AI, Nexus 2025, FlixBus, India, Natural Language

Bridging Language Barriers with AI: Lessons from Nexus 2025

I just got back from attending Nexus 2025 in Dussedorf, Cognigy’s flagship event, and it was nothing short of inspiring. The conference brought together some of the brightest minds in conversational AI, automation, and customer experience. One recurring theme resonated with me personally—how AI is revolutionizing multilingual contact centers, especially in linguistically diverse countries like India.

Conversational AI: Beyond Language Translation

One of the standout sessions for me was focused on scaling customer service across languages and dialects using AI, where the team behind FlixBus India shared their journey.

India is home to 22 official languages and hundreds of dialects, with each region boasting its own colloquialisms and speech patterns. In such an environment, a one-size-fits-all approach to customer service simply doesn’t work.

FlixBus India: The Power of Local Nuance

FlixBus India faced a common but critical challenge: how to offer consistent, high-quality support in a way that feels natural to speakers of Hindi, Tamil, Telugu, Kannada, Marathi, and beyond—including their many dialects and regional quirks.

Instead of relying solely on translation tools, FlixBus used NLU capabilities to train their virtual agents on region-specific phrases and intents. This meant the bots could understand not just what was being said, but how it was being said—recognizing slang, abbreviations, and code-mixed language (e.g., “Hinglish”).

For instance, a customer might say, “Mujhe kal ka ticket cancel karwana hai par refund kitna milega?” (I want to cancel tomorrow’s ticket, but how much will I get refunded?)—a fairly straightforward request, but packed with informal structure. The AI now understands such variations and responds naturally, often even switching context when the customer changes mid-conversation, as we often do when speaking.

My Key Takeaways

Here’s what I walked away with from the Nexus event when it comes to multilingual contact center strategies:

• Language ≠ Communication: It’s not just about translating words—it’s about understanding intent, tone, and context.
• Training with Real Data: The best models are trained with real conversations, including slang and code-switching. Synthetic training data doesn’t cut it.
• Continuous Learning: AI systems need ongoing feedback loops to adapt to new trends in language use (especially important in countries where language evolves rapidly).
• Human + AI Collaboration: Even the most advanced bots have escalation paths to human agents, who are now empowered with context-aware summaries thanks to Cognigy’s real-time agent assist.

Looking Ahead

The Nexus event reinforced something we’ve all sensed—AI isn’t here to replace customer support; it’s here to elevate it. And in the case of multilingual contact centers, AI is becoming the linchpin that holds together seamless, localized, and scalable customer experiences.

As we build out our own solutions and partner with businesses tackling language diversity, the learnings from Nexus—especially the FlixBus India example—are a guiding light.

If you’d like to speak to me some more about how A&M Technology Solutions can help you on your journey to elevate your contact center we can start this journey now with the intent and not just the language. The right AI tools will follow.