Bytes of knowledge

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.

Your CRM has AI. Your help desk has chatbots. So why invest in separate automation platforms or AI customer service solutions? Because tools that connect systems aren’t the same as tools that handle conversations.

Queries and Tester – the features of KODA Intelligence – address the need for constant analysis and optimization of AI assistants’ performance and allow for adapting automation performance to evolving goals, context, and user needs.

Evaluators are manual and automated tools for monitoring the quality and safety of AI-generated answers. Learn how in the KODA platform we control LLM-generated content internally – before it ever reaches the user.

Analysis of McKinsey, BCG, Gartner, and MIT research reveals why AI projects fail and what successful organizations measure differently. Learn how to define success metrics for your specific context.

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.