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Overview

FaceSign’s node-based flow system allows you to create sophisticated verification workflows tailored to your specific requirements. Here are battle-tested flows for common use cases.
Camera buffer requirementVideo-analysis nodes — liveness_detection, face_scan, face_compare, and recognition — need at least 5 seconds of accumulated camera feed before they can run. A conversation node with actual avatar speech is the canonical way to set up that buffer and must precede the first video-analysis node in the flow.Other nodes that keep the camera live during their UI — two_factor_email and two_factor_sms — also accumulate camera feed, so when they sit between the start of the session and the first video-analysis node they can substitute for the greeting conversation.Once the buffer is established, subsequent video-analysis nodes chain back-to-back without another conversation in between. See Conversation Rules → Greeting length for the full rule.

Basic Step-Up Verification

Simple Liveness Check

Confirm a real person is in front of the camera and rule out photos, videos, or deepfake spoofs. Liveness detection requires camera access and at least 5 seconds of accumulated video feed, so a short greeting CONVERSATION must precede the liveness node to give the camera time to warm up.
Basic Liveness Detection

Document Verification with Selfie

Standard KYC flow: verify government ID and match it with a selfie.
Document + Face Match

Document Scanning Flow

When using document_scan followed by face_compare, prep the user with a conversation node before launching the scanner. The face_scan node triggers a dedicated selfie capture UI — if you do not need an explicit selfie step, skip it. Biometrics are captured naturally during any session, and recognition on subsequent sessions will match against faces seen before without an explicit enrollment step.
Document scan with face comparison
The conversation node before document_scan uses an empty string condition (condition: '') for unconditional advancement — the avatar speaks the prep message and immediately transitions to the scanner.

Two-Factor Authentication

Both two_factor_email and two_factor_sms collect a contact and verify an OTP. Prefer enter_email followed by two_factor_email for most integrations. Email OTPs deliver reliably, the form-to-OTP handoff works cleanly, and you avoid SMS delivery costs.
two_factor_sms currently has a known form-to-speech handoff timing issue where the avatar occasionally asks for the phone number verbally after the form submit. If SMS is required, audit the transition carefully before production use.

Multi-Factor Authentication Flow

Combine email and SMS verification with biometric checks.
Email + SMS + Biometric

Advanced Verification Flows

Conversational AI Verification

Use AI-powered conversation for dynamic verification questions.
AI Conversational Flow

Industry-Specific Flows

Financial Services KYC

Complete KYC flow for banking and financial services with enhanced fraud detection.
Banking KYC Flow

Healthcare Patient Verification

HIPAA-compliant patient verification flow.
Healthcare Patient ID

Age Verification for Restricted Content

Quick age verification for alcohol, gambling, or adult content.
Age Verification Flow

Testing Your Flows

Before deploying to production:
  1. Sandbox Testing: Use test API keys to verify flow logic
  2. Error Handling: Test all failure paths
  3. Performance: Monitor flow completion times
  4. Compliance: Ensure flows meet regulatory requirements

Next Steps

Node Reference

Complete field reference for all node types

Languages & Localization

Set up multilingual flows with proper prompt style

Production Checklist

Everything to verify before going live