Case Study: Seznam.cz unifies trusted AI context and data lineage with Dawiso

Seznam.cz unifies 88 data products and 681,000 governed objects with Dawiso

Seznam.cz, the Czech internet leader, faced challenges in making its vast data trustworthy and discoverable for AI and decision-making. Teams reported conflicting numbers for the same metrics, data was duplicated across scattered tables, and there was no end-to-end lineage across their Keboola, Snowflake, and Tableau stack. Their internal conversational analytics tool lacked the context to provide accurate answers, so they partnered with vendor Dawiso to implement a solution.

Dawiso provided a trusted AI context layer via its Model Context Protocol (MCP) server, which feeds the conversational tool with authoritative definitions and points it to governed data products. The solution delivered end-to-end lineage across all tools and consolidated scattered data. As a result, Seznam.cz now gets consistent, trusted answers from its AI, and teams have clear ownership and discovery of data. The impact includes 88 data products, end-to-end lineage for impact analysis, and a platform with 238 registered users.

Seznam.cz