AtScale
The Universal Semantic Layer for AI
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Latest posts
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Grok and AtScale help your AI stop guessing what business metrics are and how they’re computed
AtScale joined the SpaceX Super Intelligence Partner Network, so now Grok Build gets the metric definitions your finance team already signed off on. Executive summary: AtScale is now a Marketplace Partner in the SpaceX Super […] The post Grok and AtScale help your AI stop…
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A better LLM isn’t the biggest upgrade for Text-to-SQL
Executive Summary Seven LLMs answered the same 410 business questions from the BIRD-Interact benchmark, once against PostgreSQL with full documentation and once through an AtScale semantic layer. Their tool-call logs show seven working styles. Grok […] The post A better LLM…
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AtScale and OpenAI: The Comprehensive Guide
OpenAI has changed how people work. Enterprise teams use ChatGPT every day to draft, summarize, research, and write code. Building enterprise applications on business data is a harder row to hoe. Ask Codex to build […] The post AtScale and OpenAI: The Comprehensive Guide…
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Will the real semantic layer please stand up?
Executive Summary: A semantic layer defines business metrics and computes them on request. A universal semantic layer makes those definitions available across AI agents, BI tools, and spreadsheets, reducing duplicated logic. An AtScale customer-count example […] The post Will…
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BIRD-Interact, explained: the conversational text-to-SQL benchmark
What is BIRD-Interact? BIRD-Interact is an independent benchmark that tests how well AI systems complete database tasks through conversation. It evaluates whether a system can clarify a vague request, explore the database schema, write correct […] The post BIRD-Interact,…
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You Defined Your Metric Once. So Why Don’t Your AI Tools Agree?
Why don’t AI tools agree on the same number? AI tools don’t agree because each one guesses which data your definition points to. Ask for retention, and the model scans the schema for tables and […] The post You Defined Your Metric Once. So Why Don’t Your AI Tools Agree? appeared…
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Self-Service Analytics Stalled Once. Will AI Stall It Again?
Why did self-service analytics for BI stall? Self-service BI stalled because the numbers didn’t agree, not because the tools were hard to use. Wayne Eckerson coined “spreadmart” for “the renegade spreadsheets and desktop databases wreaking […] The post Self-Service Analytics…
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Every AI Accuracy Fix Your Team Made This Year Reopens at the Next Upgrade
Executive summary Your team makes most AI accuracy fixes for one model. When that model changes, custom training has to be rerun on the new model, and prompts and skills files have to be retested. […] The post Every AI Accuracy Fix Your Team Made This Year Reopens at the Next…
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Stop Writing Your Semantic Model. Start Reviewing It.
Executive summary AI tools, like AtScale’s CoModel, can now draft most of a semantic model, and that will change the data modeler’s job. Claude Sonnet 5, working through a semantic layer that AI generated and […] The post Stop Writing Your Semantic Model. Start Reviewing It.…
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How to Achieve AI Accuracy: Buy the Foundation, Rent the Model
Executive summary AI leaderboard rankings measure a model working alone, on tasks that look little like your warehouse. On the 410 business questions in the BIRD-Interact benchmark, what sat under the model made a bigger […] The post How to Achieve AI Accuracy: Buy the…
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Microsoft’s About-Face on Semantic Layer Standards
When Snowflake launched the Open Semantic Interchange in September 2025, dozens of companies signed on. Microsoft wasn’t one of them. Power BI’s semantic models stayed in DAX, built for Power BI, while the rest of […] The post Microsoft’s About-Face on Semantic Layer Standards…