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Orion vs Snowflake Cortex

Snowflake Cortex answers over your Snowflake data. Orion works across the warehouses you run.

Cortex is the AI layer inside Snowflake. CoWork, formerly Snowflake Intelligence, is its work agent, grounded in a semantic model you build and maintain there. Orion connects to Snowflake, BigQuery, Databricks, and Redshift. It reuses the semantic layer you already trust, like LookML or dbt, and delivers proactive answers to where you already work.

TL;DR

Every warehouse, one analyst

Orion works with whatever warehouses you already run: Snowflake, BigQuery, Databricks, Redshift, and more. Cortex works within your Snowflake account.

Bring the semantic layer you have

Orion reads the semantic layer you already trust. Cortex needs a semantic view you build in Snowflake, or a YAML semantic model.

Answers before you ask

Orion watches your metrics and investigates what moved. Cortex answers when asked, and CoWork sends briefs and anomaly alerts on a subscription you set.

What is the difference between Orion and Snowflake Cortex?

Cortex is the AI inside Snowflake. Orion is the analyst across your whole stack.

Orion

Orion connects to the warehouses you already run and reuses the semantic layer you already trust, like LookML or dbt. Your data team and business users share one source of answers. Business users ask in Orion’s chat or in Slack and get answers on the spot, without waiting on the data team. It monitors your metrics, investigates the why, and delivers the write-up to Slack or email before anyone asks. The whole team can share one conversation, each at their own access level. It sits on top of your stack, with nothing to migrate and no dependency on any one warehouse. And if you build software yourself, you can embed Orion in your own product as a white-label analyst for your customers.

Snowflake Cortex

Snowflake Cortex is a strong AI layer for teams whose data lives in Snowflake. Cortex Analyst turns natural language into governed SQL over a semantic model you author in Snowflake, and it honors Snowflake’s access controls natively. CoWork is its work agent, with Deep Research reports. It runs where your Snowflake data lives, on a model you build and maintain there.

How do Orion and Snowflake Cortex compare feature by feature?

Orion is best for

Teams whose data spans more than Snowflake

Snowflake Cortex is best for

Native AI for teams standardized on Snowflake

OrionSnowflake Cortex
Proactive investigationAuto-detects significant changes in your metrics, writes up why they moved, and delivers the answer to Slack or emailCortex Analyst answers when asked. CoWork has subscription briefs and anomaly alerts↗
Everyone in one live conversationEveryone posts into one thread and watches the same answer stream, each at their own access level. The Room stays the single record, and nobody can copy it into a private threadEach person gets their own thread. A shared conversation is a static snapshot, and follow-ups start a new thread↗
Semantic layer ingestionReads your LookML and dbt straight from their repos and reuses the dimensions, measures, and models you already defined to write better SQL. Your repo stays the source of truth. No semantic layer yet? Orion builds one from your metadata.Build and maintain a Snowflake semantic view or YAML model, authored for Cortex. No LookML import documented.↗
Context from your existing docsA cited Knowledge Base synced from GitHub, Confluence, or Notion. Orion cites its pages inline in reports, slide decks, and dashboardsSemantic views you author. Cortex Search supplies literal column values. No Confluence or Notion connector documented↗
Works across warehousesConnects to Snowflake, BigQuery, Databricks, and Redshift, and reasons across them in one analysisWorks within your Snowflake account. External Iceberg catalogs sync in through catalog-linked databases↗
Runs inside your warehouse perimeterConnects from outside, through a service account you scope to the data it may analyzeAI runs in your Snowflake account and honors Snowflake role-based access control natively↗

What if your data is not all in Snowflake?

Cortex is a strong fit if your data already lives in Snowflake and your team works in Snowsight. Orion does not ask you to consolidate onto one vendor's stack. It connects to the warehouses you already run, reuses the semantic layer you already trust, and delivers the answer without anyone opening Snowflake.

Your data may span Snowflake alongside BigQuery or Databricks. Orion reasons across all of it in a single investigation, and tells you what changed and why.

When should you choose Snowflake Cortex instead?

The Snowflake Cortex vs Orion decision comes down to where your data lives and who does the investigating.

Choose Snowflake Cortex if

  • Your data and your team are standardized on Snowflake and work happens in Snowsight.
  • You want AI that runs inside your Snowflake perimeter and honors Snowflake role-based access control natively.
  • All of your data already lives in Snowflake, and you want the AI to stay inside that account.

Choose Orion if

  • Your data spans Snowflake alongside BigQuery, Databricks, or Redshift, and you want one analysis across all of it.
  • You want to reuse the LookML and dbt you already maintain instead of authoring a Cortex-specific model.
  • You want proactive investigation delivered to Slack or email, before anyone thinks to ask.

Orion vs Snowflake Cortex: what do buyers ask most?

For proactive analysis, yes: the part that comes to you is what Orion adds. Cortex Analyst turns a question into SQL over a semantic model and answers when asked. That is useful, but you still have to know which question to ask. Orion adds the proactive layer. It watches your metrics and auto-detects the significant changes you did not think to ask about. It investigates the root cause and delivers the write-up before anyone requests it. So even on Snowflake, Cortex answers the questions you remember to ask. Orion also catches the ones you did not, which is where the unknown unknowns a stretched data team misses actually live.

