AI Visibility Tracking

Recall vs OtterlyAI

Recall measures how ChatGPT, Copilot, Perplexity, Gemini, and Google AI Overviews answer the questions your buyers ask, and keeps the evidence: the stored answer behind every number, the pages it cited, and which of the four causes of an absence applies. Then it measures whether the fix worked. OtterlyAI is an AI visibility tracking tool covering the same engines.

Recall

Evidence-LinkedCause AttributionWhite-Label

Measures how ChatGPT, Copilot, Perplexity, Gemini, and Google AI Overviews answer your buyers’ questions, and keeps the evidence: the stored answer behind every number and the pages it cited.

OtterlyAI

AI Visibility Tracking

Gartner Cool Vendor 2025 with GEO Audit (25+ factors)

OtterlyAI at a glance

Screenshot of OtterlyAI homepage

About OtterlyAI

OtterlyAI was named a Gartner Cool Vendor 2025 and reports over 20,000 users. Their GEO Audit evaluates 25+ on-page factors for AI readability. They also offer AI keyword research, crawler simulation, and industry benchmarks.

Popularity grade: A

  • Gartner Cool Vendor 2025
  • 20,000+ users
  • GEO Audit evaluating 25+ on-page factors

Feature comparison

FeatureRecallOtterlyAI
Core Tracking
Multi-LLM Tracking
AI Visibility Score
Citation Analytics
Competitor Benchmarking
Brand Mention Tracking
Platform
White-Label / Agency
Open Source
Content Generation
Advanced Analytics
Prompt Volume Estimates
Sentiment Analysis
AI Crawler Analytics
Geographic Tracking
Social Media Tracking
Shopping Tracking
Multi-Language
Actionable Insights
Action Recommendations
Content Gap Analysis
AI Site Audits
AI Keyword Research
Reporting & Integration
Email Alerts
Data Export / API
BI Connectors

Key differences

Only in Recall

  • Multi-Language
  • Data Export / API

Both offer

  • Multi-LLM Tracking
  • AI Visibility Score
  • Citation Analytics
  • Competitor Benchmarking
  • Brand Mention Tracking
  • White-Label / Agency
  • Geographic Tracking
  • Action Recommendations
  • AI Site Audits
  • Email Alerts

Only in OtterlyAI

  • AI Crawler Analytics
  • AI Keyword Research

What you get with Recall

Evidence, not a black-box score

Inspect the underlying prompt, answer, citations, engine, locale, and run outcome behind each metric.

The cause, not the score

An absence has four causes and four different fixes. Every recommendation names which one it answers, so the work is chosen by the reason rather than the size of a number.

Your data stays yours

Every answer, citation, and measurement exports in full at any time. You own the record and can take it with you wherever you want to use it.

Matched before and after

Lock the prompt, engine, locale, scoring method, and sampling plan before a change ships, then report the result with its uncertainty.

/ FAQ

Frequently Asked Questions

What is the difference between Recall and OtterlyAI?
OtterlyAI is an AI visibility tracking tool. Recall is an answer-engine measurement platform: it runs your questions repeatedly, stores every answer and the pages each one cited, and reports a share of answers with the confidence interval around it. Where you are missing, it names the cause — the engines cannot read your pages, cannot tell who you are, are not reading sources that mention you, or describe you in the wrong terms — because each of those has a different fix.
What do you get with Recall that a visibility score does not give you?
The working behind it. Every figure opens onto the answers it was computed from, with the cited pages captured at the moment they were cited. Recommendations are tied to a named cause rather than a lower score, and once you ship one, Recall re-measures the same questions and reports whether the answer actually changed — including when the result is inconclusive.
Is OtterlyAI open source?
No, OtterlyAI is a closed-source hosted product. Recall is closed-source and hosted as well; what it publishes is the evidence under each number — the stored answer, the pages cited, and the interval around the figure.
Can I self-host Recall?
Not at the moment. Recall runs as a hosted platform, with each customer's data isolated at the database level. Measuring answer engines means paying for every answer collected, which is why it ships as a service rather than something you run yourself.

Ready to track your AI visibility?

Start with the buyer questions closest to revenue or deal flow, preserve every answer and source, then measure whether the work changed the shortlist.