Sigma Launches Native Semantic Layer Integration and AI SQL Capabilities on Snowflake AI Data Cloud
'Sigma is building toward a future where every layer of the data stack speaks the same language—defined once, executed everywhere.'
Query Semantic Views Directly in Sigma
With this integration, Sigma unlocks warehouse-defined metrics, dimensions, and relationships for downstream analysis, dashboards, and apps – cementing the data warehouse as the single source of truth for semantics.
This new integration offers joint customers the most seamless, warehouse-native analytics experience on the market. By partnering with Snowflake, the AI Data Cloud company, Sigma is helping to fully realize a long-held industry vision: semantic logic defined once, governed centrally, and accessed directly in the warehouse—no duplication, no drift. Together, the companies are mobilizing the world's data to help organizations operate in an environment where semantic logic lives natively in the warehouse, not duplicated across disconnected tools.
'Sigma's integration with Snowflake Semantic Views isn't just compatible — it's truly native, built for flexibility, scale, and the next generation of analytics,' said Mike Palmer, CEO of Sigma. 'By meeting the semantic layer where it belongs, we're giving business teams instant access to governed metrics and logic without compromise. And this is just the beginning. From bi-directional syncs to visual semantic exploration, Sigma is building toward a unified modeling experience that brings clarity and control to every layer of the data stack.'
'The integration between Sigma and Snowflake's Semantic Views marks an important step forward in enabling enterprises to leverage the state-of-the-art AI solutions available with Snowflake Intelligence and Cortex Analyst,' said Carl Perry, Head of Analytics, Snowflake. 'This advancement helps our customers maximize the value of their data within Snowflake's AI Data Cloud through AI and BI experiences, creating more efficient and powerful workflows for their teams.'
'This is a major leap forward in delivering a consistent, governed experience powered entirely by Snowflake,' added Palmer. 'Sigma is building toward a future where every layer of the data stack speaks the same language—defined once, executed everywhere.'
Bringing Structure to Unstructured Data - Powered by Cortex AISQL
Also announced today at Snowflake Summit 2025, is the news that Sigma is among the first analytics platforms to fully support Snowflake AI SQL, a new capability that lets users query unstructured data—like contracts, receipts, product specs, and image files—as if it lived in a table. This news comes on the heels of Sigma's recent launch of its new File Column Type feature, allowing end users to connect unstructured content with structured data for the first time, making complex, real-world workflows fully executable inside Sigma.
Teams can upload files with Sigma, run them through Snowflake's powerful LLM-based functions, and analyze the structured results alongside traditional datasets—no pipelines and no special tools required.
'For decades, legacy BI tools assumed your data was clean, structured, and waiting politely in rows and columns,' said Palmer. 'But some of the most important business decisions are made with the messy stuff: legal documents, compliance PDFs, screenshots, receipts, product specs, and annotated images. Historically, those formats required a human in the loop: to read, interpret, and manually extract insights. That's the bottleneck AI SQL removes. Sigma and Snowflake turn human knowledge into scalable systems, unlocking entirely new types of analysis across industries and teams.'
'Every organization recognizes the potential of AI. But too often, harnessing AI means overcoming complex infrastructure, performance limitations, high costs, and a reliance on engineers to build custom pipelines,' said Perry. 'We're removing those barriers, whether it's enabling anyone to analyze and act on all their data with Cortex AISQL or accelerating migrations off legacy systems through SnowConvert AI. By empowering teams to move faster, work smarter, and turn data into real impact, we're reimagining analytics for the AI era.'
Snowflake's AI SQL functions analyze the content using LLMs, and Sigma picks up the structured output and renders it live in dashboards or workflows.
This unlocks transformative use cases:
Process thousands of vendor contracts
Review receipts as part of claims workflows
Extract key clauses from dense legal agreements
Attach evidence to operational data for full-context analytics
There's no need for custom pipelines, reformatting, or manual review. Just files in, answers out. Governed, traceable, and ready to use.
Joint customers can start using the semantic layer integration immediately through their existing Snowflake and Sigma environments as well as the full support for Cortex AISQL. For more information on Sigma's integration with Snowflake Semantic Views, click here and for more information on Snowflake's AI SQL function, read here.
ABOUT SIGMA
Sigma is business intelligence built for the cloud. With a spreadsheet UI, business users can work in the formulas and functions they already know, while more technical users can write SQL and apply AI models to data. Sigma queries the cloud warehouse directly, making it incredibly fast and secure—data never leaves the warehouse, and Sigma can analyze billions of rows in seconds. Beyond dashboards and reports, teams use Sigma to build custom data apps, which integrate live data with end user input. Sigma is the first analytics platform to enable data writeback, and continues to lead the market with innovation across AI, reporting, and embedded analytics.
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