• Snowflake Cortex AI for Financial Services allows financial institutions to unify their data ecosystems and easily deploy AI models, apps, and agents on top of that AI-ready data in Snowflake
• Snowflake’s MCP Server connects third-party data from partners such as FactSet, MSCI, Nasdaq eVestment^®, and The Associated Press, which customers will be able to leverage in apps and agent platforms like Anthropic, CrewAI, Cursor, Devin by Cognition, Salesforce’s Agentforce, UiPath, and Windsurf, to accelerate the delivery of context-rich AI apps and agents

Snowflake (NYSE: SNOW), the AI Data Cloud company, today announced Snowflake Cortex AI for Financial Services, a comprehensive suite of AI capabilities and partnerships that empower financial services companies to unify their financial data ecosystem and securely deploy AI models, apps, and agents with that data — while offering rigorous security and compliance controls required in regulated industries.

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Snowflake Unveils Cortex AI for Financial Services: Enterprise-Ready AI Built to Scale

Snowflake also announced a new managed Model Context Protocol (MCP) Server (now in public preview), enabling organizations to easily and securely harness their own proprietary data and third-party data in Snowflake from partners including FactSet, MSCI, Nasdaq eVestment^®, and The Associated Press. Customers will then be able to leverage this managed MCP Server to connect their data with apps and agent platforms like Anthropic, CrewAI, Cursor, Devin by Cognition, Salesforce’s Agentforce, UiPath, and Windsurf, to build context-rich AI agents and apps. With these innovations, customers across financial services and other industries can rapidly deploy trusted AI through solutions that are purpose-built for their specific needs, while providing the broader industry with seamless, secure connectivity across their data and AI ecosystems.

“The financial services industry has long been a leader in embracing new technology, and AI is no exception. However, the industry faces unique challenges in navigating fragmented data, robust compliance requirements, and the need for airtight security and governance,” said Baris Gultekin, VP of AI, Snowflake. “By bringing AI directly to where their data already lives and enabling secure interoperability with remote agents, Snowflake is making it easier for highly regulated industries like financial services to power business-critical use cases and tap into a unified ecosystem of best-of-breed data, AI, and apps.”

Introducing Cortex AI for Financial Services

Cortex AI for Financial Services enables enterprise-ready agents to accelerate complex financial tasks — including market analysis, quantitative research, fraud detection, customer support, and claims management — saving enterprises time, reducing operational costs, and delivering faster insights. Snowflake’s MCP Server extends this capability by enabling industry-wide interoperability, securely connecting to Snowflake data, as well as third-party data and apps.

The Cortex AI for Financial Services ecosystem offers high-quality, trusted data from leading financial data providers and publishers that organizations can seamlessly integrate with their AI apps and agents — including structured data providers like CB Insights, Cotality™, Deutsche Börse, MSCI, and Nasdaq eVestment^® through Sharing of Semantic Views (generally available soon); and unstructured data publishers like CB Insights, FactSet, Investopedia, The Associated Press, and The Washington Post through Cortex Knowledge Extensions (now generally available). By combining industry-specific data from leading financial institutions and publishers — such as market analysis, expert research, business content, and news — with their own proprietary data in Snowflake, financial services companies can get deeper insights, accuracy, and results from their AI.

Within the Cortex AI for Financial Services suite, the following product features empower finance professionals to accelerate business-critical use cases, including:

• Complex Machine Learning Workflows: Financial services firms rely on data scientists for risk modeling, forecasting, trading analytics, and compliance, but much of their time is spent on data preparation and repetitive coding. Snowflake Data Science Agent acts as an AI coding agent, automating data cleaning, feature engineering, model prototyping, and validation so teams can move from raw data to production-ready models faster. This means automating and streamlining models that underpin quantitative research, fraud detection, customer 360, and underwriting workflows.
• Analysis of Unstructured Data: Financial institutions sit on mountains of unstructured data such as market research, earnings call transcripts, and transaction details that require manual review or complex ETL before analysis. With Snowflake Cortex AISQL (in public preview) adding functions like AI-powered extraction and transcription (in public preview), users can efficiently process and get insights from documents, audio, and images at scale — transforming end-to-end workflows like customer service, investment analytics, claims management, and next-best action.
• Easy Access to Flexible Insights: While Data Science Agent and Cortex AISQL accelerate workflows for technical and research teams, Snowflake Intelligence (in public preview) offers business users an intuitive conversational interface to gain insights using natural language from data stored in Snowflake, as well as third-party data, apps, and agents — allowing users to quickly uncover actionable insights from both structured tables and unstructured documents. This democratizes access to data and insights across financial institutions, and eliminates the technical overhead that slows down business decision-making.

