Revolution in Customer Care and HR: AI, Human Approach, and Advanced Personalization

Feedyou, a leading Czech specialist in conversational and generative artificial intelligence, is revolutionizing customer care.

“With over 300 successful AI projects for companies like PPL, ČEZ, Foxconn, Toyota Central Europe, and MONETA Money Bank, we combine cutting-edge technological know-how with long-term experience. As a result, our clients save hundreds of hours of work, leading to cost reductions in the hundreds of thousands of crowns. For example, at Foxconn, 70% of calls are fully automated,” explains Vojtěch Dlouhý, Co-Founder & CEO of Feedyou.

The combination of traditional conversational scenarios with powerful language models enables contact centers to respond to a wide range of customer needs—from quick answers to routine inquiries to complex issues requiring deeper understanding and empathy. Thanks to this synergy, AI virtual assistants have immense potential.

AI as a Core Tool for Everyday Interactions

The successful deployment of AI assistants lies in combining proven conversational scenarios with conventional language models (NLP/NLU) and advanced large language models (LLM). This synergy delivers astonishing results that were unimaginable just a short time ago.

Whether your goal is to increase efficiency, improve customer service, or speed up issue resolution, here are key trends and practices to help you fully leverage AI in practice.

AI Knowledge Base: The Sixth Sense for Operators

Many companies are looking for ways to automate and digitize their processes, but for some, direct AI deployment (e.g., voicebots) still feels like too big of a leap. Sometimes, they’re simply not ready to switch to “autopilot” yet. That’s why an ideal first step is the AI Knowledge Base—a solution that serves as a “copilot.”

“In real-time, it assists operators with guidance on handling calls and responding effectively to customer inquiries. Thanks to Generative AI, it fully adapts to the context of each interaction, drawing from previously solved cases, documents, manuals, and guides. This enables fast, accurate, and consistent responses,” explains Dlouhý.

By integrating NLP/NLU, LLM, and potentially conversational scenarios, businesses can avoid issues such as nonsensical AI-generated responses (“hallucinations”) and high operational costs. The AI Knowledge Base simply supports the operator, who retains full control over what information is shared with the customer-

Real-Time Analytics in Every Call

While calls used to be analyzed retrospectively, analytics, transcriptions, and operator recommendations now happen simultaneously in real time. Companies can instantly monitor whether customers receive the expected support during a voicebot interaction and, if an issue arises, automatically transfer the call to a live agent. This approach, already common with chatbots, is now available for voicebots, opening new possibilities for quality control in customer support.

“Real-time analytics mean that every call can be more efficient. When a voicebot struggles, an operator immediately takes over and can manage multiple calls at once, ensuring no customer is overlooked,” explains Dlouhý. The same technology can also be applied to live agent calls, enabling real-time statistics and improving human support efficiency—proving that call centers are far from disappearing.

A Custom Voice in Just One Day

The naturalness of voicebot voices has advanced significantly. Thanks to Generative AI, companies can now create a unique voice in just one day without needing a professional studio or lengthy recording sessions. With the right technology partner, businesses can deploy a voicebot with a voice that aligns with their brand image and feels natural to customers, significantly enhancing engagement and satisfaction.

Virtual Avatars Are Back on the Scene

Advancements in technology have brought digital personas—avatars—back into the spotlight. Companies now use virtual assistants that communicate not only via chat and voice but also through realistic visual representations (faces). In mobile apps or on touchscreens, avatars behave like real personas, elevating the user experience to a new level.

Imagine mobile banking apps or energy provider services: instead of manually adjusting settings in an app, users can simply ask an avatar how to increase their daily card limit or modify electricity payments. The avatar handles it for them, making interactions more convenient, natural, and exponentially faster.

Technologies like Microsoft Cognitive Services, Google Chirp, OpenAI Whisper, and Deepgram now enable the recognition of complex queries even in difficult phone call environments. They can process a variety of variables, including time, order numbers, addresses, and contact details, dramatically increasing the flexibility of AI solutions.

Currently, Feedyou supports approximately 50 languages, ranging from Czech to less common Eastern European languages, as well as Uzbek, Mongolian, and Vietnamese.

Emotional Intelligence Transforms Calls into Natural Conversations

While emotion analysis typically occurs after converting speech to text, recent advancements from OpenAI (Advanced Voice Mode) enable working directly with the acoustic curve—tone and intonation of voice. However, this technology still requires higher computational power and costs, making it not yet widely available. As a result, most companies continue to use traditional sentiment analysis, which is more financially accessible but misses important acoustic signals lost in text conversion. Additionally, signal quality significantly affects analysis accuracy.

The Solution? In practice, the best results come from combining sentiment analysis (or profanity detection, which we use to immediately transfer calls to a live agent) with emotion recognition. Together, these enhance the voicebot’s response accuracy, ensuring its reactions align with the caller’s mood and expectations.

Using Generative AI voices also enables more natural conversations, where the voicebot doesn’t follow a rigid script but adapts each interaction individually. With natural pauses, correct intonation, breathing, and even subtle sounds like lip smacks or hesitations, the voicebot creates an authentic and believable experience—even though it’s still a robot. Every conversation feels unique.

The future of customer care is here—digital, personal, and AI-driven. It’s about seamlessly integrating artificial intelligence with a human touch. This fusion enables advanced data analysis and personalization while maintaining genuine customer understanding.

Although voice assistant technology has made rapid progress, key challenges remain—such as instant responsiveness and natural communication that reflects callers’ emotions. A high-quality solution must be fast and precise to ensure conversations feel seamless, significantly enhancing the customer experience.

“We see AI as a tool to make operators’ jobs easier while improving the customer experience. Our solutions are not about replacing people but about building better teams where AI and humans work in harmony,” concludes Dlouhý.

However, AI is not a magic bullet. Not every interaction can be effectively automated, and deploying AI without thorough analysis and a focus on the human element can complicate communication rather than improve it. When implemented correctly, AI becomes a powerful tool that, with the right partner, can elevate customer support to a new level—often achieving a return on investment within just one year.

Make the Most of AI—We’ll Show You How