Generative AI (GenAI) has incredible potential, but most analytics teams haven’t been able to take advantage of it. Why? Because today’s AI tooling hasn’t been built with their use cases in mind.
We’ve all seen ChatGPT generate code and summarize documents. But when it comes to applying generative AI to real business data, which is often high volume, unstructured, and inconsistent, the limitations quickly become clear. Most Large Language Model (LLM) tools assume technical expertise, offer limited guidance, and break down when scale or governance enters the picture.
Alteryx users have been telling us the same things again and again:
LLMs are powerful. What's been missing? A practical way to put them to work in everyday analytics. That changes now.
What if we told you that you can now tackle these challenges that were once too manual, too inconsistent, or simply too complex to solve at scale? From accelerating analysis to improving data quality, these are the kinds of high-value problems that used to take hours (or weren’t tackled at all), and now, they’re within reach—right inside Designer.
Here are seven real-world challenges analysts can now tackle head-on for the first time:
These aren’t future possibilities. They’re available right now. With new GenAI Tools in Alteryx, analysts can finally put LLMs to work on real business data, at real scale.
We’re excited to announce that Alteryx GenAI Tools are now available in Public Preview through Alteryx One. This release brings generative AI directly into Alteryx Designer, allowing you to apply your approved language models to real business data using the same drag-and-drop experience you already know. No code. No external platforms. No need to build infrastructure from scratch.
With these tools, you can now solve all the use cases above, and more! You define the task, choose the LLM, and Alteryx handles the rest.
The Public Preview includes four tools purpose-built for practical use in analytic workflows:
Send row-level prompts to your selected LLM to classify, summarize, extract, or reword text. Use the built-in Prompt Builder to test and refine prompts before scaling. |
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Standardize inconsistent text values using AI-powered fuzzy matching. Works across languages and can be guided by a reference list. |
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Map a source dataset to match a target schema automatically. Ideal for partner feeds, shared models, or onboarding new data sources. |
Generate realistic synthetic records by describing the structure and content you need. Useful for testing and prototyping. |
These tools support over 13 LLM providers through API connections, so you can bring the model that best fits your needs.
Most generative AI tools are built for developers or one-off experiments. Alteryx’s GenAI Tools are different. Here’s how:
Easy to use
Each drag-and-drop tool runs inside Alteryx Designer. No code. No external orchestration. No custom deployments.
Scales with your data
Whether you’re processing 500 rows or 50,000, GenAI Tools work across your entire dataset without requiring batch scripts or engineering workarounds.
Works with your LLM of choice
Connect to over 15 supported providers using API keys managed centrally. You can use OpenAI, Gemini, Anthropic, Mistral, Cohere, and others without hard coding credentials into workflows.
Secure by design
All credentials and connection details are stored in Alteryx One. Access can be controlled by user roles, and connections can be segmented by tenant or team. IT admins stay in control of how models are accessed and used.
Built-in support for prompt engineering
The Prompt Builder gives analysts a fast, structured way to experiment with different instructions and templates before applying them at scale.
The result is faster insight for analysts and more control for IT.
This is your chance to help shape how generative AI fits into real analytic workflows. Try Alteryx’s GenAI Tools now and see what’s possible.
With GenAI Tools, generative AI is no longer experimental. It is now a practical, secure part of everyday analytics in Alteryx.
The tools are here. They work at scale. And we’re excited to see what you build with them.
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