We build pipelines that read your PDFs and scans, pull out the fields you need, and put them in Excel, Google Sheets or a database. Anything the system is not sure about goes to a short review screen for a person to check, instead of quietly going in wrong.
Tell us what you needSee typical projectsYou know what you're getting before work begins.
What we hear from businesses before a project like this starts.
The requests that come up most often for this kind of work, and what each one takes to work properly.
Transactions pulled from each bank's statement layout, balances checked, and spending categorised for a monthly report.
Attachments picked up from an inbox, fields extracted, and only the doubtful ones held for a person.
Form fields read directly from the PDF, including checkboxes and dropdowns, which is faster and more accurate than OCR.
Text extracted from scans, stored with the source page, so you can search and filter it later.
Product names, codes, prices and specs pulled from PDF catalogues into a sheet ready for import.
Scans or photos turned into editable files or structured rows, with a check for anything unreadable.
Tools that come up most: OCR, Python, Excel, Google Sheets, Power Automate, Airtable, MySQL, Postgres, CSV.
Concrete pieces, each one something you can open and check when it's done.
The fields you name, from the documents you get: dates, totals, line items, account numbers, names and addresses.
OCR, layout-aware document models, rules per document typeEach field gets a confidence score. Low-confidence fields go to a review screen with the page beside them; the rest go straight through.
A simple web review screen or a review tab in SheetsLine items that must add up to the total, balances that must carry over, suppliers that must exist. Anything that fails is flagged.
Validation rules agreed in the scopeClean rows in Excel, Google Sheets, a database or an import file for your accounting system.
Excel, Google Sheets, Postgres, QuickBooks and Xero import filesDocuments picked up from an email inbox, a Drive or Dropbox folder, or an upload page.
Gmail, Outlook, Google Drive, Dropbox, SFTPEvery row linked back to its source file and page, so anyone can check where a number came from.
Source links, run logsExample packages to show the shape of the work. These are examples, not past clients; yours gets its own written scope.
Example package
Invoice PDFs from an inbox or folder turned into one row per invoice, plus line items, ready for review and import.
You get
Example package
Statement PDFs from your banks turned into one transactions table, categorised, with a monthly summary sheet.
You get
Example package
A batch of fillable PDF forms read field by field into one Excel workbook.
You get
Example package
Purchase orders or remittances that arrive by email extracted automatically, with only the doubtful ones held for a person.
You get
An accounts-payable team was keying 200+ supplier invoices a week by hand from PDFs and scans. We built an extraction pipeline that reads each invoice, pulls the header fields and every line item, checks the math, catches duplicates and matches the PO. Confident invoices go straight through; anything uncertain lands in a review screen with the source document highlighted next to the extracted values. Approved invoices export to Excel or post to the accounting system.
Python, OCR, layout-aware PDF parsing, LLM extraction with validation rules, PostgreSQL, React
A working example we built to show this kind of work. It is a demonstration, not a client project.
Sample build
Reads supplier invoice PDFs in three different vendor layouts and writes header fields and every line item to an Excel workbook, with a check column that flags invoices whose lines don't add up to the total.
Python, pdfplumber, openpyxl, reportlab, Docker
About the screenshots: A generated sample invoice and the workbook the extractor wrote from it.
The habits that keep this kind of project from going wrong.
We run a sample of your real documents at the first milestone and show you field-by-field results before building the rest.
Digital PDFs and fillable forms are read directly. OCR and document models are used only where the document is a scan or a photo.
Totals, balances and dates are cross-checked, so a misread number is caught rather than passed on.
Anything uncertain goes to a review step. Nothing is forced through to make the numbers look complete.
You describe it. We write it down, build it, and hand it over.
Tell us what you need in your own words, and which tools you already use. A few lines is plenty to start.
We reply with a short written scope: what gets built, what is out of scope, which accounts we need, and how we'll both know it works. You know what you're getting before work begins.
The work is split into milestones. At each one you see it working in your own account and sign it off before we go on.
You get the working system, its documentation and a walkthrough. If anything we built breaks in the next 30 days, we fix it at no charge.
Pushbuild has built software for businesses since 2010, for more than 40 clients. Every project is led by a former public-company CTO, from Groton, Massachusetts. See products we've built.
It depends on your documents, so we measure it rather than promise a number. At the first milestone we run a sample of your real documents and show you the results. The review step exists so that uncertain fields are checked, not guessed.
Documents are processed in accounts in your name wherever possible, and we tell you in the scope exactly which services see the files. Nothing is kept by us after handover.
No. We build a system that does the extraction, so the next batch costs you nothing. If you need a one-off batch typed, we will tell you that a typing service is cheaper.
You do. The code goes into a repository you own, it runs in an account in your name, and the data stays in your spreadsheet or database.
Most projects take one to three weeks from the signed scope. Send us 10 to 20 sample documents with your brief and the scope will be more precise.
The review step catches it, so bad data does not slip through. In the 30 days after handover we adjust for it at no charge; after that, they are scoped and agreed with you before we start.
Email a few lines about what you want and which tools you use, or call. We reply with questions or a written scope.
hello@pushbuild.com