There’s a quiet revolution happening in how enterprises approach AI — less about flashy demos and more about shipping durable, scalable systems that deliver daily value. If you’ve been watching closely, Snowflake’s 2025 Summit confirmed it: the next wave of AI isn’t just about LLMs answering questions — it’s about agents that act.

Cortex Agents, introduced as part of Snowflake’s native AI capabilities, are designed for exactly that. These aren’t one-off copilots. They’re modular, observable, and production-ready agents that sit inside your data stack — ready to handle complex, multi-step workflows, autonomously and securely.

In this post, we’ll unpack what Cortex Agents are, how you can build and monitor them responsibly, and why they may represent one of the most significant steps Snowflake has taken toward enterprise-grade, AI-native architecture.

Why Agents, and Why Now?

Most GenAI efforts still live in notebooks, sandboxed environments, or separate pipelines. They’re interesting — but not operational. And that’s the gap Snowflake is aiming to close.

With Cortex Agents, the goal is to bring agentic reasoning into the data cloud. That means:

• Accessing the most up-to-date, governed enterprise data

• Executing workflows that involve multiple steps or systems

• Returning results that are traceable and consistent

• Adapting over time based on input and feedback

For Snowflake users, this removes a lot of the friction between experimentation and production. Instead of figuring out how to deploy a vector database, a separate LLM service, and some orchestration glue, you start with what you already know: the Snowflake ecosystem.

What Is a Cortex Agent?

At a high level, a Cortex Agent is a programmable, self-directed GenAI app that:

• Interacts with data inside Snowflake

• Uses built-in tools (like RAG, function calls, or SQL execution)

• Accepts goals in natural language or structured inputs

• Returns responses, documents, reports, or next actions

Each agent is modular, meaning it can be reused across different departments or apps. A ​“Customer Summary Agent” might serve both your support and sales teams, for example — surfacing relevant insights pulled from CRM tables, product feedback logs, and contract metadata.

And because it runs within Snowflake, you don’t have to move sensitive data around or bolt on new governance frameworks. Everything stays within your existing security perimeter.

How to Build a Cortex Agent: A Practical Approach

Snowflake hasn’t reinvented the wheel here — but they’ve made it easier to turn ideas into real workflows.

Here’s how you can get started:

1. Define the Use Case

Start with a repeatable task, like:

• Creating executive summaries for quarterly business reviews

• Generating explanations of anomalous revenue spikes

• Preparing daily summaries of sales pipeline movement

Choose something low-risk but valuable, where automation will save time without creating trust issues.

2. Set Up RAG (Retrieval-Augmented Generation)

Most agents benefit from context-aware reasoning. Snowflake supports native RAG workflows:

• Embed documents, emails, or reports using Cortex Vector Search

• Map metadata like customer ID, document type, or timeframes

• Use retrieval to feed only relevant context into your model

This helps reduce hallucinations and ensures outputs are grounded in real, governed data.

3. Chain Actions Together

Use the agent orchestration to run multi-step tasks:

• Search → summarize → analyze → notify

• Run SQL queries → compare metrics → draft explanations

• Retrieve documents → classify → generate next-step recommendations

Cortex lets you set logic flows that go beyond prompt-and-response.

4. Test and Evaluate

This is where most GenAI projects fail: lack of evaluation.

Snowflake includes tools for:

• Output scoring (accuracy, completeness, tone)

• Traceability of data sources used

• Logging prompts and results for future tuning

Loop in human reviewers early. Even better — let them submit feedback directly through the UI.

Monitoring and Governance: Making It Production-Grade

Even the smartest agent is useless if it’s unpredictable or insecure. Fortunately, Snowflake’s built-in observability tools give teams confidence to scale:

Key Capabilities:

• Usage tracking: Monitor how often each agent is triggered, by whom, and for what.

• Cost visibility: Track function calls and compute usage to avoid runaway bills.

• Access control: Limit agents to specific roles, datasets, or execution windows.

• Guardrails: Set hard stops for certain terms, thresholds, or output conditions.

We recommend setting alerting thresholds early — especially when agents interact with financial or legal data.

Why This Matters to Teams Using Snowflake Today

Cortex Agents aren’t just for the AI lab. They’re for anyone who’s already storing data in Snowflake and wants to:

• Automate repetitive, low-trust work

• Create new interfaces to old data

• Reduce the time between analysis and action

If you’re in RevOps, Finance, Legal Ops, or even Customer Support, you can now build lightweight apps without spinning up new platforms. It’s the kind of embedded AI that lives where your data lives—and that’s powerful.

Challenges Still Ahead

Of course, not everything is solved. Here’s what early adopters will need to keep an eye on:

• Latency: Multi-step reasoning can take time. Caching and prompt optimization will matter.

• Version control: How do you track agent behavior across changes to models or data?

• Evaluation metrics: We still lack standardized ways to measure GenAI app performance over time.

• Organizational readiness: Just because you can deploy an agent doesn’t mean the business is ready to trust it. Start with hybrid workflows.

Final Thought: Agents That Belong in Production

The takeaway from Snowflake’s 2025 Summit is clear: AI is no longer something separate. With Cortex Agents, it’s baked into the platform you already use. That means less friction, more reliability — and more meaningful automation.

These agents won’t replace your team. But they will start to take on some of the glue work — the summaries, the digests, the daily reports — that slow everyone down. And that opens up space for more strategic, creative thinking.

If you’re a Snowflake user, this isn’t just a new feature. It’s a new way of working. And it’s one we’re excited to build with.