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AI Consensus Fit Review

MonitorAEO AI Search Audit Fit Review for Mid-Market Companies

MonitorAEO is a good fit for mid-market companies that want a fast, low-cost, multi-engine AI search audit with competitor, citation-source, and prioritized-action outputs.

Research: 2026-09-187 usable platform responsesRead the methodology ↗

Answer Capsule

MonitorAEO is a good fit for mid-market companies that want a fast, low-cost, multi-engine AI search audit with competitor, citation-source, and prioritized-action outputs. Two of the seven platforms in this study named MonitorAEO during the ranking stage (deepseek and kimi), where it averaged rank 1.5 and reached rank 1. The strongest reason to consider it is the Full Audit's five-engine, 40-query, 200-answer scope at a $79 one-time price [1]. The main limitation is that the evidence is almost entirely company-owned: no independent validation of accuracy, repeatability, or customer outcomes was found, and the audit is a point-in-time snapshot that the provider itself says will drift [3].

Research Snapshot

FieldFinding
Platform mentions in ranking stage2 of 7 platforms (deepseek, kimi)
Share of included platform responses28.6%
Average listed rank1.5
Best listed rank1
Relevant product/model/planFull Audit; Full Audit (All 5 Engines)
Overall use-case fitGood (five platforms rated "good," two rated "strong")
Research date2026-09-18

Why MonitorAEO Qualified for This Study

Questions This Section Answers

  • Is MonitorAEO a good choice for AI Search Audits for Mid-Market Companies?
  • Why did only two of seven AI platforms name MonitorAEO in the ranking stage?

MonitorAEO qualified because it cleared the study's minimum-mention threshold and because its Full Audit maps directly onto the six configured audit criteria: recommendation analysis, mention and citation measurement, competitor benchmarking, influential source-domain analysis, content and authority gaps, and a prioritized improvement roadmap [4]. Two platforms named it during ranking discovery — deepseek at rank 1 and kimi at rank 2 — giving it a 28.6% share of included platform responses and an average listed rank of 1.5. All seven platforms went on to evaluate its fit for this use case, and five rated it "good" while two (google and grok) rated it "strong."

The qualification is narrow rather than broad. MonitorAEO did not appear in every platform's ranking set, and independent reviews checked during this research placed stronger emphasis on competing tools for sustained monitoring and benchmarking programs [6]. Buyers should read the two ranking mentions as evidence of relevance to the use case, not as proof of product superiority.

The Product, Model, Plan, or Service Most Relevant to AI Search Audits for Mid-Market Companies

Questions This Section Answers

  • Which MonitorAEO plan should a mid-market buyer choose for a one-time five-engine AI search audit?
  • Does the MonitorAEO Full Audit include competitor benchmarking and citation measurement?

The relevant offering is the Full Audit, also described as Full Audit (All 5 Engines). It is a one-time diagnostic priced at $79 that runs 40 buyer-facing queries across Google AI Overviews, ChatGPT, Claude, Perplexity, and Gemini — 200 analyzed AI answers in total — and includes an engine heatmap, per-engine sentiment and accuracy scoring, and a prioritized action plan [8]. A cheaper Two Engine Audit at $29 covers only Google AI Overviews and ChatGPT, producing 80 answers [10].

The Full Audit's stated outputs include competitor share of voice, a map of top-cited source domains, per-query drill-down evidence, 15 GEO-foundation checks, and hallucination flags [8]. The provider advertises a completion time of roughly 5–10 minutes because queries run in parallel and a second-pass LLM scoring step follows [12]. A free eight-question preview on Google AI Overviews is available before purchase [9].

For buyers who need recurring data rather than a snapshot, MonitorAEO sells Full Monitoring at $95 per month, which includes monthly five-engine reruns, 40 monitored questions, trend tracking, and a refreshed action plan [13]. The audit and the monitoring subscription are separate purchases.

What the AI Platforms Agreed About

Questions This Section Answers

  • What do multiple AI platforms agree the MonitorAEO Full Audit delivers for mid-market buyers?
  • Is the MonitorAEO Full Audit worth it for a mid-market team that needs five-engine coverage at low cost?

The clearest cross-platform agreement concerns scope and price. Multiple platforms independently reported that the Full Audit covers five engines, runs 40 queries, analyzes 200 answers, and costs $79 as a one-time purchase [14]. Grok described the same figures and called the fit "strong" for mid-market buyers who want snapshot visibility without subscriptions or enterprise overhead [18].

Platforms also broadly agreed that the audit addresses the configured criteria. OpenAI, grok, kimi, and google all reported that the Full Audit includes competitor share-of-voice analysis, top-cited source domains, and a prioritized action plan split into content, schema, and entity fixes [14]. Kimi specifically described a "PR target list" of the top 20 domains AI engines pulled from when answering category questions [16].

