Snowflake Intelligence
Snowflake Intelligence, now rebranded as Snowflake CoWork, is an agentic analytics layer that lets users query both structured tables and unstructured documents using natural language, without writing SQL or Python.
Publisher review
Snowflake Intelligence, now rebranded as Snowflake CoWork, is an agentic analytics layer that lets users query both structured tables and unstructured documents using natural language, without writing SQL or Python. It is designed for business analysts, data stewards, and decision-makers who need instant answers from Snowflake's data cloud but lack deep technical skills. The product sits on top of Snowflake's existing warehouse infrastructure and uses a chat interface to generate automatic insights, trigger actions, and orchestrate multi-step research tasks. It is not a standalone tool; it requires an active Snowflake account and is tightly coupled to the Snowflake ecosystem, including the Snowflake Marketplace for external data enrichment.
At its core, Snowflake Intelligence employs a set of specialized agents — including a Deep Research Agent — that can decompose complex business questions into sub-queries, scan both structured columns and unstructured documents (e.g., PDFs, JSON blobs, support tickets), and return synthesized answers. The system supports automatic insight generation, meaning it can proactively surface trends, anomalies, or correlations without a user asking a specific question. For example, a user can ask "Why did our Q3 churn rate increase?" and the agent will join customer tables with call transcripts stored as unstructured data. The integration with Snowflake Marketplace allows the agent to pull in third-party datasets (e.g., demographic or economic indicators) to enrich analysis on the fly. However, each query consumes Snowflake credits, and early reports from the Cortex AI era show that a single complex query can run up costs exceeding $5,000 if not carefully governed.
In the agentic analytics market, Snowflake Intelligence competes directly with Databricks' AI/BI dashboards and Microsoft Power BI's Copilot. Databricks positions its lakehouse as a unified platform for both BI and machine learning, claiming a 20% cost reduction for customers who migrate from Snowflake. Microsoft Power BI, with its deep integration into Office 365 and Azure, offers natural-language querying through Copilot but lacks native support for unstructured data within the same query engine. Snowflake's advantage is its ability to handle structured and unstructured data in a single query without moving data to a separate vector store, but its disadvantage is that it locks users into Snowflake's compute pricing model, which can become unpredictable at scale.
The honest trade-offs are significant. First, cost transparency is poor: Snowflake does not publish per-query pricing for Intelligence, and users must rely on warehouse credits and Cortex AI consumption, which can spike without warning. Second, the product is still maturing — the rebrand to CoWork suggests ongoing feature churn, and enterprise deployment may require additional setup for role-based access controls and data governance policies. Third, while the Deep Research Agent is powerful, it can take minutes to return results for multi-step queries, which may frustrate users accustomed to sub-second BI dashboards. Finally, the tool is Snowflake-only; organizations with multi-cloud or multi-platform data strategies will find it difficult to use Intelligence without first centralizing all data in Snowflake.
How it works
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Natural language querying
Users ask questions in plain English; the agent translates them into SQL or searches unstructured data without requiring coding.
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Deep Research Agent
A multi-step agent that decomposes complex questions, runs sub-queries across tables and documents, and synthesizes a final answer.
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Automatic insight generation
Proactively surfaces trends, anomalies, or correlations without a user initiating a query, based on data patterns.
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Structured + unstructured support
Queries can join relational tables with unstructured sources like PDFs, JSON blobs, and call transcripts in one request.
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Marketplace data enrichment
Integrates with Snowflake Marketplace to pull third-party datasets (demographic, economic) into analysis on demand.
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Actionable task creation
Insights can trigger automated actions, such as sending alerts, updating dashboards, or initiating workflows.
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Unified chat interface
A single conversational UI replaces multiple BI tools, allowing users to interact with all data assets in one place.
Strengths and trade-offs
Strengths
- Supports both structured tables and unstructured documents (e.g., PDFs, JSON) in a single natural-language query without moving data to a separate store.
- Includes a Deep Research Agent that can decompose complex business questions into sub-queries and synthesize results automatically.
- Integrates natively with Snowflake Marketplace, enabling users to enrich analyses with third-party datasets without additional ETL.
- Proactively generates automatic insights — such as trend detection and anomaly alerts — without requiring a user to ask a specific question.
Trade-offs
- Cost structure is not transparent; a single complex query using Cortex AI has been reported to cost over $5,000 in credits if not governed.
- Requires an active Snowflake account and is tightly coupled to Snowflake's compute pricing, making it unsuitable for multi-cloud or non-Snowflake environments.
- The product is still maturing — rebranded from Snowflake Intelligence to Snowflake CoWork — suggesting ongoing feature changes and potential instability.
- Multi-step Deep Research Agent queries can take minutes to return results, which may frustrate users accustomed to sub-second BI dashboard responses.
