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Snowflake Launches AI Data Agents: Future of Enterprise AI

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Snowflake Intelligence is a groundbreaking platform that will empower business users to create data agents, so they can analyze, summarize, and take action from their enterprise data

Snowflake, the AI Data Cloud company, announced at its annual developer conference, BUILD 2024, Snowflake Intelligence (in private preview soon), a new platform that will enable enterprises to easily ask business questions across their enterprise data to unlock data-driven answers, and in just a few steps, create data agents that take action on those insights.

Snowflake Intelligence ushers in a new era for how users can interact with their enterprise data, building on Snowflake’s easy, efficient, and trusted AI services. Snowflake Intelligence will give businesses enterprise-grade data agents built on Snowflake’s data foundation that efficiently get organizational work done, while protecting customer IP and delivering answers backed by reliable, trusted enterprise data. Snowflake Intelligence enables everyone to easily access and harness the full potential of their data, and seamlessly connect with third-party tools — including sales transactions in a database, documents in knowledge bases such as SharePoint, productivity tools such as Slack, Salesforce, and Google Workspace, alongside business intelligence data in Snowflake — so they can talk to their data using natural language. Snowflake Intelligence also supports API calling to enable actions and data modifications to advance business users’ work forward.

“With Snowflake Intelligence, teams can easily create data agents that allow business users to talk to their enterprise data using natural language, and then analyze, summarize, and take action on those results from one unified platform,” said Baris Gultekin, Head of AI, Snowflake. “Snowflake Intelligence represents the next step in Snowflake’s AI journey, further enabling teams to easily, and safely, advance their businesses with data-driven insights they can act on to deliver measurable impact.”

Snowflake Intelligence Redefines Business Intelligence and Data-Driven Action for All Users

Today, many organizations struggle to make informed decisions due to fragmented governance across their data sources, infrastructure silos between unstructured and structured data formats, and limited access to analysts who can write code and connect the dots across the business. Snowflake Intelligence will address all of these challenges, by first helping organizations integrate various data systems with a single governance layer. With that foundation in place, teams can then accurately process and retrieve data from both unstructured and structured data sources using natural language, truly democratizing data and AI access, while empowering any user to take data-driven actions.

Also Read: Ataccama Debuts AI Agent for Data Management

In turn, this enables users to define the datasets they want to ask questions to, which can include PDFs or tables in a database, without having to write any code. As questions get asked, Snowflake Intelligence then puts data agents into action to do analysis, summarization or generation tasks. Data agents can also use APIs or write to Snowflake tables to record business decisions, making it easier to track results and measure impacts.

Snowflake Cortex AI and the Snowflake Horizon Catalog – the AI Engine and Governance Framework Behind Snowflake Intelligence

In order to scale their AI and business needs, organizations require enterprise-grade solutions, and Snowflake Intelligence is designed to deliver on this for organizations. Snowflake Intelligence uses Snowflake Cortex AI, Snowflake’s fully managed AI service that provides a suite of generative AI features, as the AI engine powering its capabilities, and was built using Cortex Search (now generally available) to run queries on unstructured data, and Cortex Analyst (in public preview) to run queries on structured data. New innovations to Cortex AI enable more users to harness Cortex AI’s serverless large language model (LLM) inference, fine-tuning, retrieval augmented generation (RAG), and text-to-SQL, so data teams can process unstructured data while developers quickly build enterprise AI apps.

Snowflake Intelligence also comes natively integrated with Snowflake Horizon Catalog at the foundational level, making it compatible with industry leading open formats like Apache Iceberg™ and Apache Polaris™ (Incubating). This combination delivers strong enterprise-grade compliance, security, privacy, discovery, and collaboration capabilities. This extends across clouds and regions, so organizations can spend less time worrying about implementing security and governance to protect their data, and more time driving impact. Snowflake is enhancing the Horizon Catalog so all users gain deeper capabilities to deliver secure and governed AI at scale.

Source: Businesswire

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