Guide · Onboarding
Turn a client intake PDF into an online form
Every firm already has the document: the intake form, the questionnaire, the application PDF that gets emailed out and filled in by hand or in a PDF reader. This guide covers what actually has to happen to turn that PDF into fillable fields a client completes on their phone, and what tends to go wrong with generic form builders along the way.
- The PDF you already use is a better starting point than a blank form builder
- Field detection, not manual rebuilding, is what actually saves the time
- Checkboxes, tables and repeating sections are where generic builders struggle
Why does the PDF you already use matter more than starting from a blank form builder?
A blank form builder asks you to recreate every field, label and validation rule from scratch, and to guess at wording and order your team has often already refined through years of actual client intake. The PDF you already use encodes that work: the exact fields a client needs to answer, in the order and phrasing your staff and clients already understand, plus any layout, sections or instructions that make it usable. Starting from that document instead of a blank canvas means you are digitising a form that already works, rather than redesigning one and hoping the new version matches what clients and staff expect.
What actually has to happen to turn a static PDF into fillable fields?
Every field on the page, a text box, a date, a checkbox, a signature line, has to be identified and mapped to the right input type, and the underlying question behind each field, what is this actually asking the client for, has to be captured so the digital version validates and stores it correctly. Done manually, this means someone opening the PDF, going field by field, and rebuilding each one in a form editor, which is slow and error-prone on anything longer than a single page. This is exactly the step AI field detection is built to do automatically instead.
What goes wrong with generic form builders when the source is a dense PDF?
Generic form builders are built around a blank canvas: you drag on a text field, a dropdown, a date picker, one at a time. Faced with a dense, multi-page PDF, that means manually transcribing every field, which takes real time and introduces transcription mistakes, a missed field, a wrong label, a validation rule that does not match what the original document required. The result is often a form that looks similar to the original but behaves differently in small ways clients or staff only notice once something does not match.
How do you handle a PDF with checkboxes, tables, or repeating sections?
Checkboxes need to become actual selectable inputs, not static images of a tick. Tables with several rows of similar questions, dependants, assets, prior addresses, need to become a repeatable section a client can add to as many times as they need, rather than a fixed number of rows copied from the original layout. Handling these correctly is what separates a form that merely looks like the PDF from one that actually captures the same structured information the PDF was designed to collect, in a shape your systems can use afterward.
How do you keep the output document looking like the original for filing or audit purposes?
For many firms, the value of the original PDF layout is not just the fields, it is the finished, filled document looking like the form a client, auditor or regulator expects to see, matching your letterhead, your existing filing conventions, or a template a professional body has issued. Keeping that visual structure while making the fields interactive online means the completed document, once filled and signed, can still be filed, printed or submitted anywhere the original PDF was accepted, rather than producing an unfamiliar new format that needs its own explanation.
How AI field detection does this step in Braigest instead of manual rebuilding
Upload the PDF you already use, and Braigest's AI detects every field on the page automatically, in whatever language the document is written in, and turns it into the form your client fills from their phone, keeping the same structure and order your team already knows. Checkboxes, tables and repeating sections are handled as part of that detection rather than a manual follow-up step. If the source document changes later, a new version, a tweaked clause, you update the PDF rather than rebuilding a form from scratch a second time.
In Braigest
Your own PDF becomes the form, detected automatically
AI field detection turns any PDF you upload into a form clients fill from their phone, in any language, and it is what the AI workflow builder uses when it drafts a flow from a description. Included from the Solo plan at €29/month.
Frequently asked questions
Does this work with a PDF in a language other than English?
Yes. Field detection works on the PDF in whatever language it is written in, so the same process applies whether your intake document is in English, Italian, Spanish or another language.
What happens if I later change the PDF?
Update the PDF and the form updates with it. There is no separate rebuilding project each time a clause or a field changes in the source document.
Can the same PDF fill in data collected earlier in the flow?
Yes. Once a client's answers exist from an earlier step, the same values can prefill later documents in the same pack, so an address or a name is not typed more than once.
Does the finished, filled document still look like the original PDF?
Yes. The output keeps the layout and structure of the original document, so a filled and signed version can still be filed or submitted wherever the original PDF was accepted.
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