OpenAI and Snowflake have entered a multi‑year $200M partnership to bring OpenAI’s frontier models directly into Snowflake products, including Snowflake Cortex AI and Snowflake Intelligence. Enterprise teams can build AI agents and generate insights inside Snowflake, combining powerful models with the platform’s governance, security and data controls.

OpenAI × Snowflake: bringing frontier intelligence to enterprise data

OpenAI and Snowflake announced a multi‑year, $200 million partnership that brings OpenAI’s latest models directly into the Snowflake AI Data Cloud. The integration covers Snowflake’s native AI experiences—Cortex AI and Snowflake Intelligence—so customers can create AI agents, ask complex questions in natural language and automate analysis without moving data out of Snowflake.

Why this matters

Enterprise AI succeeds when two things come together: trusted data and capable models. This partnership meets in the middle. Snowflake keeps sensitive data where compliance and lineage are already enforced, while OpenAI’s models provide reasoning, planning and generation. The result: faster insights, safer automation and fewer brittle, bespoke pipelines.

What customers can do

• Ask questions in natural language against governed data and get verifiable answers backed by citations, notebook steps or SQL where applicable.

• Build AI agents for tasks like KPI analysis, anomaly triage, forecasting, and operational summaries—running within Snowflake’s controls.

• Generate content (exec briefings, product notes, remediation steps) grounded in enterprise data and policy.

• Accelerate developers and analysts with model‑assisted transformations, documentation and code suggestions tied to warehouse objects.

Where it shows up in Snowflake

• Snowflake Cortex AI: quick, natural‑language access to models for common analytics and app patterns.

• Snowflake Intelligence: a unified experience for search, insight generation and agent workflows across your data estate.

• Partner ecosystem: the integration complements existing connectors and apps, so teams can extend use cases without exporting data.

Governance & security (at a glance)

• Data stays in Snowflake: analysis runs within the platform’s security, governance and auditing boundaries.

• Role‑based access applies: models only see what a user or service role can query.

• Lineage & observability: outputs can be tied back to sources, improving trust and compliance reviews.

• Policy controls: administrators can govern which models and capabilities are available per role, project or environment.

Typical use cases

• Executive & FP&A: month‑end close briefings, variance narratives, scenario exploration across P&L datasets.

• Customer & product teams: churn predictors explained in plain English with links back to features and cohorts.

• Risk & ops: incident post‑mortems, control checks and remediation recommendations grounded in logs and policies.

• Data teams: SQL co‑pilot, pipeline documentation, test generation and data quality triage.

How this differs from “model‑over‑API” approaches

• No uncontrolled data egress: governed data remains in Snowflake.

• Operational simplicity: teams use Snowflake’s native surfaces (Cortex AI, Snowflake Intelligence) instead of building from scratch.

• Enterprise guardrails: identity, policy and audit are first‑class—crucial for regulated businesses.

Availability

The partnership is multi‑year and begins rolling out through Cortex AI and Snowflake Intelligence experiences. Customers should check their account region and entitlements for access details and roadmap timing.

Getting started

1. Enable the experiences in your Snowflake account (admin settings as required).

2. Define access policies/roles for model usage; confirm data classifications and masking rules.

3. Pilot a focused use case (e.g., automated weekly KPI brief) to validate trust signals and review process.

4. Scale to additional teams, adding observability and human‑in‑the‑loop review where needed.

What to watch next

• Continued updates to Cortex AI and Snowflake Intelligence as new model capabilities ship.

• Deeper agentic workflows (planning → tool use → verification) embedded in Snowflake UI and partner apps.

• Expanded administration controls, usage telemetry and cost management for AI workloads.

FAQs

What exactly was announced?
A multi‑year, $200M partnership to bring OpenAI’s models natively into Snowflake product experiences, enabling AI agents and natural‑language insight generation over governed data.

Do I have to move my data to another cloud?
No. The idea is to keep analysis within Snowflake so governance and compliance policies continue to apply.

Which Snowflake products are included?
Cortex AI and Snowflake Intelligence, with roadmap expansion over time.

How is access controlled?
Through Snowflake’s existing identity, roles and policies. Models only operate on data a user or service role is permitted to access.

What are some first projects to try?
Automated executive briefings, KPI explainers with links to source tables, anomaly triage for ops, and narrative generation for finance or product reviews.