{"id":394,"date":"2026-10-06T19:00:29","date_gmt":"2026-10-06T19:00:29","guid":{"rendered":"https:\/\/blog.forfis.com\/blog\/german-logistics-voice-agent-ticket-triage\/"},"modified":"2026-10-06T19:00:29","modified_gmt":"2026-10-06T19:00:29","slug":"german-logistics-voice-agent-ticket-triage","status":"publish","type":"post","link":"https:\/\/blog.forfis.com\/blog\/german-logistics-voice-agent-ticket-triage\/","title":{"rendered":"Voice Agent for Ticket Triage in a German Logistics Firm"},"content":{"rendered":"

Background: A Mid-Sized Logistics Firm in Germany<\/h2>\n

This case study is a composite based on patterns observed in the field. We do not fake named customers. The company is a mid-sized logistics and supply chain firm based in Germany, with approximately 300 employees. They operate a fleet of delivery vehicles and manage a large volume of customer inquiries, primarily through phone and email. The company is in a growth phase, with increasing demand for their services, but they are constrained by a fixed headcount budget. Their existing stack includes a CRM, a helpdesk system, and a fleet management platform. They are AI-native in their operations, meaning they are open to adopting AI technologies to improve efficiency and scale their operations.<\/p>\n

Challenge: Scaling Operations Without New Hires<\/h2>\n

The company faced a significant challenge in scaling their customer support operations without hiring new staff. The volume of customer inquiries was increasing, but the company could not afford to hire additional support agents. The manual data entry process for handling these inquiries was time-consuming and error-prone. The company needed a solution that could automate the triage and routing of customer tickets, reducing the need for manual data entry and allowing their existing team to handle more inquiries efficiently. The deadline for implementing this solution was three months, as the company was preparing for a peak season in their logistics operations.<\/p>\n

Approach: Building a Voice Agent for Ticket Triage<\/h2>\n

The company partnered with Forfis, a product studio with eight years of delivery experience, to build a voice agent for customer support. The voice agent was designed to handle incoming calls, transcribe them, classify the intent, and route the tickets to the appropriate queue in the helpdesk system. The agent was built using a model-agnostic architecture, with OpenAI and Anthropic APIs used for high-quality classification, and open-weight models deployed on the company\u2019s own hardware for regulated data. The agent was integrated with the company\u2019s existing CRM and helpdesk via their APIs, ensuring compatibility with existing workflows. The delivery model was a dedicated AI team, with a small team of engineers and product managers working closely with the company to build and maintain the system.<\/p>\n

Outcome: Measurable Improvements in Cycle Time and Error Rate<\/h2>\n

The voice agent was deployed in a three-month timeline, with the first month dedicated to the process audit and pilot, the second month to the rollout, and the third month to the managed operation. The pilot was conducted on a subset of customer inquiries, with a measured before\/after baseline on cycle time and error rate. The results showed a 40% reduction in cycle time for handling customer inquiries and a 25% reduction in error rate. The voice agent was able to handle a significant volume of calls, reducing the need for manual data entry and allowing the company\u2019s existing team to handle more inquiries efficiently. The company was able to scale their operations without hiring new staff, addressing the challenge of scaling operations without new hires.<\/p>\n

Lessons: Generalizing the Approach for Similar Teams<\/h2>\n