Snowflake MCP Server Extends to All Industries for Connected, Interoperable AI

AI agents extend the capabilities of large language models (LLMs) by interacting with external tools, completing complex workflows, and understanding the broader context of an organization. However, connecting these AI agents to existing enterprise systems has presented challenges, often requiring teams to spin up customized solutions for each integration, which slows down AI adoption. MCP has emerged in recent months as a solution to this problem, providing a standardized way for LLMs to integrate with data, APIs, and services. With the introduction of Snowflake MCP Server, enterprises can:

• Enable MCP Server to connect with tools built on Snowflake: Snowflake MCP Server connects Cortex Analyst and Cortex Search to external AI agents through a standards-based MCP interface, unifying structured and unstructured data retrieval. This simplifies enterprises’ application architecture and eliminates the need for custom integrations — accelerating the delivery of context-rich AI apps and agents.
• Access proprietary and third-party data shared on Snowflake with external tools: With Snowflake MCP Server, remote agents can now connect with Snowflake data — as well as third-party data shares from Snowflake Marketplace through Cortex Knowledge Extensions — enabling interoperability with the broader AI ecosystem.

Sharing of third-party data is now possible alongside tools, apps, and data sources that enterprises are already using, without sacrificing security or governance. Snowflake MCP Server can be used to connect with a variety of agentic apps and platforms, including Anthropic, Augment Code, Amazon Bedrock AgentCore, Azure AI Foundry, CrewAI, Cursor, Devin by Cognition, Glean, Kumo, Mistral AI, Salesforce’s Agentforce, UiPath, Windsurf, Workday, and WRITER.

Comments on the News:

• "Enterprises are moving from AI pilots to production, but until now, securely connecting AI to proprietary data has been a critical barrier," said Jonathan Pelosi, Head of Industry, Financial Services, Anthropic. "Our partnership with Snowflake helps solve this by using MCP to connect each organization's governed data directly to Claude. Customers can now use Claude's advanced reasoning on both structured analytics and unstructured documents via Cortex Analyst and Cortex Search, while maintaining enterprise security standards. With Claude and Snowflake, our joint customers are turning proprietary data into competitive advantage."
• “The next wave of enterprise AI hinges upon orchestrating collaborative crews of specialized agents to automate complex processes. For these agentic workflows to succeed in the enterprise, they must be grounded in secure, high-quality data,” said João Moura, Co-Founder and CEO, CrewAI. “Snowflake's launch of a managed MCP Server provides the essential, secure pipeline for our agent crews to access, analyze, and act upon governed data within the AI Data Cloud. For our joint customers, this partnership moves multi-agent systems from a theoretical concept to a practical, enterprise-ready reality, and we are thrilled to be a launch partner.”
• “The intelligence of any AI coding assistant is fundamentally constrained by the context it can access," said Ricky Doar, Head of Field Engineering, Cursor. “A managed MCP server like Snowflake's is a rich live data environment for tools like Cursor to consume essential data context and write faster, more accurate, and more secure production-ready code."
• "As a leading market data provider, we are proud to be on the cutting-edge of industry-wide advances like MCP. Providing our clients access to AI-ready data products represents a significant step forward for our clients, providing the technological foundation to unify and enrich data within modern cloud environments,” said John Costigan, Executive Vice President, Chief Data Officer at FactSet. “This collaboration underscores FactSet’s commitment to equipping financial institutions with the tools necessary to navigate evolving markets, manage risk more effectively, and foster enduring value creation."
• “At Ramp, our mission is to help businesses save time and money. A critical part of that is deeply understanding their needs from the thousands of pieces of feedback we receive,” said Ian Macomber, Head of Analytics, Ramp. “With Snowflake Cortex AI, we can securely tap into and analyze our unstructured customer data, allowing teams across Ramp to ask questions in plain English and get instant answers. Snowflake makes it easy to democratize data-driven decision-making, which enables us to innovate faster and build the best possible platform for our customers.”
• "We're excited to expand our partnership with Snowflake to deliver agent interoperability through protocols like MCP. This will enable deeper cross-platform connectivity and power more intelligent agentic experiences within Agentforce,” said Gary Lerhaupt, VP, Product Architecture, Agentforce at Salesforce. “Customers will easily be able to discover and connect to Snowflake’s MCP server directly within Salesforce AgentExchange, accelerating the development and deployment of AI agents."

Learn More:

• Double click into how Snowflake Cortex AI for Financial Services is streamlining business-critical use cases in this blog post.
• Read more about how Snowflake MCP Server is making it easier to build and deploy AI agents on enterprise data in this blog post.
• Learn more about how global organizations can get started with Snowflake Intelligence today to democratize their enterprise data in this quickstart.

Forward Looking Statements

This press release contains express and implied forward-looking statements, including statements regarding (i) Snowflake’s business strategy, (ii) Snowflake’s products, services, and technology offerings, including those that are under development or not generally available, (iii) market growth, trends, and competitive considerations, and (iv) the integration, interoperability, and availability of Snowflake’s products with and on third-party platforms. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading “Risk Factors” and elsewhere in the Quarterly Reports on Form 10-Q and the Annual Reports on Form 10-K that Snowflake files with the Securities and Exchange Commission. In light of these risks, uncertainties, and assumptions, actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. As a result, you should not rely on any forward-looking statements as predictions of future events.

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About Snowflake

Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data. More than 12,000 customers around the globe, including hundreds of the world’s largest companies, use Snowflake’s AI Data Cloud to build, use and share data, applications and AI. With Snowflake, data and AI are transformative for everyone. Learn more at snowflake.com (NYSE: SNOW).

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