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Your Snowflake Team
Snowflake's FinancialServices Data Cloud
Understanding the basics
Cortex for Financial Services
Snowflake Intelligence*
Conversational AI for business. Ask questions across structured and unstructured data and get intelligent insights instantly, all within Snowflake. Easy to deploy, and enterprise-ready for business users.
Cortex Agents†
Orchestrate across both structured and unstructured data to retrieve and synthesize high-quality data insights.
Cortex AISQL†
Transform multimodal data into insights using familiar SQL syntax. Analyze text, images and audio alongside structured data, all within Snowflake's unified platform. Build AI-powered analytics pipelines without complex coding or data movement.
Cortex Analyst
Use AI to accurately convert natural language to SQL; Simple to use, cost-efficient to scale.
Cortex Search
Find information by asking questions within a given set of documents with fully managed text embedding, hybrid search (semantic + keyword) and retrieval.
Large language models (LLMs)
Access industry-leading large language models including Anthropic Claude, Meta Llama and Mistral Large 2 using serverless functions and APIs.
How Financial Services Institutions Should Think About Unstructured Data — and Why It Matters for a Sound Enterprise AI Strategy
Snowflake Cortex AI provides a secure, scalable, and cost-effective platform for financial services to manage unstructured data.
It offers a full-stack AI solution that handles the entire process, from data ingestion to the deployment of AI-driven applications.
Cortex AI lets businesses use powerful AI models directly on their data, ensuring data security and streamlined governance without sending data to external models.
Snowflake Cortex Analyst: Preventing Join Hallucinations and Double Counting
We’re thrilled to announce that we’ve expanded our join capabilities beyond simple star and snowflake schemas to support multifact tables and measures spread across multiple tables — all while maintaining the accuracy of your queries. At the core of this achievement lies a powerful primitive: directed graphs. This article will dive into the challenges of complex schemas, explain how directed graphs enable us to solve them, and show how we use them to prevent join hallucination and double counting.
Evaluating and Optimizing Search Quality: Seamlessly Tune Your Snowflake Cortex Search Service with an LLM Judge
What if there was a way to serve high-quality results to the user without spending days and resources tuning each parameter? What if you could rely on an autonomous pipeline that could do this for you? In this investigation, we find that, with the use of LLMs, you can build high-quality evaluation data sets for iteration without spending precious human hours to improve your search system — all with Snowflake.
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