Here’s how to use AI to convert data from a BOL to a spreadsheet
1
Upload your bill of lading PDF
Select and upload the PDFs you want to convert.
2
Configure your settings
The tool will help auto-detect tables, but refine the columns and content you want from there.
3
Review and download
Once your data looks right, download it, or pull the data into Parabola to take more actions.
A quick refresher on bills of lading — and BOL to Excel converters
The TL;DR on bills of lading
A bill of lading is a shipping document that serves three main purposes:
- It’s a receipt for shipped goods
- A contract of carriage between shipper and carrier
- A document of title to the goods
You can think of it as the most important piece of paperwork in shipping. Without it, you can’t prove ownership or take delivery of cargo.
A bill of lading includes key information like:
- The names and addresses of the shipper and receiver
- Description of the goods
- Shipping instructions
- Packaging details
- Origin and destination
- Terms of delivery
The TL;DR on bill of lading to Excel converters
A bill of lading to Excel converter is an AI-powered tool designed to extract data from PDF bills of lading and convert it into an editable Excel format. The tool uses AI to accurately extract, organize, and contextualize whatever information you want from bills of lading, such as item descriptions, quantities, prices, and totals.
For freight, ops, and logistics professionals, this tool streamlines the process of digitizing and organizing invoice data, making it easier to manage shipments, track costs, and perform data analysis.
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What makes working with bills of lading so challenging for operators?
Like much of the data ops professionals have to manage on a daily basis, bills of lading provide a unique challenge when it comes to actually making their data usable.
Bills of lading often involve multiple parties (shipper, carrier, consignee); have complex cargo descriptions; include special handling instructions and notations; are of varying quality and formats; detail interconnected shipping references and booking numbers…the list goes on.
But perhaps most frustrating, BOLs are often sent to email inboxes as PDF attachments. Getting data from those attachments requires a person to open the file, copy-paste data over to a spreadsheet, cleaning it all up along the way. This makes for a super manual (and error-prone) process.
Traditional PDF parsing solutions often struggle with 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 bills of lading to Excel?
Getting BOL 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:
- Track shipment status and cargo location in real time
- Automate cargo release and delivery processes
- Create comprehensive shipping documentation records
- Facilitate easier integration with your TMS and visibility platforms
- Enable quick data sharing across supply chain partners
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 bills of lading
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 document; 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.