Pricing context
Not explicitly published; consumption is billed through Snowflake warehouse credits and Cortex AI compute. Early reports indicate single queries can exceed $5,000 without proper governance.
Getting started with Snowflake Intelligence
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Sign up for Snowflake
Create a Snowflake account if you do not have one. Navigate to the Snowflake website and complete the registration process. Ensure your account has access to the Cortex AI features required for Snowflake Intelligence.
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Connect your data sources
Load your structured tables and unstructured documents (PDFs, JSON blobs) into Snowflake. Use the Snowflake console or SQL commands to ingest data into your warehouse. Verify that the data is accessible and properly cataloged.
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Configure access controls
Set up role-based access controls and data governance policies in Snowflake. Define which users or roles can query specific datasets. This step prevents unauthorized access and helps manage credit consumption.
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Ask a natural language question
Open the Snowflake Intelligence chat interface. Type a business question in plain English, such as 'Why did our Q3 churn rate increase?' The agent will decompose the query and search both structured and unstructured data.
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Review and act on insights
Examine the synthesized answer and any automatic insights generated. Use the results to trigger actions, such as sending alerts or updating dashboards. Monitor credit usage in the Snowflake console to avoid unexpected costs.
Frequently Asked Questions
What is Snowflake Intelligence and how does it work?
Snowflake Intelligence, now rebranded as Snowflake CoWork, is an agentic analytics layer that lets users query structured tables and unstructured documents using natural language. It uses specialized agents to decompose questions, run sub-queries, and synthesize answers without requiring SQL or Python skills.
How much does Snowflake Intelligence cost?
Snowflake Intelligence pricing is not explicitly published. It is billed through Snowflake warehouse credits and Cortex AI compute. Early reports indicate a single complex query can exceed $5,000 in credits if not carefully governed, making cost transparency a significant concern for users.
Can Snowflake Intelligence query unstructured data like PDFs?
Yes, Snowflake Intelligence supports both structured tables and unstructured documents such as PDFs, JSON blobs, and call transcripts in a single natural-language query. This eliminates the need to move data to a separate vector store, providing a unified query experience across diverse data types.
What is the Deep Research Agent in Snowflake Intelligence?
The Deep Research Agent is a multi-step agent that decomposes complex business questions into sub-queries, scans structured columns and unstructured documents, and synthesizes a final answer. It can handle tasks like analyzing churn by joining customer tables with call transcripts, but results may take minutes to return.
How does Snowflake Intelligence compare to Databricks AI/BI?
Snowflake Intelligence competes with Databricks AI/BI dashboards and Microsoft Power BI Copilot. Databricks claims a 20% cost reduction for migrating customers and offers a unified lakehouse for BI and ML. Snowflake's advantage is handling structured and unstructured data in one query, but it locks users into its compute pricing.
What are the main weaknesses of Snowflake Intelligence?
Key weaknesses include poor cost transparency, with single queries potentially costing over $5,000. The product is still maturing, as shown by its rebrand to CoWork, and multi-step queries can take minutes. It also requires an active Snowflake account, limiting use in multi-cloud environments.
Alternatives
How Snowflake Intelligence compares
Direct head-to-head against 3 competitors. Picked by 7wData.
Snowflake Intelligence
- Pricing
- Not explicitly published; consumption is billed through Snowflake warehouse credits and Cortex AI compute. Early reports indicate single queries can exceed $5,000 without proper governance.
- Target
- Snowflake Intelligence, now rebranded as Snowflake CoWork, is an agentic analytics layer that lets users query both structured tables and unstructured documents using natural language,
- Strength
- Supports both structured tables and unstructured documents (e.g., PDFs, JSON) in a single natural-language query without moving data to a separate store.
- Watch for
- Cost structure is not transparent; a single complex query using Cortex AI has been reported to cost over $5,000 in credits if not governed.
Basejump AI
- Pricing
- Free and open-source
- Target
- Teams needing open-source AI data agents
- Deployment
- Self-hosted
- Strength
- Verification system for reliable outputs
- Watch for
- Early-stage project, limited enterprise support
Databricks Lakehouse AI
- Pricing
- Premium add-on (contact sales)
- Target
- Enterprises with existing Databricks workflows
- Deployment
- Cloud or hybrid
- Strength
- Tight integration with Delta Lake
- Watch for
- Complex pricing tiers at scale
Microsoft SQL Server with Copilot
- Pricing
- $0.185/vCore/hour (Azure)
- Target
- Microsoft ecosystem enterprises
- Deployment
- Cloud or on-prem
- Strength
- Native Azure Synapse integration
- Watch for
- Limited agentic capabilities vs. Snowflake
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Sources
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