Use cases/Events + communities

Speaker Submission

Evaluate proposals with AI-generated relevance scores.

The problem with speaker forms

  • Hundreds of submissions, manual scoring
  • Abstract quality varies wildly
  • No way to filter by topic or experience
  • Availability conflicts discovered late

How NativeForm fixes this

  • Conversation captures title, format, level, and topics
  • Smart Fields score proposal quality and relevance
  • Asks about speaking experience naturally
  • Availability captured upfront

Describe it. AI builds it.

Tell NativeForm what you need. It generates the right questions. When users struggle to answer, AI helps them go deeper to give you richer, more complete responses.

You say

"I need a speaker submission form for a tech conference"

NativeForm generates
  • What's your talk title?
  • What will attendees learn?
  • Is this a talk, workshop, or panel?
  • What experience level is it for?
  • Tell us about yourself as a speaker
  • Which days/times work for you?

Smart Fields: insights, not just data

Define what you want to extract. AI reads each response and computes actionable fields: sentiment, urgency, categories, scores. No manual tagging, ever.

Relevance score

Prompt: Rate proposal fit 1-100 based on topic, depth, and speaker experience

Response says

"Production RAG lessons from ML Lead with conference experience"

88
Experience level

Prompt: Speaker experience: first-time, some, experienced, expert

Response says

"Spoken at 3 conferences, led workshops"

experienced

Checkbox data vs real insights

AI helps users articulate what they really mean. The result: responses you can actually act on.

Traditional speaker submission form
Title: Building RAG Systems
Abstract: How we built a RAG system and what we learned
Format: Talk
Level: Intermediate
Topics: AI, retrieval
Speaker: Jane Doe, ML Lead at TechCo
Experience: Spoke at 3 conferences
Availability: Day 1 afternoon
NativeForm speaker
Title: Building Production RAG Systems
Abstract: Lessons from deploying RAG at scale...
Format: 30-min talk with demo
Level: Intermediate
Topics: AI, infrastructure, best-practices
Speaker: Jane Doe, ML Lead at TechCo
Experience: 5+ years, spoke at 3 conferences
Availability: Day 1 or Day 2, afternoon preferred
Experience level: experienced (Smart Field)
Relevance score: 88 (Smart Field)

Now, act on it

This is where it all comes together. Smart Fields become triggers. Route urgent issues instantly. Alert the right team based on sentiment. Update your CRM with qualified leads. All automatic, all based on AI understanding.

Make
n8n
New submission
Add to proposals database
If Relevance score ≥ 85AI
Fast-track for review
If Experience = first-timeAI
Assign speaker mentor
If Relevance score < 50AI
Send decline email

Works with 1000+ apps via Make, n8n, and Zapier

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Ready to transform your speaker submission?

Request early access and tell us about your use case. We'll help you set up a form that actually works.

Request early access

The early access form is built with NativeForm.