WeBuyCars, the JSE-listed South African vehicle trading platform, has introduced two proprietary artificial intelligence tools—“Blue” and “Orange”—which the company believes will be foundational to its long-term growth and operational efficiency.
The tools are designed to serve distinct but complementary functions within the business:
- Orange is a customer-facing large language model (LLM) integrated into the company’s website. It also includes agentic AI capabilities for internal use, enabling autonomous and proactive support for both customers and staff. According to Wynand Beukes, Chief Digital Officer at WeBuyCars, Orange is designed to enhance user interactions and streamline internal workflows.
- Blue, on the other hand, is a backend machine-learning engine that powers the company’s proprietary pricing and decision-making systems. It draws on a vast dataset that includes historical buying and selling data, market trends, and analytics to generate accurate vehicle valuations. Updated weekly, Blue has already autonomously priced and purchased over 2,800 vehicles, with no human intervention.
“We’re scaling that up as we go,” said Beukes, highlighting the system’s growing role in automating high-volume, low-complexity transactions.
WeBuyCars’ approach is not to replace human expertise but to augment it. The company uses AI to handle routine, high-volume cases—such as pricing common models like the Volkswagen Polo Vivo—while reserving human judgment for more complex or rare vehicles, such as a 1974 Mercedes-Benz.
WeBuyCars operates a hybrid model that combines e-commerce capabilities with a physical footprint, including 17 vehicle supermarkets and around 100 buying pods across South Africa. The company’s digital-first philosophy has allowed it to build its own software and data infrastructure from the ground up, free from legacy system constraints.
“When we started, there was nothing. We didn’t have to deal with legacy, which was one of the great things,” said Beukes. “We wanted to be in control of the software and we wanted to be in control of the data.”
A key part of WeBuyCars’ innovation strategy is its experimentation platform, which allows the company to test new ideas quickly and cost-effectively. By exposing new features or tools to small user segments, the company can gather feedback, iterate rapidly, and scale only what works. “If it fails, it fails fast – with minimal cost,” Beukes noted.
By combining AI, data, and agile experimentation, WeBuyCars is positioning itself at the forefront of digital transformation in the automotive retail sector—balancing automation with human insight to scale operations while maintaining quality and trust.
