Why We Built ExtractBee: The Invoice Processing Problem We Couldn't Ignore

We build software. We've built accounting software, automotive platforms, legal document tools. Across all of them, there was one problem we kept running into in every client's office, in every industry, in every country.

Someone was manually copying data from PDFs.

Not occasionally. Not as a workaround for an edge case. As a regular, daily part of their workflow. An accountant at a logistics firm spending an hour each morning entering invoice data from supplier PDFs. A finance manager at a small manufacturer typing bank statement transactions into a spreadsheet to prepare for month-end. A bookkeeper at an accounting firm processing client receipts one by one.

The tools to automate this existed — but they weren't working for these teams. Not really.

The Problem with Existing Tools

The document extraction tools available before ExtractBee fell into two categories.

Category 1: Template-based tools. These required you to define extraction rules — "invoice number is in the top-right corner," "total is the last number in column 4." They worked well for documents from a fixed set of vendors with consistent layouts. But the moment a new vendor appeared, you needed a new template. When a vendor updated their accounting software and changed their invoice format, the template broke. One accounting firm we worked with maintained dozens of active parsing templates, several of which broke every month.

Category 2: Enterprise IDP platforms. Capable, accurate, genuinely impressive technology — and priced and implemented for enterprise procurement cycles. Often a multi-month implementation, consulting involvement, and annual contracts well beyond what a 5-person firm would consider. An accounting firm with 5 staff processing 300 invoices per month isn't the target customer for these platforms, and the pricing makes that clear.

The gap between "template tool that breaks every time a vendor changes their format" and "enterprise platform that requires a procurement process" was enormous. And in that gap lived most of the small and medium businesses and accounting firms that had the most to gain from automation.

What Changed

The technology that made ExtractBee possible wasn't viable at the quality and price point we needed until the 2024–2025 wave of frontier models.

Large language models can now read a document and understand its content semantically, the way a human does. Not by matching text to coordinates. Not by applying rules. By actually understanding that the number after "Invoice No:" is the invoice number, regardless of where on the page it appears or what font it's in.

Combined with Tesseract OCR for scanned documents, this gives us a pipeline that works on any document from any vendor without any configuration. Today our pipeline runs primarily on Google's Gemini, with Claude as an automatic fallback — we route each document to whichever model gives the best accuracy per cent.

We tested this extensively before building a product around it. We ran 500 real-world invoices from 200 different vendors through the pipeline. The extraction worked — not perfectly on every document, but well enough to be genuinely useful, with field-level confidence scores to flag the uncertain cases for human review.

The economics also worked. Modern LLM API pricing, combined with OCR pre-processing and prompt caching, brings the cost per page to a level that supports subscription pricing accessible to small businesses.

What We Built

ExtractBee is the tool we wished existed when we were building software for clients who had this problem.

Zero setup. Upload a document and extraction runs immediately. No templates, no rules, no configuration per vendor. An invoice from a supplier you've never processed before works on the first attempt.

Direct integration with the tools finance teams actually use. Xero, QuickBooks, Google Sheets, Slack, Microsoft Teams, OneDrive, and Make.com — plus HMAC-signed webhooks for everything else. Not "export a CSV and import it manually" — actual, automatic data flow.

A Human Review UI that catches uncertain extractions before they reach your accounting system. Not perfect AI, but AI with a supervised correction step that makes it reliable enough to trust.

And pricing that makes sense for small businesses and accounting firms — starting free, scaling with volume.

Who We're Building For

ExtractBee is built for teams who process business documents regularly and are currently doing part of that work manually.

Accounting firms where staff spend time on invoice data entry that should be automated. Where a new client means a new set of vendors to handle. Where template maintenance is eating into time that should go to actual accounting.

Finance teams at SMBs where the person responsible for accounts payable also has five other jobs. Where invoice processing is done in batches because doing it daily isn't worth the context switch. Where the question isn't "should we automate this?" but "is there something that actually works for us?"

Operations teams who receive purchase orders, delivery confirmations, or other documents that need to be tracked in a spreadsheet or database. Where the data exists in PDFs but getting it out requires manual effort.

We are a small team. We move fast. We are building this in public, sharing what we learn, and we are genuinely interested in the problems our customers have — not just the ones we anticipated.

What We're Building Toward

The v1 of ExtractBee solves the core problem: getting structured data out of documents without templates.

What comes next:

More document types. Contracts, delivery notes, remittance advices, payroll documents. Each document type our customers need to process is a document type we want to support.

Better integrations. Direct connections to more accounting systems, more automation platforms, more of the tools finance teams use. More native connections, fewer generic-webhook workarounds.

Smarter human review. Right now, Human Review flags uncertain fields. We want it to learn — to get better over time at predicting which documents and which fields will need review, and to require less and less intervention as confidence improves.

Multi-language expansion. Localized interfaces (starting with major European languages) are on our roadmap. If you're processing documents in a language we don't yet support in the UI, we want to hear from you.

A Note on Where We're Based

ExtractBee is operated by MB Dokigo, registered in Vilnius, Lithuania. We are an EU company, building for a global market, with EU data residency by default.

This matters for our customers in ways that go beyond compliance. It means we're subject to GDPR as a native requirement, not a retrofit. It means your data stays in the EU unless you explicitly need otherwise. It means our DPA is not a legal afterthought — it's how we designed the product.

If you've been manually copying invoice data into a spreadsheet, we built ExtractBee for you.

Try it free — 20 pages, no card required →

New here? Start with Introducing ExtractBee, or see how we compare to Nanonets, Parseur, and Docparser.

We'd love to know what you think.

ExtractBee is operated by MB Dokigo, Vilnius, Lithuania.

Last updated: June 2026.