One number, in every tool
Agents query over MCP while analysts stay in Excel and Power BI, and both see the same number.
ATSCALE FOR AI : LIVE DEMO
AI gets 1 in
5 business
questions right.
See AtScale double it.
Your teams ask AI for answers and get a different number from every tool. AtScale makes every AI and BI answer match one agreed definition, so the number in the board deck is the number the chatbot gives.
30-MINUTE LIVE DEMO
TRUSTED BY DATA TEAMS AT
Deliver high accuracy from your AI
30h → 90s
Blue Yonder turned a four-day analysis into a 90-second AI answer on its semantic models.
More than 2x
AI accuracy with AtScale’s semantic layer. BIRD-Interact, preliminary.
21,000x
Less warehouse spend for the same questions. Tier 1 bank benchmark.
<3 sec
Papa Johns query times, down from 30–45 seconds.
What changes when AI stops guessing.
Every answer is computed
Every number traces to a signed definition, computed in your warehouse.
Ambiguous questions get clarified
AVA routes “revenue” to the metric you meant, and asks when it isn’t sure.
Metrics you can explain to an auditor
Definitions ship like code, and warehouse permissions carry through.
AtScale CoModel
Agents draft the model; a modeler approves before anything ships.
An accuracy score you can check
Canary runs your questions against known-right answers and flags what broke.
THE PROBLEM
AI works. Enterprise accuracy doesn’t.
LLMs are built to guess. They infer joins from column names, and a wrong answer looks exactly like a right one.
1 in 5
Enterprise questions answered correctly by AI without a semantic layer. BIRD-Interact, preliminary.
No single source of truth. Every tool holds its own version of revenue.
Semantics siloed per tool. A definition in one BI tool never reaches the next, or your agents.
No audit trail. Nobody can say who owns a number or explain it to finance.
CUSTOMER STORY : BLUE YONDER
“We essentially collapsed 30 hours of work over a four-day period between multiple people… into a one-and-a-half-minute wait time out of an AI tool.”
Jeremy Arendt
Sr. Director of Analytics Engineering, Blue Yonder
What happens in your demo.
01
Bring the metric your team argues about. We’ll define it once and compute it in your warehouse.
02
Ask it from the tools you already use. Claude or Copilot, then Excel or Power BI, and get the same number.
03
Get early access to what’s next. CoModel and Canary, coming this fall.
FAQ
INFORMATION
What is AtScale?
AtScale is a universal semantic layer platform that defines business metrics once and computes them where your data already lives, so every BI tool, AI agent, and application gets the same answer. Its AI Computation Engine (ACE) turns each request into optimized SQL and runs it in your cloud data warehouse, such as Snowflake, Databricks, or Google BigQuery.
How is this different from text-to-SQL on my warehouse?
Copy review needed: add the approved comparison with text-to-SQL.
Do I have to replace my BI tools or data platform?
No. AtScale computes each metric in your data platform and returns the same result to the BI tools and AI agents you already use.
How long does setup take?
Most customers have their first governed semantic model live in 6-8 weeks. With AtScale’s new AI CoModel, we are shortening the time to value. A typical rollout connects AtScale to the warehouse, builds or imports the first model, then connects BI tools and AI agents.
What should I bring to the demo?
Copy review needed: add the approved demo preparation instructions.
What’s available today and what’s coming?
AtScale is one platform. ACE computes your metrics inside your data platform. Ava works out which metric a question means before anything runs. Governance carries your access rules through and versions every definition like code. CoModel, for building and maintaining the model with AI, and Canary, for testing answers against known-correct results, are coming.
If it’s not AtScale,
it’s just a guess.
Bring one metric to a 30 minute session and watch every tool return the same answer.