How to implement AI in your Customer Support and the challenges to overcome

How to implement AI in your Customer Support and the challenges to overcome
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  • Blog: Personalized Models: Empowering Customer Support with Generative AI
  • Video: Automated Resolution Ratio

Blog: Personalized Models - Empowering Customer Support with Generative AI 💪🏽

Generative AI has been making waves in various industries due to its ability to generate human-like responses to a variety of queries. However, it has been noted that ChatGPT can sometimes "hallucinate", creating responses that are not relevant or accurate to the question at hand. While this issue can be resolved by feeding the model with correct data and guiding it to stay within the lines, implementing generative AI in customer support remains challenging.

Unlike other industries where there is a shared ground truth, each business in customer support has a unique knowledge set. This means that every business will require its own personally-tuned model to cater to its specific needs. While repetitive support tickets with high volumes may not pose significant challenges, businesses with limited data may struggle to implement generative AI in their customer support processes.

However, as technology continues to advance, tuning models for specific use cases will become a standard practice, enabling generative AI to provide valuable support to businesses. With personalized models, generative AI can help support teams answer customer queries faster and more accurately, leading to improved customer satisfaction and increased business efficiency.


While there are challenges to implementing generative AI in customer support, such as the need for personalized models and limited data, it has the potential to revolutionize the industry by improving response times and accuracy. With advancements in technology, it is only a matter of time before generative AI becomes standard practice in customer support.

Video:  What is Automated Resolution Ratio and why is it so important 🎬


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