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Excited to share that Claude Opus 4.8 is available now on Snowflake Cortex AI in public preview. As a launch partner with Anthropic, Snowflake brings Opus 4.8 directly into Cortex Code, Cortex Agents, Cortex AI Functions, Cortex Inference, and Snowflake Intelligence—all within Snowflake’s secure, governed AI platform. That means teams can build and scale more advanced agentic AI workflows with stronger reasoning, code generation, and long-running task execution while keeping enterprise governance built in. Details: https://bit.ly/4fdPPFk

Cortex plus 4.8 is the enterprise version of the same shift: the model moved from answering to executing against your governed data. So your data model and access controls, not the LLM, decide whether the agent ships value or chaos. my take: https://www.linkedin.com/posts/michalpiszczek_anthropic-just-shipped-claude-opus-48-the-share-7465810610719678464-AB1a/

Been using Opus 4.7 heavily within Snowflake Cortex AI for complex migration and data transformation analysis work, and the reasoning capability has been genuinely impressive. Especially useful for large-scale SQL validation, lineage tracing, mapping analysis, and understanding legacy billing flows across systems. Excited to explore what Opus 4.8 brings next 🚀

I didn't even hear they opus 4.8 got launched, and it's already live in Snowflake.

Snowflake’s integration of Claude Opus 4.8 into Cortex represents a shift toward embedding agentic AI directly within enterprise data infrastructure. By combining reasoning models with governed data systems, it enables automated analysis, code generation, and workflow execution while preserving security and compliance boundaries.

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Exciting advancement for enterprise AI. Integrating Claude Opus 4.8 with Snowflake Cortex AI will significantly enhance governed, scalable, and intelligent AI workflow automation for data-driven organizations.

The key part here is that the AI is operating where the governed data already lives. For financial services firms, agentic workflows are only practical when they respect security, access controls, auditability, and the existing data environment. That is usually the difference between an interesting AI demo and something a firm can actually put into production.

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