Doop vs Visiby: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Doop and Visiby — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Doop

Kevin Goedecke

Free

Open-source infinite design canvas where humans and AI agents design together live, with agents joining through a built-in MCP server.

Agent-Native MCP Canvas: Agents connect over an HTTP MCP endpoint with a single command and one browser OAuth approval, then edit the canvas as you, attributed and accountable, with no API keys handed over.
Streaming Frames: Every section an agent writes renders on the canvas the moment it lands, so you watch the design arrive rather than waiting on a spinner.
Comments as Tasks: A note left anywhere on the canvas becomes a task the right agent picks up, works on, and replies to with a screenshot, turning feedback directly into the backlog.
Agent Self-Review: A built-in headless renderer gives agents screenshots of their own frames so they judge fit, spacing and contrast like a senior designer and correct issues before handoff.
Shared Canvas Memory: Tasks, decisions and comments live on the canvas rather than in one agent's context, so any agent that joins later plugs into the same state and continues.
Learned Taste Profile: Casual feedback such as 'rounder corners' or 'keep it to the blue' is distilled into a persistent taste profile applied to every new frame and inherited by every agent.
Live Export URLs: Each frame is a URL that can be embedded in a doc, a post or an og:image and re-renders whenever the design changes, so shared assets never go stale.
Reference and URL Import: Paste screenshots to have agents distill palette, type and mood into a written brief, or paste a public URL to land an editable snapshot of your existing page on the canvas for side-by-side variants.

Agent-Assisted Landing Pages: Steering Claude Code or Codex through hero, pricing and footer frames on one canvas and watching each render live.
Design Review Loops: Leaving contrast or spacing notes on a frame and letting an agent apply the fix and return a screenshot without a synchronous handoff.
Redesign Comparison: Importing an existing public page as an editable snapshot so agent-generated variants sit next to the original instead of replacing it blind.
Team Design Sessions: Multiple people and multiple agents working the same canvas, each seeing what the others' agents are doing in real time.
Style Consistency: Building a canvas taste profile once so every subsequent frame and every new agent inherits the same corner radius, palette and type decisions.
Always-Fresh Shared Assets: Embedding live frame URLs in documentation or social posts so the shared image updates automatically when the design changes.

FNA Technology

Paid

AI visibility platform that tracks how ChatGPT, Perplexity, Claude, Gemini and AI Overviews cite your brand, and ships fixes.

AI Citation Tracking: Continuously samples roughly 50,000 prompts per week across ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews to record where and how a brand is cited.
Per-Engine Visibility Scoring: Reports a composite AI Visibility score plus share of voice and prompts won or lost, broken out engine by engine so declines can be traced to a specific model.
Prompts & Citations Explorer: Lets teams open any tracked prompt and read the actual model answer to see which competitor was named and why.
Brand Entity Analysis: Maps the adjectives each engine associates with your brand versus competitors and suggests reframing plays to change that portrait.
Competitor Intelligence: Tracks rival citation share on comparison and 'alternatives to' prompts, highlighting categories where a competitor dominates.
Prioritized Action Plan: Converts findings into P0/P1 recommendations such as schema additions or comparison pages, each with a time estimate and projected score gain.
Site Audit for AI Parseability: Audits pages for missing entity definitions, structured Q&A data and other signals that prevent models from citing the site correctly.
White-Label Reporting and API: Higher tiers add white-label client reports, SSO/SAML and API access for agencies managing multiple brands.

AI Search Monitoring: Marketing teams track whether ChatGPT and Perplexity recommend their product or a competitor on high-intent category prompts.
Competitive Benchmarking: Brands quantify how much citation share a named rival is capturing on 'alternatives to' and 'best of' queries.
Content Prioritization: Content teams decide which pages to write or refresh based on which prompts are currently missed rather than on keyword volume alone.
Technical AEO Audits: SEO specialists find pages lacking FAQ schema or entity markers that keep answer engines from parsing them.
Agency Client Reporting: Agencies run pooled prompt tracking across multiple client workspaces and deliver white-label AI visibility reports.
Executive Reporting: Operators present a weekly digest showing search clicks alongside AI citation share to explain traffic shifts leadership sees.