A third area of agreement was low friction. Platforms noted that no tagging, plugins, or DNS changes are required, that the free preview lowers evaluation risk, and that the one-off purchase avoids long-term contracts [20]. This agreement reflects consistent reporting across platforms; it does not independently validate product quality or outcomes.

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Does the MonitorAEO Full Audit actually include competitor benchmarking and source-domain analysis, or is that unverified?
  • Is MonitorAEO's monitoring subscription enough for ongoing AI visibility tracking, or do buyers need a different tool?

The sharpest disagreement concerns competitor benchmarking and source-domain analysis. OpenAI, grok, kimi, and google reported these as included deliverables [22]. Anthropic stated that MonitorAEO's product documentation "does not explicitly describe competitor benchmarking capabilities" and flagged the absence of share-of-voice calculation detail as a limitation [26]. Perplexity rated the same factors "unclear," saying public materials did not clearly verify domain-level source analysis or citation-share measurement [28]. This is a genuine conflict in platform findings, not a settled question.

Monitoring depth drew similar uncertainty. Anthropic reported that subscription documentation says "monthly re-runs" but does not specify whether alerts, multi-run aggregation, or comparative baselines are included [31]. Kimi noted that monitoring pricing was undisclosed on the audit page and that total cost of ownership was therefore unclear [24]. OpenAI, by contrast, described Full Monitoring as including trend charts, alerts, and source and competitor changes [32].

Pricing transparency also split by platform. Deepseek reported that pricing was not public and that the site indicated custom quotes, with low pricing confidence [33]. Every other platform reported the $29/$79 audit and $35/$95 monthly figures from public pages [34]. Deepseek's research date was 2026-04-11, five months before the authoritative run date, which may explain the discrepancy.

Finally, platforms disagreed on overall fit strength. Google called MonitorAEO "an outstanding, cost-effective fit" and grok called it a "strong fit" [25], while anthropic concluded it "falls short as a complete AEO platform for teams building sustained AI visibility programs" [31]. The difference tracks how much weight each platform placed on one-time audit value versus ongoing program needs.

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • Which MonitorAEO Full Audit features matter most for a mid-market company auditing AI search visibility?
  • Does the MonitorAEO Full Audit cover content and authority gaps, or only mention tracking?

Recommendation and citation measurement are the audit's core outputs. For each engine-query combination, MonitorAEO reports whether the brand is named in the answer text and whether the buyer's domain is cited as a source, with per-query drill-down evidence [38]. The Full Audit analyzes 200 answers and includes an engine heatmap and citation map [40].

Competitor benchmarking is reported as share of voice based on rivals named in the same answers, with competitor mentions and citations available in the drill-down [38]. Public materials do not specify competitor-selection controls, normalization methodology, or statistical confidence intervals [38]. Anthropic and perplexity both flagged this as unverified [43].

Influential source-domain analysis appears as a top-20 list of domains cited by AI engines in the buyer's category, positioned as potential PR or earned-mention targets [38]. The public materials do not establish that these domains are independently verified as authoritative or that source influence is causal [38].

Content and authority gaps are the weakest-documented criterion. OpenAI rated this factor "neutral," noting that the report identifies gaps by query type but does not confirm a comprehensive content inventory, backlink analysis, topical-authority model, or page-level gap mapping [38]. Kimi similarly reported that gap identification is organized by query type — brand, category, problem, comparison, and vertical — without traditional keyword-difficulty or backlink-gap analysis [42].

The prioritized roadmap is included in every paid tier. It is a Claude-generated checklist divided into content, schema, and entity fixes, with rationale, expected impact, and a concrete next step [38]. The provider describes these recommendations as educated guesses and does not warrant business outcomes [47]. Public pages do not define how expected impact is calculated [38].

Technical AI-readiness coverage comes from 15 GEO-foundation checks covering items such as robots.txt, sitemap, llms.txt, schema, server-rendered content, metadata, and performance [38]. Kimi noted it was unclear whether these checks are bundled into paid audit tiers or sold separately [42]. This complements AI-search measurement but is not a substitute for a broader technical SEO audit [38].

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does the MonitorAEO Full Audit cost, and are there setup or cancellation fees?
  • What does MonitorAEO Full Monitoring cost per month, and can a mid-market buyer cancel anytime?

The Full Audit is listed at $79 as a one-time purchase, and the Two Engine Audit at $29 one-time; a free eight-question preview requires no card or signup [49]. The $79 price includes all five engines, 40 queries, 200 analyzed answers, scoring, drill-down evidence, the action plan, 15 GEO checks, dashboard access, and CSV export [49]. Applicable tax is calculated and added by Stripe at checkout [49].

Ongoing costs are separate. Full Monitoring is listed at $95 per month and includes monthly five-engine reruns, 40 monitored questions, trend tracking, source and competitor changes, and a refreshed action plan; Two Engine Monitoring is listed at $35 per month [50]. No separate audit fee beyond the listed price is publicly documented, and agency or volume pricing is referenced for monitoring but the amount is unclear [49].

