A clear architecture has formed beneath every enterprise AI agent, and the industry has quietly agreed on its shape: a semantic layer that settles what data means, and a context layer that governs how meaning gets used. However, another critical component beneath both is a trust layer that decides whether the data was ever true to begin with.
As data platforms like Snowflake continue to advance native semantic and context capabilities, organizations need to ensure they’re also feeding AI with quantified trusted data, not just better models or richer context. Without trusted data, even the most sophisticated AI agents can produce unreliable outcomes.
Join Ataccama and Snowflake in this webinar and see how trusted data becomes the foundation for trusted AI. We’ll demonstrate how to set up your semantic layer together with governed business context and trust signals to optimize your agents accuracy, reduce data governance & engineering overhead, and provide transparency to human consumers.
Key Takeaways
- Understand the three foundational layers of the modern AI stack: trust, semantics, and context.
- Learn why trusted data is the prerequisite for trustworthy AI outputs.
- See how governed trust signals can be integrated directly into Snowflake’s semantic layer using the Open Semantic Interchange (Ossie) spec.
- Watch a live demonstration of how AI agents benefit from trusted, governed enterprise data.
- Discover practical steps to prepare your organization for enterprise-scale AI with trusted data at its core.
Speakers
