Snowflake launches AI innovations, accelerating efficient and trusted AI into production with enterprise data

4 weeks ago

Snowflake has announced new AI features to its platform, enabling developers to effortlessly build conversational apps for structured and unstructured data with high accuracy, efficiently batch inference of large language models (LLM) for natural language processing (NLP) pipelines, and train custom models with GPU-powered containers — all with built-in governance, access controls, observability, and safety guardrails ensuring that AI security and trust remain at the forefront. The launches make it easier for companies to deliver simple, effective and reliable AI solutions for all data, including structured and unstructured data.

Snowflake is also introducing Snowflake Intelligence (available soon in private preview), a new platform where companies can ask questions of their business data, and based on the results, quickly create data agents that take action based on these insights, as well as advancements in Cortex AI that empower companies to develop high-quality conversational applications. This and much more was presented during BUILD 2024 – Snowflake’s annual event for developers.

Snowflake enables companies to unlock value across data silos

Enterprise data is often spread out in silos on different storage platforms, making it difficult to use to create value. To improve the conditions for companies to create value from their data, Snowflake has launched the Snowflake Open Catalog, now publicly available. It allows companies to easily integrate and secure data within open lakehouse structures, such as Apache Iceberg based systems. The service ensures consistent governance and management across different engines, providing flexibility, while maintaining reliability, security and scalability.

To help businesses scale out unnecessary expenses, improve performance, and transform data lakes into more open lakehouse structures with Apache Iceberg, a range of new streaming, data ingestion, change data capture pipelines, and integrations are also being launched.

Snowflake’s service for analyzing unstructured data, Document AI, is now available on AWS and Microsoft Azure. Powered by Snowflake’s advanced Arctic-TILT model, Document AI extracts valuable insights from text-heavy information and other elements in documents, such as logos and handwritten text. The service has already been adopted by several large organizations to analyze text-heavy documents for valuable insights using NLP.

The future of Data Agents for Enterprise AI

Snowflake Intelligence, soon available in private preview, will allow users to ask natural language questions of their business data to enhance understanding, and generate actionable insights.

Snowflake Intelligence will provide access to best-in-class data agents built on Snowflake’s data foundation, while protecting corporate IP and delivering answers based on credible corporate data. In addition, Snowflake Intelligence makes it easy to access and utilize the full potential of both on-premises data and that found in various third-party tools such as SharePoint, Slack, Salesforce, and Google Workspace.

Build high-quality conversational apps – faster

Thousands of companies worldwide rely on Cortex AI to scale and deploy their AI applications. Snowflake’s latest releases for the platform make it easier for companies to build trusted AI apps with both structured and unstructured data sources, easier orchestration, and built-in evaluation and monitoring. Here are some of the key launches for Snowflake Cortex AI.

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