Snowflake Cortex Analyst
AI data analysis agents
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What is Snowflake Cortex Analyst
Snowflake Cortex Analyst is a natural-language-to-SQL analysis capability within the Snowflake platform that helps users ask questions in plain language and receive generated SQL and results against governed data. It targets analysts, data engineers, and application teams building conversational analytics experiences on top of Snowflake data. The product is designed to work with Snowflake’s security, governance, and semantic modeling patterns so teams can control what data is queried and how metrics are interpreted. It is typically used for self-service analytics, embedded analytics, and accelerating ad hoc analysis on Snowflake-hosted datasets.
Native Snowflake data access
It runs where the data already resides in Snowflake, reducing the need to move data into a separate BI or agent platform for analysis. This can simplify authentication, authorization, and auditing because it aligns with Snowflake’s existing access controls. It also fits teams standardizing on Snowflake for warehousing/lakehouse workloads and wanting AI-assisted querying without additional data replication.
NL-to-SQL transparency
The system produces SQL as an explicit artifact, which allows technical users to review, validate, and optimize generated queries. This supports governance and troubleshooting workflows that are harder when an agent only returns narrative answers. It also helps teams operationalize outputs by reusing generated SQL in dashboards, pipelines, or applications.
Governance-aligned analytics patterns
Cortex Analyst is designed to operate with governed datasets and semantic definitions so organizations can constrain what the agent can query and how business terms map to data. This can reduce ambiguity in metric definitions compared with purely free-form querying. It is well-suited to enterprise environments that require consistent definitions, role-based access, and auditability.
Snowflake-centric dependency
The capability is tightly coupled to the Snowflake ecosystem, so organizations with significant data outside Snowflake may need additional integration work or accept partial coverage. This can limit portability of agent experiences across multiple warehouses or analytics stacks. It may also increase platform lock-in for teams that want vendor-neutral conversational analytics.
Requires strong data modeling
Answer quality depends on well-structured schemas, clear naming conventions, and curated semantic definitions. Without disciplined modeling and governance, natural-language questions can map to incorrect tables, joins, or metrics. Teams often need data engineering effort to prepare datasets for reliable self-service use.
Not a full BI suite
Cortex Analyst focuses on conversational analysis and SQL generation rather than end-to-end BI capabilities such as rich dashboard authoring, pixel-perfect reporting, and broad visualization workflows. Many organizations will still rely on separate tools for complex reporting, interactive dashboards, or product analytics instrumentation. This can introduce a multi-tool workflow for stakeholders who expect a single interface for analysis and reporting.
Plan & Pricing
Pricing model: Pay-as-you-go (Snowflake Credits based)
Billing units (official):
- Cortex Analyst (Cortex Analyst API): 67 Credits per 1,000 messages (i.e., 0.067 Credits per message). (applies when using the Cortex Analyst API)
- Cortex Analyst (when invoked via Snowflake Intelligence or Cortex Agents): token-based rates (Credits per 1,000,000 tokens) that vary by model. Representative rates from the official table (Credits per 1,000,000 tokens):
- claude-3-5-sonnet: Input 3.14, Output 15.69.
- mistral-large2: Input 2.09, Output 6.28.
- openai-gpt-4.1: Input 2.30, Output 9.21.
- claude-haiku-4-54: Input 1.15, Output 5.75. (See the official Service Consumption Table for the full model list and rates.)
Additional charges & notes (official):
- The Cortex-Analyst AI charge covers the AI/text-to-SQL generation only. Executing the generated SQL runs on your Snowflake virtual warehouse and incurs separate warehouse compute credits (per your warehouse configuration).
- Provisioned Throughput (PTU) reservations are available for certain Snowflake AI features (reserve continuous access at a fixed PTU rate). Example: AWS PTU price = 0.08 Credits per PTU per hour (see Provisioned Throughput table).
- Other serverless/cloud-service charges (Cloud Services credits) and unit charges may apply as described in the Service Consumption Table and Documentation.
Example costs (official units, credits):
- 1,000 Cortex Analyst API messages = 67 Credits.
- 1 Cortex Analyst API message = 0.067 Credits.
- 1,000,000 input tokens with claude-3-5-sonnet = 3.14 Credits; 1,000,000 output tokens = 15.69 Credits.
Discount/options:
- Provisioned Throughput reservations (reserve PTUs for a fixed term) — PTU rates listed in the Service Consumption Table; subject to minimum PTU quantities and Snowflake approval.
- Consumption is metered in Snowflake Credits; standard capacity/commitment ordering and billing terms may apply per customer Order Form (see Documentation and Order Form).
Key official references:
- Snowflake Service Consumption Table (effective Feb 18, 2026): lists "Cortex Analyst 67 Credits per 1,000 messages" and the per-model token credit rates.
- Cortex Analyst Documentation (Cost considerations): notes message-based billing for the Cortex Analyst API and that warehouse costs apply when executing generated SQL.
Seller details
Snowflake Inc.
Bozeman, Montana, USA
2012
Public
https://www.snowflake.com/
https://x.com/SnowflakeDB
https://www.linkedin.com/company/snowflake-computing/
