Use AI to convert data from a PDF to a spreadsheet

Convert data from a PDF to spreadsheet format in five simple steps using Parabola's free mini-tool.

The Parabola Team
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Transform your data in five easy steps using Parabola's drag-and-drop interface, powered by AI.

  1. Set up your data source by creating a new Parabola flow and uploading your PDF files. This creates your workflow foundation.
  2. Use Parabola's AI document processing tools to analyze and identify key information. Configure any necessary text recognition settings.
  3. Apply AI extraction rules to pull specific data points and content sections. This step converts unstructured PDF data into organized format.
  4. Use Parabola's spreadsheet formatting tools to structure the extracted data into your desired layout. Add any necessary data cleaning or validation.
  5. Generate your results by previewing the converted data and running your automated flow. Once configured, this process will handle new PDFs automatically.
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What makes working with PDFs so challenging for operators?

There are many benefits of using PDFs.

PDFs are secure. They’re compatible with any device. They compress files to very convenient sizes. They’re easy to scan, and ideal for printing. There’s a reason why they’re used for so many essential business documents and processes.

The discourse around PDFs, however, has also always been about how difficult it is to extract and translate information from them.

PDFs are limiting. The same characteristics that make them great are why they’re complicated to work with when digitizing documents.

  1. PDFs are a bit rigid in nature. While that is what contributes to the format’s consistency, it’s also what makes them harder to manipulate.
  1. Unstructured data presents a major roadblock to being able to quickly analyze the contents of a file and extract needed information.

The main challenge for most parsing software is that, much like the paper documents they aim to mirror, PDF formats can vary widely. Though parsing tools may offer consistency, they tend to lack flexibility.

Parabola engineer Jordan Lawler notes that, in order to process a particular document type quickly and accurately, some parsers need to be trained on hundreds of instances of the same document. This requires great upfront time investment, which can be virtually undone by small changes to the source document.

Plus, even using a flawless PDF parser can be a needlessly manual process, says Adam Reisfield, Special Projects Lead at Parabola: “Today, realistically, I would just give the PDF to ChatGPT, but the limitation there is that’s not an operationalized part of my process. Next time I receive a PDF, I’m gonna have to open up ChatGPT, drop that PDF in there — it’s not actually helping me automate that whole end-to-end process.”

Traditional PDF parsing solutions often struggle with all of this complexity, requiring manual correction over the top. That’s why Parabola’s PDF converter is unique: It combines OCR vision technology with top-of-the-line LLMs to not only pull data from PDFs precisely, but to also contextualize that data using AI.

What are the benefits of converting data from PDFs to Excel?

Getting data out of PDFs and into a standardized format is the first step to actually making use of that data. By converting that data to a workable format, you open the door to tons of value-adding benefits for your business.

While there’s no shortage of projects that could follow, you could use this data to do things like:

  1. Streamline customs compliance by having structured data ready for import declarations
  2. Automate reconciliation between purchase orders and invoices
  3. Automate freight audit and payment processes
  4. Track shipment status and cargo location in real time
  5. Build comprehensive supplier performance metrics so you can get your best from your partners
  6. Automate duty and fee calculations

Just take it from the customs team at a multinational freight forwarder who are working to automate PDF ingestion across their department. This project to digitize all kinds of PDF documents through the end of the year (ISFs, airway bills, commercial invoices, etc.) will save an estimated $1,000,000 in labor. For them, just getting that data from clunky PDFs into Excel without requiring manual data entry is creating undeniable value.

When shipping volume is high, manual data entry becomes a major line item.

The real-world impact of using AI to ingest PDFs

If it’s not abundantly clear: Manual data entry is a burden on businesses.

On average, it takes 15–20 minutes to process a single PDF, typically 1–3% of entries entered by humans have errors, businesses often have to dedicate full-time staff to data entry, and when busy seasons roll around, the strain on those folks is significant.

This used to be the only option for businesses.

But it’s not anymore, in large part due to advances in AI technology that can contextualize, ingest, and organize data more efficiently and accurately than humans ever could.

Zachary Wilner, head of data and analytics at Pair Eyewear recently implemented this PDF to Excel converter on his own team: “It’s been very, very accurate from day one. I barely put any prompts into the AI — I just turned it on, added the columns I wanted, and set it free. It’s a really, really big unlock for us. These PDFs can be like six pages of poorly formatted order data that even to a human can be hard to read.”

AI-powered data ingestion offers a powerful alternative to the world ops folks have known. Processing time is almost instantaneous, there’s a higher level of accuracy, and busy seasons or scaling business no longer equate to over-burdened staff or hiring needs. Data can be available immediately, in real time, as opposed to weekly or monthly at the mercy of team bandwidth.

And morale is better for it.

For Katya Lotzof, the Associate Director of Logistics and Fulfillment Operations at Caraway, she can easily point to time and cost savings associated with leveraging AI doc ingestion in her workflows, but it’s the impact on her team she’s most excited about.

“Parabola has eliminated tons and tons of manual steps, it saves hours of work on a weekly basis, and it also helps eliminate human errors,” says Lotzof. “And because my team is not working on these manual, repetitive steps, they can focus on something else. Their morale is actually improving because they can work on something interesting and exciting rather than boring and repetitive.”

Data, ops, and finance leaders are finally realizing the true value of AI in their team’s daily work — and you can too.