Your head of sales sees $14.2 million in Q3 revenue. Your CFO sees $12.8 million. Both asked an AI agent this morning to provide numbers. Same data. Why the discrepancy?
This is what can happen when business logic is scattered across separate tools: a metric defined inside a BI model only one team owns, a calculation buried in a dashboard, a set of instructions manually hardcoded into an LLM prompt. The result isn’t just metric drift, where sales and finance show different numbers in response to the same question. It’s a trust gap that makes it hard to move AI projects forward quickly with confidence.
Today, that changes. Snowflake introduces Horizon Context, a new capability within Horizon Catalog that offers a connected, governed semantic foundation with active context for AI and BI.
“As AI becomes increasingly embedded across our enterprise, it’s essential that applications, analytics and agents operate from the same trusted understanding of the business. Snowflake Horizon Context helps extend consistent business definitions across our broader data ecosystem, supporting more trusted and governed AI and analytics experiences at scale.”Jeff MillerManaging Director, Global Head of Data Factory & Enterprise Data Platform, BlackRock AladdinSnowflake Horizon Context builds on Horizon Catalog’s metadata foundation by turning that metadata into governed business meaning. It collects context from across your data estate, enriching it with business definitions and relationships, and activating it so AI agents, BI tools and applications can automatically discover and apply trusted logic.
