How Formblyt's AI Form Generator Works

From a sentence to a working form

Most form builders start you with a blank canvas. Formblyt starts you with a sentence. You type something like "a school admission form for grades 1 to 10 with parent contact details and document uploads" and the AI form generator returns a complete, editable form in a few seconds.

Here is what actually happens between those two moments.

1. Intent parsing

The prompt is first parsed for three things: the purpose of the form (lead capture, registration, feedback, application), the audience filling it, and any entities you mentioned — grades, dates, documents, payment amounts. That structure matters more than the wording. Two very different prompts that describe a job application will produce a similar skeleton, because the model is matching intent, not keywords.

2. Field synthesis

Each entity becomes a field with a real type, not a text box. A mention of "email" becomes an email field with validation. "Upload marksheet" becomes a file upload with size limits. "Which board" becomes a single-choice field pre-filled with the common options. Required flags are inferred from how essential a field is to the stated purpose — you can flip any of them afterwards.

3. Ordering and grouping

Completion rate is mostly a function of order. The generator front-loads low-friction fields (name, email), groups related questions together, and pushes long-form or sensitive questions towards the end. Uploads and payments always come last, because asking for effort before commitment is the fastest way to lose a respondent.

4. Logic suggestions

Where the prompt implies branching — "if they choose international, ask for a passport number" — the generator wires up conditional logic automatically. Rules show up in the Logic tab, in plain language, and you can edit or delete them.

5. Theme and copy

Finally, the form gets a theme, a title, a description and helper text that match the tone of the request. An internal IT ticket form reads differently from a wedding RSVP.

What you do next

The generated form is a starting point, not a locked artifact. Everything is editable in the builder: drag fields to reorder, change types, add an advanced table, attach a payment field, or set an access mode so only invited emails can submit.

Practical prompts that work well

• "Customer feedback form with NPS score, one open comment, and optional email"
• "Event registration with ticket type, dietary preferences and a headcount limit"
• "Freelance client intake with budget range, timeline and a file upload for the brief"
• "Patient intake form with medical history, allergies and consent signature"

Vague prompts produce vague forms. Naming the audience and the outcome — "so I can shortlist candidates" — measurably improves the result.

Where AI generation saves the most time

The obvious saving is the first draft. The bigger one is field typing and validation, which is where manual builders leak hours. Getting a phone field, a date range, a conditional upload and a scoring rule right by hand takes real effort; getting them wrong costs you dirty data you only discover after 200 submissions.

Limits worth knowing

The generator is deterministic about structure, not about your business rules. It will not know your internal grading scheme, your refund policy, or that legal requires a specific consent wording. Review before publishing, especially for anything regulated.

Try it

Open the builder, describe your form in one line, and publish. You can share it as a link, a QR code, or embed it. Responses land in your dashboard with per-question analytics, and you can export them any time.