Contact Centers are a critical business function for a Payer/Health Plan. Today, there is heightened focus on them, particularly with the growing market demand for customer-centric experiences in healthcare. Improving the operational efficiency of contact centers and reducing agent burnout are also key priorities for all enterprises.

Watch this teaser to learn more about the rapid advancements in pharmaceutical manufacturing and the need for updated regulatory guidance due to new multimodal delivery techniques.

Learn how the AI Data Cloud for Healthcare and Life Sciences is enabling life sciences organizations like yours to drive greater personalization in their marketing. Check out this short teaser video and contact your Snowflake account representative to learn more.

Learn how the AI Data Cloud for Healthcare and Life Sciences is enabling sales reps with insights on HCP details, prescribing trends, clinical trials, product information and much more using Cortex AI.

Learn how the AI Data Cloud for Healthcare and Life Sciences is enabling life sciences organizations to increase patient conversion rates with personalized marketing leveraging graph analytics and gen AI. Check out this short teaser video and contact your Snowflake account representative to learn more.

Learn how to leverage the power of Snowflake to tap into unstructured health data of patients and effectively run analytics on top of this data — which is critical to building a holistic patient profile and ensuring health outcomes through data-driven insights. 

Global research shows that enterprises are winning big with generative AI. We dove into their strategies and measured their outcomes.

How leaders like Bayer and Siemens Energy use generative AI to increase revenue, improve productivity and better serve customers

There are incredible opportunities for the healthcare and life sciences industry to use generative AI to make changes that will have lasting, positive impacts on society. Finding cures to address the climbing cancer rates worldwide is reason enough.

A strong data strategy uses an enterprise's data to drive business success. This report, featuring insights from chief data officers, explores how they measure the effectiveness of AI, communicate its value for investment, use metrics throughout the adoption process, and foster critical partnerships between technology and business teams.

AI is transforming every major industry, and its potential use cases are vast. Research shows that for organizations seeking increased efficiency, improved customer experience, reduced costs and more, AI delivers value. In this guide, we explore myriad ways that organizations are leveraging data and AI to drive success. 

As generative AI (gen AI) adoption transforms the competitive landscape, businesses without a strong data strategy will find their ambitions limited, according to a new report by MIT Technology Review Insights, in partnership with Snowflake.

Snowflake Openflow is an integration service that connects any data source and any destination with hundreds of processors supporting structured and unstructured text, images, audio, video and sensor data. Built on Apache NiFi, Openflow lets you run a fully managed service in your own cloud for complete control.

Snowflake's Document AI is a feature that uses the Arctic-TILT large language model (LLM) to extract data from various document formats. It can pull information from both text and graphical elements like logos, signatures, tables, and checkmarks. With Document AI, you can set up pipelines to continuously process specific document types, such as invoices, and extract data from entities and tables.

Use Cortex AISQL in Snowflake to run unstructured analytics on text and images with industry-leading LLMs from OpenAI, Anthropic, Meta, Mistral AI, and DeepSeek. All models are fully hosted in Snowflake, ensuring performance, scalability, and governance while keeping your data secure and in place.

Snowflake Intelligence uses agents, which are AI models that are connected to one or more semantic views, semantic models, Cortex search services, and tools. Agents can answer questions, provide insights, and show visualizations. Snowflake Intelligence is powered by Cortex AISQL, Cortex Analyst, and Cortex Search.

Accelerate machine learning from prototype to production with distributed GPUs or CPUs on the same platform as your governed data. Streamline model development and MLOps with no infrastructure to maintain or configure — all through a centralized UI.

Cortex Agents use tools like Cortex Analyst and Cortex Search to generate insights from both structured and unstructured enterprise data. They can also be customized with stored procedures and user-defined functions (UDFs) to deliver sophisticated, data-driven applications.