MEET ATSCALE / HOW ATSCALE POWERS AI AGENTS
Agents act on numbers. Give them the right ones.
AtScale gives your agents approved metrics over MCP today, and keeps the SQL behind every answer on record.
WHAT WE’RE OUT TO SOLVE
No more than 10% of organizations are scaling AI agents in any single business function.
McKinsey, The State of AI, 2025
The main reason is trust. An agent that writes its own SQL gets some numbers wrong, and the errors are small enough that a person won’t catch them in a morning review.
HOW IT WORKS
Four steps from question to record, over MCP today.
An agent connects to AtScale’s MCP server and makes the same four calls for every number it needs. MCP works best for agents your company builds and controls, and the major agent frameworks can all call MCP tools. If a person asks the same question in Claude, they’ll get the same answer.
FIG. 1 · FROM QUESTION TO RECORD
The MCP server signs callers in through OAuth. Row- and column-level security applies to an agent just as it does to the person it’s signed in as.
AVA, ACE, CANARY AND SEMANTIC MODELING
Accurate metrics for agents, and the tests to prove them.
On the BIRD-Interact benchmark, adding AtScale made an LLM twice as accurate. The path to 100% AI accuracy covers what it takes to close the rest of the gap.
Confirms the right metric before agents guess.
AtScale Ava MCP server
An agent won’t stop to ask which revenue you meant. When a term could mean more than one metric, Ava checks it against the definitions in the semantic model, so the agent uses the right one.
The enterprise AI calculator agents call.
AtScale ACE
Inventory on hand adds up across warehouses but not across weeks. Customers move between regions, and revenue arrives in euros and yen. These rules are defined once in the semantic model, and ACE applies them the same way on every query.
Attests that the metrics agents get are accurate.
AtScale Canary
Canary is coming this fall. The questions a workflow will ask become test cases, and Canary will score each one with and without AtScale and group every miss by its cause. When you switch AI models, it’ll run the tests again.
Modeling that keeps pace with what agents ask.
AtScale Semantic Modeling
Agents ask about more of the business than an analytics team ever did. Semantic Modeling drafts each model change in SML for a person to approve, and it’s shipped through Git like any other code.
Get the AtScale for Agentic AI ebook.
EBOOK
A short field guide to running agents on accurate numbers: the four MCP calls, how ACE gets hard metrics right, how Canary will test the questions a workflow depends on, and nine agents to build by industry.
Book a workshop.
Have a workflow you’d like to automate? We’re building agentic systems with a handful of customers now.
- Bring us your most controversial metric and the business questions your team and your agents ask about it every week.
- We benchmark your AI on them, with AtScale and without it.
- You keep the semantic model we built to run the test.