Chat automation

Buenos Aires handles 2 million monthly inquiries. South Korea reached 32 million users. Polish offices – from Wrocław to Częstochowa – are testing similar solutions. Here’s what works in practice and when automation makes sense.

How multi-level intent recognition works in KODA Intelligence: from rules that ensure full control, through machine learning that detects recurring patterns, all the way to generative AI embedded in safe frameworks for business.

This article explores the spectrum of chatbot solutions, from traditional script-based models to cutting-edge AI-powered assistants. Find out which best suits your business needs.

This guide outlines the essential stages for data preparation. With each stage, you’ll gain the tools and expertise to build a solid foundation for your assistant’s success.

Discover how to build safe and reliable chatbots using Large Language Models (LLMs).

To understand how chatbots recognize user intent and tailor appropriate responses to it, there are three main categories of natural language processing algorithms: linguistic models, machine learning (ML) and large language models (LLM).