obvious.
Unfamiliar Product Categories
New users did not always understand HAIX product categories or technical features.
“Which Product Should I Choose?”
Product choice questions were a common source of support inquiries.
Staying Within Real Data
Recommendations had to match actual inventory and current product data, with no invented answers.
Our Solutions
Acquaint Softtech built a conversational AI shopping assistant combined with frontend and backend work to keep it accurate and easy to use.
Embedded Conversational Assistant
An assistant on the website that answers product-related questions in real time.
Product Catalog Integration
Recommendations based on use case, environment and user preferences, drawn from the HAIX catalog.
Inventory-Aligned Backend Logic
Logic that keeps recommendations aligned with actual inventory and current product data.
Graceful Fallback Handling
A fallback structure that handles unclear queries instead of returning irrelevant suggestions.
Assisted Browsing UI
UI enhancements that support guided browsing without interrupting the shopping flow.
Custom Functionalities
Beyond the core assistant, the team built features shaped around how professionals choose safety footwear.
Use-Case Recommendations
Suggestions matched to the job or environment, such as firefighting or outdoor work.
Stage-Aware Responses
Answers that change depending on whether the shopper is browsing, comparing or ready to buy.
Plain-Language Explanations
Technical product features explained in a way people unfamiliar with safety footwear can follow.
No-Guess Answers
The assistant stays within the boundaries of real data rather than guessing.
On Going Support
Acquaint Softtech did not treat the assistant as a one-time delivery and stayed involved after launch.
Post-Launch Response Refinement
After the first version went live, the team refined responses based on real user interactions.
Quick Phrasing Adjustments
When HAIX wanted changes to how recommendations were phrased, the team responded and iterated without delay.
On-Time Milestones
Milestones were delivered on time throughout the project.
Project Outcome
After launch, HAIX noticed more engaged browsing sessions. Customers spent more time interacting with the site, actively asking questions and exploring recommendations rather than just
scrolling. Support inquiries about which product to choose, previously a common issue, dropped.
Customers also navigated complex product decisions more easily. Instead of jumping between pages, they received guided suggestions in one place, making the buying journey feel more structured.
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