Volvo

Box Car is an advanced, expensive testing machine used for full-scale vehicle system tests at Volvo. These machines run comprehensive validation tests on vehicle systems before final integration.

With limited availability and high operational costs, Box Car resources were heavily constrained. Engineering teams struggled to coordinate access efficiently, leading to scheduling conflicts, budget uncertainty, and suboptimal resource utilization.

SK Good Tech AB built an LLM-powered agent using LangChain that serves as an intelligent coordinator for Box Car resource management.

The agent acts as a central interface between engineering teams and testing resources, automating coordination, providing budget insights, and supporting decision-making.

The engagement required close collaboration with multiple engineering teams across Volvo's vehicle development organization.

SK Good Tech AB worked directly with test engineers, system owners, and planning teams to understand coordination pain points, translated resource management needs into an AI-powered solution, and ensured the agent could operate reliably within Volvo's existing workflows.

The LLM agent streamlined Box Car resource allocation, reducing scheduling conflicts and enabling data-driven budget forecasting.

Engineering teams gained a single intelligent interface for coordinating expensive testing resources, improving utilization efficiency while maintaining testing quality standards.

Built using LangChain for agent orchestration with custom tools for SQL queries to historical testing databases. Integrated with Volvo's existing scheduling and cost tracking systems. Python-based implementation with robust error handling and logging for production reliability.