Customer description‍

A medium-sized municipality with more than 100,000 inhabitants received thousands of reports annually about waste, damage, inconvenience and disturbances in public spaces. The reports came in via an app, phone and web form.

Challenge‍

Manual review and routing of reports resulted in delays and incorrect assignment. Residents had to wait a long time for action or received no feedback. The municipal departments worked in a fragmented way and based on subjective estimates.

Solution‍

Blackbirds developed an AI classification model that automatically categorizes, prioritizes and assigns reports to the appropriate execution service. This was integrated into the existing case system, so that employees could work directly with structured input.

Approach

1. Report history analysis
   We collected and structured historical reports (text, location, type) and labeled them for handling and urgency.
2. Classification model training
   The AI model was trained to recognize notification types such as litter, street lights or dangerous situations, including location information.
3. Integration into the process
   The model was linked to the case system and notification app, so that classification was automatic upon arrival.
4. Monitoring and further development
   Feedback from performers was used to continuously improve the model and add new notification types.

Results

• 40% faster notification processing time
• More consistent assignment of reports to the right department
• Increased satisfaction among citizens and municipal staff
• Lower workload for control rooms and service desks

Conclusion‍

The use of AI in notification processing not only provides more speed, but also greater control and transparency in the process. For the municipality, this meant less noise, better services and space to proactively focus on quality of life.

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