Data Science

Ryan_Merlin

Imagine an Accounts Payable (AP) department inundated with a flood of invoices—each with a different layout, structure, or terminology. Traditional automation tools quickly hit a wall. You either build brittle rules for every vendor format or spend weeks training OCR models that still miss the mark.

But what if there was a way to automate the understanding of invoices—without depending on the cloud, risking your data, or paying per API call?

Enter the power duo: Alteryx Designer + Ollama’s local LLMs.

This article shows you how to get up and running in minutes using a downloadable Alteryx workflow that connects to a fully local, private, and GPU-accelerated LLM via Ollama. You’ll be able to extract data from messy PDFs and return clean, structured results—all without writing a single line of Python.

You can also watch a video walkthrough of this process here:

The Traditional AP Conundrum

Manual invoice processing is tedious and error-prone. With hundreds of vendors, each using different invoice formats, it becomes a nightmare to build static logic or templates that can handle every edge case. OCR tools help, but they often require ongoing training and don't handle ambiguous layouts well.

The result?

Time lost. Money wasted. People frustrated.

LLMs: A Game-Changer for Invoice Processing

Large Language Models (LLMs), like those you can now run locally with Ollama, bring a flexible, powerful approach to this problem:

Adaptive Understanding: LLMs can handle varied invoice structures with ease—no need to hardcode rules or templates.
Enhanced Accuracy: They understand the context of fields like "Invoice Date" vs. "Due Date" and extract the right values accordingly.
Scalability: Whether you're processing 10 invoices or 10,000, an LLM doesn’t care—it just works.

You no longer need to build one-off parsers for each supplier. The LLM can extract consistent, structured data from wildly different layouts with no additional training.

Real-World Impact for Accounts Payable

Implementing LLMs into AP workflows delivers tangible results:

⏱️ Time Savings: Automation reduces manual review and speeds up processing.
💸 Cost Reduction: Less manual labor and fewer costly errors.
📋 Improved Compliance: Get the data right the first time and avoid missed payments or audit issues.

By using local models via Ollama, you get all these benefits while keeping sensitive financial data fully on-premises—no data leaves your laptop.

Getting Started: Launch in Minutes with the Included Alteryx Workflow

We’ve made this easy to try. Just download our pre-built Alteryx Designer workflow and see the magic for yourself.

🛠️ The workflow includes:

PDF text extraction using Alteryx tools
Prompt construction using Formula tools
JSON formatting to call the LLM via a simple API
Result parsing and transformation back into rows and columns

🔽 Download the Sample Workflow (.yxmd)

💡 Before You Start
This workflow requires Ollama to be installed locally. If you haven’t already, check out our companion setup guide that shows how to install Ollama and run your first LLM with:

ollama run gemma3

Once that’s done, you’ll have a fully local LLM engine ready to accept requests from Alteryx—fast, secure, and completely free.

Conclusion

The integration of local LLMs with Alteryx Designer is a powerful step forward in automating complex, high-volume business processes like invoice parsing. No cloud. No guesswork. No per-token costs.

With the included workflow, you can go from concept to prototype in under 10 minutes.

And from there? The sky’s the limit.

✅ Smart automation
✅ Full data privacy
✅ Lightning-fast prototyping

Your AP team—and your future self—will thank you.