Figr vs Promptotype

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Figr compared with Promptotype
Detail	Figr	Promptotype
What it does	AI product design agent that learns your product to create UX flows and Figma-ready designs	Platform for developing, testing, and monitoring structured LLM tasks
Stage	Not given	Not given
Founded	Not given	Not given
Based in	Not given	Not given
Pricing model	Not given	Freemium
Pricing	Free plan with 10 monthly credits, 3 canvases, 1 Context Pod, and 200MB storage. Starter: $32/month (billed yearly) or $39/month (billed monthly) for 200 monthly credits, unlimited canvases, 1 full-access seat, 3 Context Pods, and 1GB storage per pod. Max: $124/month (yearly) or $149/month (monthly)	Free plan at $0/month includes advanced prompt engineering playground and test queries. Basic plan at $6/month adds prompt template library and collection testing. Professional plan at $10/month includes 60-day run history, fine-tuning, and 1 weekly scheduled run. Yearly pricing available with 2 mon
Key features	Visual Context Graph - a living map of how your product works Context Pod - reusable memory for product context Figma Sync - move work in and out of Figma cleanly Design System Intelligence - designs that respect components and tokens UX Reasoning - thinks through UX before designing Live Product Capture - screen recording analysis AI high-fidelity prototype generation Real-time collaboration with comments Export to Figma, React, and code formats	Advanced prompt engineering playground Design prompt templates with extended playground Define test queries with expected result JSON schemas or values Test prompts across entire query collections Function calling support Run and test history tracking Schedule periodic automated tests Model fine-tuning from collections Team collaboration Prompt template and model library management
What makes it different	Starts from product context and existing design systems, not generic prompts Understands complex SaaS workflows, permissions, and edge cases Does UX reasoning work before generating designs Outputs that look like your team made them, respecting design systems Credit-based pricing that scales with design effort, not seats	Structured approach to prompt engineering with JSON schema validation Test entire collections of queries simultaneously for production readiness Automatic expected result generation from model outputs Full function calling support in playground and testing
Community votes	0	0
DR (Domain Rating by Ahrefs)	52 +2 (up) since last check	17 no change since last check
Trust Flow (Majestic)	25	3
Citation Flow (Majestic)	46	26
Referring domains (Majestic)	3199	40

4 details filled in for both companies.

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