Snowflake unveils AI tools for data analytics, migration
The company announced its expansion of enterprise-grade AI with the introduction of Cortex AISQL and SnowConvert AI, designed to enable customers to extract insights from diverse data types while reducing operational costs and complexity.
Cortex AISQL incorporates generative AI directly into database queries, allowing teams to analyse and act on multiple kinds of data—ranging from structured numbers to text, images and audio—while using the SQL syntax familiar to data professionals. The solution is intended to bring what Snowflake describes as "industry-leading performance and up to 60% cost savings when filtering or joining data." Organisations such as Hex, Sigma, and TS Imagine are among those already leveraging the capabilities of Cortex AISQL.
SnowConvert AI addresses a common challenge faced by enterprises: moving data from existing warehouse and analytics platforms to modern systems. The tool uses AI automation to ease migrations from providers such as Oracle, Teradata, and Google BigQuery, reducing the need for manual re-coding and lowering the risks typically associated with large-scale data projects.
"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. 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," Carl Perry, Head of Analytics at Snowflake, commented on the new developments.
"In capital markets, speed and precision are everything. For years, SQL has been the gold standard for transforming data — and now, with Cortex AISQL, we're extending that power to unstructured text. With AISQL, our teams can analyze documents, extract insights, and build intelligence directly in the language they already know — all without complex engineering workflows. It's a game-changer for how fast we can respond to markets and deliver value to clients, while leveraging the Snowflake architecture for high performing SQL processing," Thomas Bodenski, Chief Operating Officer of TS Imagine, said, sharing his perspective as a customer.
Snowflake's Cortex AISQL harnesses generative AI—powered by models from providers such as Anthropic, Meta, Mistral, and OpenAI—to introduce advanced query functions into standard SQL. The result is that data analysts can use AI-powered functionalities within the security perimeter of the existing data cloud, without requiring specialist coding or external tools. According to Snowflake, ongoing performance optimisations have demonstrated between 30% and 70% improvements depending on the dataset, and up to 60% cost savings for certain operations.
The integration enables organisations to break down traditional data silos. For example, analysts can merge structured customer data with unstructured data like chat transcripts, images, or social media content, and perform tasks including image classification, call transcript analysis and anomaly detection entirely through SQL queries.
SnowConvert AI, meanwhile, is designed to make IT infrastructure upgrades more efficient, automating code conversion, report migration and data validation to streamline the transition to new platforms. By accelerating the code conversion and testing phases by two to three times, the tool is aimed at reducing the overall timeline and resource demands associated with digital transformation.
Alongside these tools, Snowflake also announced updates to its platform to further support analytics on open source data formats such as Apache Iceberg tables, and launched Standard Warehouse - Generation 2, which introduces hardware and software improvements to boost analytics performance by 2.1 times over previous editions.
With the introduction of these AI-powered features, Snowflake is positioning its data cloud as a central platform for enterprises seeking to modernise analytics and data handling capabilities, and to extract actionable business insights from both structured and unstructured sources.
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