Snowflake (NYSE: SNOW) has announced Snowflake Cortex AI for Financial Services, a new suite of AI capabilities and partnerships designed to enable financial services companies to unify their data ecosystems and securely deploy AI models, applications, and agents. This offering includes security and compliance controls tailored for regulated industries.
The company also introduced a new managed Model Context Protocol (MCP) Server, now in public preview, which allows organizations to integrate their proprietary data with third-party data from partners such as FactSet, MSCI, Nasdaq eVestment®, and The Associated Press. This server facilitates connections between data and AI agent platforms like Anthropic, CrewAI, Cursor, Devin by Cognition, Salesforce’s Agentforce, UiPath, and Windsurf, to build context-rich AI agents and applications.
According to Baris Gultekin, VP of AI at Snowflake, the financial services sector, while quick to adopt new technology, faces specific challenges including data fragmentation, complex compliance requirements, and stringent security and governance needs. Snowflake’s approach aims to address these by bringing AI directly to the data and enabling secure interoperability with remote agents, thereby supporting critical use cases in highly regulated environments.
Cortex AI for Financial Services is designed to accelerate complex financial tasks such as market analysis, quantitative research, fraud detection, customer support, and claims management. The goal is to reduce operational costs, save time, and deliver insights more rapidly. The MCP Server extends this capability by ensuring industry-wide interoperability, securely linking to Snowflake data, third-party data, and applications.
The Cortex AI for Financial Services ecosystem provides access to data from leading financial data providers and publishers. This includes structured data from providers like CB Insights, Cotality™, Deutsche Börse, MSCI, and Nasdaq eVestment® through Sharing of Semantic Views (to be generally available soon). Unstructured data is available from publishers such as CB Insights, FactSet, Investopedia, The Associated Press, and The Washington Post via Cortex Knowledge Extensions (now generally available). By combining this industry-specific data with their own proprietary data within Snowflake, financial services companies can achieve enhanced insights, accuracy, and results from their AI initiatives.
Key product features within the Cortex AI for Financial Services suite are designed to accelerate business-critical use cases. The Snowflake Data Science Agent automates machine learning workflows, including data cleaning, feature engineering, model prototyping, and validation, to support tasks like risk modeling, forecasting, trading analytics, compliance, fraud detection, customer 360, and underwriting. Snowflake Cortex AISQL, currently in public preview, includes AI-powered extraction and transcription functions to process insights from documents, audio, and images at scale, benefiting workflows such as customer service, investment analytics, and claims management. For business users, Snowflake Intelligence, also in public preview, offers a conversational interface for gaining insights using natural language from both structured and unstructured data, aiming to democratize data access and accelerate decision-making.
The Snowflake MCP Server’s capabilities extend beyond financial services. AI agents expand the functionality of large language models (LLMs) by interacting with external tools and managing complex workflows. However, connecting these agents to existing enterprise systems has posed integration challenges. The MCP aims to provide a standardized method for LLMs to integrate with data, APIs, and services. With the Snowflake MCP Server, enterprises can connect Cortex Analyst and Cortex Search to external AI agents via a standards-based MCP interface, unifying structured and unstructured data retrieval and simplifying application architecture. Additionally, remote agents can access proprietary and third-party data shared on Snowflake, including data from Snowflake Marketplace via Cortex Knowledge Extensions, ensuring interoperability without compromising security or governance. The server supports connections with various agentic applications 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.
Jonathan Pelosi, Head of Industry, Financial Services at Anthropic, noted the challenge of securely connecting AI to proprietary data and stated that the partnership with Snowflake addresses this by using MCP to connect governed data directly to Claude. João Moura, Co-Founder and CEO of CrewAI, emphasized the need for secure, high-quality data for collaborative agent workflows, identifying Snowflake’s managed MCP Server as a secure pipeline. Ricky Doar, Head of Field Engineering at Cursor, commented that a managed MCP server like Snowflake’s provides a crucial data environment for tools to produce accurate code. John Costigan, Executive Vice President, Chief Data Officer at FactSet, highlighted the importance of providing AI-ready data products to clients for data unification and risk management. Ian Macomber, Head of Analytics at Ramp, mentioned using Snowflake Cortex AI to analyze unstructured customer data and enable data-driven decision-making. Gary Lerhaupt, VP, Product Architecture, Agentforce at Salesforce, expressed enthusiasm for expanding their partnership with Snowflake to deliver agent interoperability through protocols like MCP, facilitating deeper cross-platform connectivity and intelligent agentic experiences within Agentforce.