No. Cortex Analyst runs on a semantic model you author specifically for Cortex. That is a semantic view built in Snowflake with SQL or the Snowsight wizard. Or it is a YAML model file that maps logical tables and metrics to your Snowflake tables. Snowflake runs your dbt projects, but Cortex's semantic model is still authored for Cortex. Snowflake's docs describe no LookML import. The business logic you already maintain gets re-created and maintained a second time. Orion instead reads the LookML and dbt you already trust where they live, as the logic behind every answer. A cited Knowledge Base adds the context that is not in the model. Nothing to port, and no second copy to keep in sync. And if you have no semantic layer, Orion builds one from your warehouse metadata and Knowledge Base.

Only once Snowflake can reach the data. Cortex's analytics run within your Snowflake account, and Snowflake documents several ways to widen what that account sees. Two matter here. Catalog-linked databases sync external Iceberg catalogs, including Databricks Unity Catalog. Openflow ships connectors that copy PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, and BigQuery data into Snowflake. But every route runs through Snowflake, so the data has to be loaded or linked there before Cortex can reason over it. Orion is built the other way around. It connects to the warehouses and sources you already run. It can investigate a question that spans Snowflake, BigQuery, and Databricks together in a single analysis. If your reality is more than one warehouse, that difference decides whether you get the whole picture or one vendor's slice of it.

Mostly you have to ask. Cortex Analyst answers when asked. Snowflake has an anomaly-detection ML function. But it is a SQL function you create and call yourself, with Tasks and Alerts for automation. No Cortex Analyst integration is documented. CoWork's subscription-driven briefs and anomaly alerts are the closer analogue. Its Automations turn a one-time report into a recurring one. Orion closes that gap: it auto-detects the significant changes in your metrics, runs the root-cause analysis, and delivers the write-up to Slack or email. A Workflow adds the scheduled version, judging whether the numbers are worth flagging and sending the result to the right people. So Cortex answers the questions you ask. Orion also brings you the ones you did not.

Orion and Cortex both ground their answers in governed logic. Cortex generates SQL against the semantic model you built in Snowflake, and honors Snowflake's role-based access control. Users see only what they are cleared to see. Orion grounds every answer in the semantic layer you already trust, like your LookML and dbt definitions, plus a cited Knowledge Base. Every analysis is captured in a notebook holding the instructions, the logic, and the code. Anyone can check how an answer came to be. Orion connects read-only, through a service account you scope to the data it may analyze. Roles on two levels, tenant and group, control who can see which projects and data. The difference is whose definitions the AI uses: Orion uses the ones you have already standardized, instead of a model you re-create inside one warehouse.

Rooms is one shared conversation between your team and Orion. Everyone asks in the same thread, and every message is attributed. Each person works at the access level they already have, so sharing the investigation never means widening access. A per-user chat answers one person at a time. A Room holds the whole team's investigation, analysts and business users together, with Orion in it.

No. Orion is warehouse-native. It connects to the warehouses you already run and queries them in place. There is nothing to load or migrate first. Cortex, by contrast, only reaches data that is loaded into or linked to Snowflake. For anything else, adoption means loading or linking it and authoring a Cortex semantic model first. With Orion you point it at what you have, it reuses your existing semantic layer, and you start getting answers with nothing to rebuild.

CoWork is Snowflake's work agent, formerly Snowflake Intelligence. Its Deep Research feature investigates across your data estate and returns cited reports. It is the right mental model for what Snowflake-native AI looks like today. Two structural differences remain. CoWork runs where your Snowflake data lives, on a semantic model you author there, and reaches tools like Slack, Gmail, and Jira through MCP connectors. Orion connects to Snowflake, BigQuery, Databricks, and Redshift and reuses the LookML and dbt you already maintain. On proactivity, Snowflake describes scheduled briefs and anomaly alerts through subscriptions. Its Automations turn a one-time report into a recurring one. Orion watches your metrics and delivers the write-up without anyone asking.

It does, and it is worth understanding before you commit. Snowflake sells consumption, so the compute an AI feature burns is revenue for the vendor. Heavier usage is not a problem that model has to solve. Orion is priced per deployment, with no per-query or per-message meter. Every extra query Orion runs and every extra token it spends is our cost rather than yours. That gives us a direct reason to reach the answer in as few queries as we can, and to keep getting better at it. Neither model is dishonest. They simply pull in opposite directions, and the direction matters more the more your team actually uses the thing.

Yes. Embedded Orion is a white-label analyst for your customers, presented under your brand inside your product. Each customer account is isolated: they see only their own data, business context, and permissions, and nothing passes between accounts. Your customers sign in to your product, and Orion inherits who they are and what they can see. There is no second login. You integrate once. Every new account is provisioned with its own branding, data connections, and access controls, so the second customer costs a fraction of the first.

Yes. Orion connects to Snowflake alongside your other warehouses. It uses the data and structure you already have in Snowflake, and also reaches everything that lives outside it. Teams keep Cortex for in-Snowflake, ask-and-get-SQL questions. They add Orion as the analyst. Orion watches the whole stack, investigates what changed, and delivers the answer without anyone opening Snowsight. You are not choosing one or the other. Orion adds proactive, cross-warehouse investigation on top of what Cortex does inside Snowflake.

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