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

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

Aloud

Wojciech Dobry

Free

Aloud records you talking through your app, cleans up what you actually meant, and hands your coding agents a precise plan with screenshots.

Synchronized Voice, Screen, and Transcript Capture: Records all three together for sessions lasting minutes or hours, while keeping the recorder UI itself out of the captured video.
Intent-Aware Transcript Cleanup: Rewrites raw speech into what you meant — merging split sentences, removing filler, and keeping only the calls you stood by after changing your mind.
Automatic Screenshot Resolution: Detects deictic phrases like 'this', 'here', or 'that button' and suggests the exact recording frame, with per-frame scrubbing and cropping before insertion.
Clarifying Questions: When a request such as 'make it feel lighter' is ambiguous, Aloud asks and offers concrete options rather than guessing at your intent.
Task Grouping and Planning: Organizes feedback into named groups and tasks, tagging each with the model tier it needs — fast model versus reasoning.
Self-Contained Agent Export: Produces one file with prompt and images included that drops straight into Claude Code, Cursor, or Codex.
On-Device Whisper Transcription: Audio and video are processed locally on Apple silicon and never leave the Mac; only transcript text is sent when you ask for cleanup.

Reviewing an Agent-Built UI: Walk through a freshly generated interface out loud and hand back a precise, screenshot-annotated punch list instead of typing every nit.
Reducing Ambiguous Prompts: Avoid the wasted agent runs and token spend that follow vague feedback, by catching ambiguity while you are still pointing at the screen.
Long-Form Design Critique: Capture an hour of design commentary in one pass and let Aloud distill it into discrete, actionable tasks.
Async Feedback Handoff: Non-engineers record their reactions to a build and the export goes directly to whoever's agent is doing the work.
Bug Reporting with Visual Context: Narrate a reproduction while recording, so every step arrives paired with the frame that shows the problem.
Privacy-Sensitive Workflows: Teams that cannot send screen recordings to a cloud service keep audio and video entirely on-device.

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.