Labelf Visits Kontakta to Talk About AI in Customer Service

Viktor and Ted from Labelf were invited to present at Kontakta, a non-profit industry association for customer contact companies in Sweden. The webinar, presented in Swedish, explored how AI Transformer technology is being applied in customer support to help organizations reduce response and resolution times while identifying the cases that consume the most resources.

The presentation covered how Labelf’s platform enables teams to analyze customer reviews, cases, and feedback collectively — helping organizations move beyond Excel-based analysis and directly measure the impact of their improvement initiatives.

Key Topics Covered at the Event

Automated Case Classification and Routing

A central theme of the presentation was how AI can automate the classification of incoming support tickets, calls, and chat messages. Rather than relying on agents to manually tag and categorize every interaction, Labelf’s platform handles this automatically and in real time. This means inquiries are routed to the right team or agent from the moment they arrive, reducing misdirected cases and cutting down on resolution times.

Tracking Backlogs and Resource Consumption

The webinar also explored how automated classification feeds into backlog tracking. When every case is categorized consistently, managers gain a clear picture of which issue types are piling up, where bottlenecks exist, and which categories consume the most agent time. This visibility makes it possible to staff appropriately, prioritize high-impact issues, and intervene before backlogs spiral out of control.

Transcription and Multi-Language Analysis

One of the standout capabilities discussed was the system’s ability to transcribe and analyze customer interactions across multiple languages — without requiring separate support centers for each language. This is particularly relevant for Nordic organizations that serve customers in Swedish, Norwegian, Danish, Finnish, and English, all from a single team.

ChatGPT-Powered Response Suggestions

The presentation highlighted how AI-powered response suggestions can improve both consistency and speed. By surfacing relevant, pre-drafted answers to agents in real time, the system reduces the cognitive load on each interaction and helps newer agents perform at a level closer to experienced colleagues from day one.

What Attendees Learned

Attendees came away with a practical understanding of how AI Transformer models apply to everyday contact center operations. Key takeaways included:

• Faster agent onboarding. New hires get up to speed more quickly when the system suggests responses and automates routine classification tasks, reducing the training burden on the team.

• Reduced manual work. Automating tagging, categorization, and routing frees agents to focus on solving customer problems rather than administrative tasks.

• Consistent, scalable analytics. Moving from spreadsheet-based tracking to automated analysis means the data improves over time and stays reliable as volume grows.

• Cross-functional insights. The customer interaction data captured and analyzed by the platform is not only useful for the support team. It generates insights applicable to marketing, product development, and sales decisions as well.

Why This Matters for Customer Service

Customer service organizations sit on a goldmine of data, but most of it goes unanalyzed. Every call, email, and chat contains signals about what customers need, what frustrates them, and where products or processes are falling short. The challenge has always been extracting those signals at scale.

The approach Viktor and Ted presented at Kontakta addresses this directly. By applying AI classification and analytics to the full volume of customer interactions, organizations can stop guessing and start measuring. They can see which initiatives actually reduce contact volume, which issue types are growing, and where agent effort is best spent.

This is not about replacing human agents. It is about giving them better tools and giving leaders the information they need to make smarter decisions. When agents spend less time on repetitive tasks and more time on complex, high-value interactions, both customer satisfaction and employee engagement improve.

For organizations still relying on manual tagging and Excel reports, the gap is only widening. The tools to automate this work are available now, and as the Kontakta presentation demonstrated, the results speak for themselves.