News
Snowflake announced general availability of Snowflake Intelligence — its enterprise intelligence agent — on November 4, 2025. The platform is now available to more than 12,000 global customers, marking one of the company’s largest AI releases to date. Designed to democratize AI and data access across the enterprise, Snowflake Intelligence allows any employee to ask questions in natural language, explore multimodal data and generate deep analytical insights without writing code.
The company reports that 1,000+ customers have already deployed over 15,000 AI agents using Snowflake Intelligence in just the past three months.
Customers adopting the platform span industries and use cases — from Cisco and Fanatics to Toyota Motor Europe, USA Bobsled/Skeleton, TS Imagine and Wolfspeed — all using Snowflake Intelligence to speed decision-making, automate analysis and eliminate data silos.
Your toughest business questions just met their match. Meet Snowflake Intelligence—now generally available! 🔥
— Snowflake (@Snowflake) November 4, 2025
We've launched a new category of AI: enterprise intelligence agents. This isn't just another chatbot; it’s a trusted agent that manages context, refines its approach,… pic.twitter.com/Lt8WCduazs
Table of Contents
- What Snowflake Intelligence Brings to the Enterprise
- Rapid Adoption Across Industries
- New Tools to Build Custom Data Agents
- Snowflake and SAP Announce New Enterprise Data Partnership
- Why This Matters for Enterprise AI
What Snowflake Intelligence Brings to the Enterprise
“Snowflake Intelligence democratizes the power of AI so every employee can make smarter and faster decisions."
- Christian Kleinerman
EVP of Product, Snowflake
Snowflake Intelligence unifies structured and unstructured data, documents and third-party sources such as Salesforce Data 360 via Zero Copy sharing. Instead of relying on analysts to write complex SQL or extract data manually, employees can securely query all enterprise data in plain language.
Key capabilities include:
- Multimodal data insight from tables, documents, knowledge bases, and external applications
- Enterprise-ready governance and security, ensuring confidential data remains protected
- Natural language querying powered by leading AI models from providers such as Anthropic
- Up to 3X faster text-to-SQL performance, powered by Snowflake’s AI Research innovations
- Agent GPA (Goal, Plan, Action) framework, a new evaluation method that detects up to 95% of errors, achieving near-human accuracy in error detection
Enterprises can now convert complex analytical workflows into conversational queries, a shift Snowflake says will “fundamentally change how customers innovate for years to come.”
Related Article: AI Agent Development Guide: No-Code Builders, Frameworks and Safe Scaling
Rapid Adoption Across Industries
Snowflake customers cite automation, faster development cycles and faster analytics as core reasons for adoption:
- Toyota Motor Europe reduced agent deployment timelines from months to weeks and cut data movement risk
- Wolfspeed is troubleshooting equipment issues in two minutes instead of two hours
- TS Imagine users assess performance in minutes rather than days
- Fanatics is building real-time, addressable audiences for advertising and customer experience
- Cisco is developing internal AI agents to improve automation across teams
- The USA Bobsled/Skeleton Team is using AI insights to improve athletic performance
Snowflake’s own sales and marketing teams also use Snowflake Intelligence internally, with more than 6,000 employees asking over 12,500 questions per week, according to the company.
New Tools to Build Custom Data Agents
To help enterprises scale AI agents in production environments, Snowflake announced multiple innovations now generally available:
| Innovation | What It Enables |
|---|---|
| Cortex Agents | Build custom data agents that plan tasks, use tools and interact with structured and unstructured data |
| Managed MCP Server | Standardized, secure interoperability with external agents like Anthropic, Cursor and Salesforce Agentforce |
| Cortex Knowledge Extensions | Use trusted third-party data from providers like FactSet, IPinfo and MSCI |
| Sharing of Semantic Views | Share and reuse trusted business logic across apps and teams |
These offerings standardize how enterprises deploy multi-agent workflows while maintaining governance and data privacy standards.
Snowflake and SAP Announce New Enterprise Data Partnership
“Enterprises can now innovate faster with Snowflake and SAP BDC and seamlessly share data between the platforms."
- Christian Kleinerman, EVP of Product
EVP of Product, Snowflake
In a separate announcement, Snowflake and SAP unveiled a new collaboration that connects Snowflake’s AI Data Cloud with SAP Business Data Cloud (SAP BDC) to help enterprises build AI applications and analytics on semantically rich business data.
Key elements of the partnership include:
- SAP Snowflake solution extension, targeted for general availability in Q1 2026
- Zero-copy, bidirectional data sharing between Snowflake and SAP BDC
- SAP BDC Connect for Snowflake, planned for H1 2026
The partnership will allow customers to unify SAP and non-SAP data without duplication, while leveraging Snowflake’s AI, analytics and storage capabilities.
Early adopters include AstraZeneca, which says real-time data access with SAP and Snowflake will accelerate drug development efforts and patient-impacting research.
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Why This Matters for Enterprise AI
For global organizations struggling with fragmented data, manual analytics and slow decision-making, Snowflake Intelligence is designed to act as a single conversational interface for trusted enterprise information. Unlike consumer chatbots, it operates inside existing corporate governance frameworks and can analyze secure internal datasets — a key requirement for regulated industries.
With more than 12,000 customers and rapid AI agent deployment in production environments, Snowflake’s strategy positions it as both an AI platform and a data foundation powering enterprise automation and multi-agent systems.
