Case Study: Building a Problem-First AI Assistant for Liftroller Australia

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For companies with extensive technical product catalogs, the sales process often begins with a bottleneck. Customers know their problem-like needing to get materials to a specific floor of a construction site-but they don't necessarily know the exact product name or SKU that solves it. This forces them to manually search through dense PDF catalogs or websites, trying to match their real-world need with a product specification sheet.

We recently worked with Liftroller Australia, a provider of specialized material handling equipment for the construction industry, to address this specific challenge. Their customers are professionals who need the right tool for the job, fast. The goal was to build a system that allowed users to describe their problem in their own words and get an immediate, accurate equipment recommendation.

You can see a demonstration of the system here: https://www.instagram.com/reel/DVRhKqUCKmi/

Designing the Recommendation Logic

Instead of a generic chatbot that might struggle with technical specifics, we built a system we call Rolli. The core of the logic was to invert the typical search process. Rather than having the user search for a product, the system asks the user for their problem.

A user can state, "I need to lift materials to the 5th floor." Rolli doesn't just search for keywords. It analyzes the statement against the structured data from Liftroller's entire product database-including specifications, load capacities, and operational limits. It then presents the most suitable equipment as interactive product cards.

From these cards, users can directly access the critical information they need to make a decision:

  • Downloadable PDF spec sheets

  • Technical drawings

  • Links to BIM models

Building Information Modeling (BIM) is a process that creates detailed 3D digital models of buildings, combining geometry with rich data about the project. Providing direct links to these models is critical for architects and contractors who need to integrate equipment into their project plans.

Handling Complex Project Inquiries

Not all inquiries are simple. A straightforward question about lifting height can be handled automatically, but complex projects with unique site challenges require human expertise. A simple contact form isn't sufficient for these cases, as it often leads to a long back-and-forth email chain to gather the necessary details.

We designed a second function for Rolli: a lead capture agent. When a project is identified as complex, the system's logic shifts. It intelligently prompts the user for all the required project details, cross-referencing the information to ensure nothing is missing. It asks for specifics like site access, material types, and project timelines.

Once all the information is collected, Rolli summarizes the entire request into a structured brief and sends it directly to the Liftroller sales team. This means the sales team receives a fully qualified lead with all the necessary context, allowing them to prepare a detailed and accurate quote without the initial discovery calls.

The Outcome

The system is now live for Liftroller Australia. Customers no longer have to dig through catalogs to find a solution. They can state their problem and get an instant, actionable answer. For the sales team, the process of qualifying complex leads is now automated, freeing them up to focus on closing deals rather than chasing information.

Case Study: Building a Problem-First AI Assistant for Liftroller Australia

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Website made by Imdev.ai

2025 copyright. All rights reserved

Website made by Imdev.ai