AEO Audit is a free tool that scores B2B SaaS websites for AI search visibility — how likely they are to be cited by ChatGPT, Perplexity, and Google AI Overviews when B2B buyers search.

What is AI Engine Optimization (AEO)?

AI Engine Optimization (AEO) is the practice of structuring content, entity signals, and technical infrastructure so that AI engines cite your brand in generated answers. It extends traditional SEO to cover ChatGPT, Perplexity, Gemini, and Google AI Overviews.

Yes. AEO Audit is free. Enter any B2B SaaS brand and receive a full AI visibility score with prioritised recommendations.

How does AEO Audit score websites?

AEO Audit scores across six pillars: AI Visibility (22%), Brand Authority (23%), Content Quality (18%), Platform Optimization (15%), Structured Data (12%), and Technical AEO (10%). Each pillar reflects specific signals that AI engines use when deciding which sources to cite.

Subcategory · AI Citation Index

Who AI is citing in Error Tracking

AI cites Logrocket and Sentry for error tracking, but neither dominates shortlists; the category shows weak AI visibility overall.

Brands tracked

Avg AEO score

68/100

Citation coverage

of brands cited at least once

Dominant brands

cited > 50% of queries

Discovery stage

The shortlist

When buyers ask AI for the best Error Tracking software

No discovery-stage prompts have been scored against this category yet — once the shortlist cron runs, this section will surface which brands AI cites most.

Evaluation stage

The battleground

How brands fare on comparison queries · category median 17/100

Logrocket leads head-to-head evaluations with an average score of 34 across 4 comparison queries. Sentry scored 0 across 6 comparison queries, well below the category median of 17. The delta suggests Logrocket's session replay and frontend monitoring features resonate more in direct evaluations than Sentry's core exception tracking.

Each brand's evaluation score averages how AI responds to head-to-head comparison queries that mention them. Above-median brands win their comparisons more often than they lose.

Trends

Over the last 12 months

Too few audits to establish a trend. The two available months show average scores rising from 58 in March 2026 to 68 in April, but sample sizes of 2 and 4 are insufficient for meaningful pattern recognition. Sentry is flagged as rising with a delta of 11 points.

Biggest gain

Sentry

+11 pts

Editorial picks

Brands worth watching

Logrocket

Logrocket scores 72 and wins 34 average points in head-to-head comparisons, the highest evaluation performance in the category. Its session replay and frontend analytics differentiate it from pure exception trackers.

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Sentry

Sentry scores 63 but averaged 0 in 6 comparison queries, indicating weak relative positioning despite being flagged as rising with an 11-point delta. The brand appears in audits but rarely wins citation weight against alternatives.

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Airbrake

Airbrake appears in featured candidates but has no scored audits. Its presence suggests legacy recognition in error tracking, though AI models show no measurable citation activity in the current dataset.

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FAQ

Error Tracking questions, answered

What is the best error tracking software for web applications?+

Logrocket scores highest at 72 in the available audits, followed by Sentry at 63. Neither brand achieves consistent shortlist presence, indicating AI models do not yet strongly favor one tool for discovery-stage queries.

How does Logrocket compare to Sentry for error tracking?+

Logrocket outperforms Sentry in head-to-head comparisons with an average evaluation score of 34 versus Sentry's 0 across six queries. Logrocket's session replay and user experience monitoring capabilities appear to give it an edge in comparative evaluations.

Which error tracking tools do AI models recommend most often?+

Neither Logrocket nor Sentry appears on AI shortlists despite being the only brands with scored audits. The category's 0% shortlist coverage rate across 13 prompts suggests AI models lack strong training signals for error tracking recommendations.

Are error tracking tools gaining visibility in AI recommendations?+

Data is insufficient to confirm a trend. Average scores rose from 58 to 68 between March and April 2026, but sample sizes of 2 and 4 audits are too small for meaningful pattern analysis. Sentry shows an 11-point rise, flagged as the category's rising brand.

What error tracking tools should developers evaluate besides Logrocket and Sentry?+

Airbrake, Atatus, Bugzilla, Cypress, and Lightrun appear as featured candidates but have no scored audits in the dataset. Their inclusion suggests historical relevance, though current AI citation activity is unmeasured.

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