Join AtScale and Distillery to explore how semantic governance makes NLQ work—across multiple tools, chatbots, and GenAI platforms.
In this 60-minute session, we’ll walk through:
- Escape Vendor Lock-In with Open Semantics
Why open semantic approaches beat proprietary solutions from Snowflake and Databricks. - Universal Chatbot Compatibility via MCP
How MCP lets your semantic layer work with Claude, ChatGPT, Slack, Teams, and any AI assistant. - Governance That Actually Works
How AtScale enforces consistent data definitions across every conversational interface. - From Demo to Production
What it takes to move beyond chatbot prototypes to enterprise-ready AI analytics.
Who should attend?
This webinar is designed for:
- Data Leaders looking to scale AI analytics without compromising governance
- Platform Engineers evaluating open vs. proprietary AI infrastructure
- GenAI Enthusiasts interested in production-ready conversational analytics
- Anyone tired of chatbot demos that never make it to production
Why it matters:
Most enterprises are stuck choosing between vendor lock-in solutions or building everything from scratch. This webinar reveals a third path: leveraging open protocols and semantic layers to create flexible, governed AI experiences that work with your existing tools and any approved LLM.
You’ll walk away with a clear roadmap for implementing trusted natural language query across your organization—without the usual compromises on security, consistency, or compatibility.
