What is SiliForm?
SiliForm is an AI-powered conversational form builder for research, feedback, and onboarding — built for situations where response quality matters more than form volume.
What SiliForm actually is
SiliForm is a form and survey platform built around a simple observation: most form tools optimize for how fast a form can be built, not for how well it collects information. SiliForm inverts that — the builder uses AI to generate a first draft of your form from a description, and the respondent-facing experience is a guided, one-question-at-a-time conversation rather than a long page of fields.
Under the hood, every SiliForm form is one of two types:
- Static forms — a fixed sequence of questions you design once, similar in spirit to Typeform or Google Forms, but rendered as a conversational flow.
- Dynamic forms — the AI generates follow-up questions in real time based on the respondent's previous answers, so the question path adapts person-to-person instead of staying fixed.
Who SiliForm is for
SiliForm is built for people who don't create forms every day — but need the answers to be reliable when they do.
- Startup founders validating an idea through customer discovery calls and surveys
- Universities and academic departments running participant intake or feedback studies
- Researchers and students collecting self-reported data for a thesis, dissertation, or study
- Educators gathering structured feedback from students or parents
- HR and people teams running pulse surveys, exit interviews, and onboarding checklists
- Coaches and consultants using intake questionnaires as a first client touchpoint
The problem with traditional forms
Most form tools are designed for speed and volume, not thinking. They show too many questions at once, provide little insight into respondent behavior, and treat partial responses as failures to be discarded rather than data worth keeping.
As a result, teams often collect data that looks complete on a dashboard — a 92% completion rate, for example — but is shallow, rushed, or shaped by the format itself rather than the respondent's actual thinking. A full breakdown of why this happens is in why psychology surveys fail.
How SiliForm works, step by step
- Describe the form. Tell the AI form builder what you're trying to collect — "a post-workshop feedback survey for 40 attendees", for example — and it drafts a full question set, choosing appropriate field types (text, multiple choice, rating, file upload) automatically.
- Refine on the canvas. The drag-and-drop builder lets you reorder, edit, group into sections, or add blocks by hand. Nothing about the AI draft is locked — it's a starting point, not a final answer.
- Choose static or dynamic mode. Static keeps the question order fixed. Dynamic lets the AI generate the next question live, based on the answer just given — useful for open-ended discovery questions where a fixed follow-up doesn't fit every respondent.
- Publish and share. Forms are served as a hosted link or embedded directly into a website, and render as a sequential, conversational flow rather than a single long page.
- Review responses as insight, not just rows. Beyond raw response tables, SiliForm can summarize open-text answers into themes, sentiment, and patterns across structured fields.
Core features
- AI form generation — draft a complete form from a text prompt, with field types chosen automatically
- Dynamic, adaptive questioning — follow-up questions generated per respondent, not a fixed script
- Layered AI input validation — format rules, then heuristic checks, then an LLM pass that flags plausible-but-fake answers (disposable emails, sequential phone numbers, keyboard-walk gibberish) before they're counted — full breakdown here
- Question-level drop-off analytics — in-progress drafts are tracked and aggregated by question, so you see exactly where respondents abandon a form instead of one aggregate completion percentage
- Nine block types — text field, text area, single choice, checkboxes, star rating, file upload, headings, paragraphs, and sections
- Theming — colors, fonts, logo, and a custom submission message per form
- Integrations — automatic sync to Google Sheets and Zapier, plus HubSpot and webhooks for anything else
- AI-generated response insights — themes, sentiment, and notable patterns pulled from your response data automatically, once a form has at least a handful of responses
What's included
SiliForm is 100% free — there's no paid tier gating form-building, response collection, or analytics:
| Included | Free |
|---|---|
| Forms & responses | Unlimited |
| AI form generation, all block types | Yes |
| AI input validation & drop-off analytics | Yes |
| Basic analytics | Yes |
| UTM tracking & attribution | Yes |
| AI response summary (themes/sentiment) | Yes |
| HubSpot & Zapier | Yes |
| Webhooks | Yes |
| Remove SiliForm branding | Coming soon |
The only things not included yet are removing the "Made with SiliForm" badge and custom logo upload, both reserved for a future paid plan — everything else is free, no card required.
SiliForm vs. Typeform vs. Google Forms
The three tools sit at different points on the same spectrum — from purely static data collection to fully adaptive conversation:
- Google Forms is free, fast, and utilitarian. Every respondent sees the exact same fixed question list, and there's no AI involved in building or adapting the form.
- Typeform improves the respondent experience with a one-question-at- a-time interface and conditional logic, but the question set is still authored and fixed by the form creator — logic branches are manual, not AI-generated.
- SiliForm keeps the one-question-at-a-time interface but adds AI at both ends: generating the form itself from a description, and — in dynamic mode — generating the next question live based on what a respondent just said.
For a fuller comparison across ten tools, including free-tier limits and pricing, see 10 Best Typeform Alternatives in 2026.
From responses to decisions
SiliForm doesn't just show charts and numbers. It highlights friction points, unclear questions, and behavioral signals in the response data — helping teams understand why responses look the way they do, not just what they say on the surface.
Forms shouldn't just collect answers — they should reveal understanding.