THE PROBLEM
Enterprise leaders want to put generative AI on their business data. They can’t — because agents hallucinate metrics, invent definitions, and produce confident answers that don’t match the dashboards leadership already trusts. The blocker isn’t the model. It’s the missing layer of governed business context between the data and the agent.
THE ARCHITECTURE
An OpenAI agent answers a business question by reasoning over metrics governed by AtScale’s semantic layer, served from live data in Snowflake. The agent doesn’t redefine the company’s numbers — it uses the source of truth the business already trusts.
How it works
A campaign performance scenario — the workload every CMO, CFO, and analyst needs to trust.
THE USE CASE
The Challenge
Marketing leaders ask agents questions like “Why is ROAS down on connected TV?” Without governance, the agent calculates ROAS its own way — producing a number that doesn’t match the CMO’s dashboard. Trust collapses. The agent gets abandoned.
The Solution
With AtScale’s semantic layer between OpenAI and Snowflake, the agent uses the same metric definitions the company has already approved. Every answer is traceable to a governed definition. The agent isn’t a separate source of truth — it’s an interface to the source of truth the business already trusts.
What Enterprises Get
Agents that answer KPI-heavy questions with the same numbers as the dashboard. Auditable definitions for every metric. A foundation that scales from one workflow today to dozens tomorrow without rewriting the governance underneath.
WHAT THE AGENT ANSWERS
What was our ROAS on the Summer Sprint campaign?
Why is ROAS down on connected TV specifically?
What’s our incremental reach adding CTV to YouTube?
