PolyWorkBench: Evaluating Multilingual LLM Agents in Long-Horizon Tasks

AI-based agents are transforming business productivity, but when they must operate in multiple languages, critical challenges arise that traditional benchmarks fail to capture. In this article, we analyze the concept behind PolyWorkBench, an evaluation environment for LLM agents in multilingual, long-duration workflows. We explore how language mixing impacts reasoning, tool invocation, and output quality, and what implications this has for companies needing enterprise AI that is robust and truly global. Additionally, we address how services such as custom applications, AWS and Azure cloud infrastructure, cybersecurity, and business intelligence solutions like Power BI can support the deployment of multilingual agents in real-world environments. A technical and strategic analysis for those looking to take automation with AI agents to the next level, with Q2BSTUDIO as a technology partner.