AI agent for Woonbedrijf automates high-quality maintenance ticket creation
Streamlining social housing maintenance through an intelligent conversational agent that captures precise repair data.
Woonbedrijf
Woonbedrijf, a leading Dutch housing association, sought to modernise their internal maintenance reporting process. The goal was to replace static forms with an intelligent AI agent capable of interviewing employees to generate complete, actionable maintenance tickets for their technical teams.
Manual ticket entry often resulted in incomplete or vague descriptions, forcing back-office staff to spend hours clarifying details with employees or tenants. This lack of data quality led to misallocated resources, incorrect spare parts being ordered, and significant delays in resolving urgent repairs across their property portfolio.
What SevenLab built
SevenLab built a custom AI agent that uses natural language processing to guide employees through a structured conversation. The agent dynamically asks follow-up questions based on the context of the repair, ensuring every ticket meets the technical requirements for immediate dispatch.
Contextual interviewing
The agent adapts its questions in real-time to capture specific technical details based on the reported issue.
Automated data validation
Ensures all mandatory fields and technical specifications are present before a ticket is finalised.
Backend integration
Seamlessly pushes structured data directly into the existing property management system without manual entry.
Instant priority routing
Automatically classifies the urgency of repairs to ensure critical safety issues are addressed first.
Measurable business impact
The AI agent has transformed the maintenance workflow by ensuring that every ticket is 'first-time right'. By automating the interrogation and documentation process, Woonbedrijf has significantly reduced the administrative burden on back-office staff while improving the speed of service for their residents.
The AI agent has completely changed how we handle maintenance requests. By ensuring we get the right information from the very first interaction, we have eliminated the constant back-and-forth that used to slow down our repairs.
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