Contract terms are relatively light. One-off audits are charged once [52]. If an audit fails to run successfully, MonitorAEO states it issues an automatic full refund; if the audit runs but is unsatisfactory, the terms state the buyer should contact support within 14 days for a rerun or full refund [52]. Monitoring can be canceled at any time, with access continuing through the current billing period and no prorated refund [52]. The terms state that disputes are governed by New South Wales, Australia law and courts [52].

Two pricing caveats matter. Deepseek reported that pricing was not publicly listed and that the site indicated custom quotes, with low pricing confidence — a direct conflict with the other six platforms [54]. And kimi reported that monitoring pricing was undisclosed on the audit page, making total cost of ownership unclear from that page alone [55]. Buyers should confirm current prices at checkout rather than relying on any single platform's summary.

Best Suited For

Questions This Section Answers

  • Who gets the most value from a MonitorAEO Full Audit for mid-market AI search intelligence?
  • Is MonitorAEO best for a one-time AI visibility baseline or for ongoing tracking?

MonitorAEO's Full Audit is best suited to cost-sensitive marketing, SEO, content, and PR teams that need a fast five-engine baseline [56]. It fits companies evaluating AI visibility across brand, category, problem, comparison, and vertical queries, since those are the five query types the audit covers [58].

It also suits teams that value a concrete action checklist and CSV-exportable evidence over consulting services [60]. Buyers who want a one-time diagnostic before committing to ongoing monitoring are a stated target, as are teams that need visibility across Google AI Overviews, ChatGPT, Claude, Perplexity, and Gemini in a single report [61].

Platforms also identified mid-market companies with limited AEO/GEO budget wanting a one-time comprehensive snapshot, and organizations prioritizing buyer-query coverage and multi-engine breadth over deep technical SEO remediation [59]. Grok summarized the fit as mid-market US companies needing snapshot visibility across five AI engines without subscriptions or enterprise overhead [62].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose MonitorAEO for AI Search Audits for Mid-Market Companies?
  • Is MonitorAEO a poor fit for a mid-market buyer that needs validated measurement methodology or enterprise governance?

Buyers who require independently validated measurement methodology or audited performance outcomes should look elsewhere. No independent review, benchmark, validation study, or customer-outcome evidence was identified in the checked sources [63]. Anthropic reported no public customer case studies, G2 reviews, or independent testimonials confirming mid-market adoption or outcomes [66].

Large multi-brand programs needing enterprise governance, integrations, custom query volumes, or formal service commitments are also a poor fit. Public materials do not document SSO, role-based access, API access, procurement documentation, or support response targets for the Full Audit [63]. Anthropic reported no documented multi-user access, team workflows, or client-facing reporting suitable for agencies [67].

Buyers needing a full content inventory, backlink or authority audit, or guaranteed causal recommendations should not treat this as a substitute. The provider describes recommendations as educated guesses and does not warrant business outcomes [65]. Organizations requiring continuous monthly monitoring and competitive benchmarking as a single integrated purchase should note that monitoring is sold separately [68].

Finally, buyers whose purchase decision depends on clearly verified competitor benchmarking, source-domain influence analysis, or enterprise procurement detail should treat those as open questions rather than settled deliverables [69].

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to MonitorAEO for a mid-market buyer that needs continuous AI visibility monitoring?
  • When should a mid-market buyer choose a different AI search audit provider instead of MonitorAEO?

Choose a more enterprise-oriented AI-search intelligence platform or specialist consultancy when the buyer needs larger custom query sets, multi-market coverage, integrations, governance, analyst interpretation, or formal service commitments [72]. Choose an SEO or content intelligence platform in addition to or instead of MonitorAEO when the primary need is comprehensive page-level content gaps, backlink authority, topic modeling, or technical SEO remediation [72].

For ongoing daily or weekly monitoring with instant alerts, platforms reported that alternatives such as Omnia and Profound offer real-time visibility with action layers mid-market teams expect [73]. When competitor benchmarking and share-of-voice are primary requirements, tools like Profound and AEO Vision were reported to include multi-competitor tracking and comparative share-of-model scoring [73]. For multi-client or agency workflows, Peec AI and RankScale were reported to serve multi-client teams, while MonitorAEO has no documented agency features [73].

Budget-tier alternatives exist below MonitorAEO's entry point: Otterly was reported at $25–$29 per month and AEO Vision at $9 per month for basic monitoring, though with fewer engines [73]. Kimi listed additional alternatives by need: TriRank at $999 per month for done-for-you tracking, Profound at $99–$399 per month for monitoring, SEOGrade.ai at $349–$997 for board-ready deliverables, and free tiers from TurboAudit and Metronyx AI for budgets under $30 [74]. These alternative names and prices are platform-reported and were not independently verified in this study.

One internal consideration: buyers who need recurring trend data, alerts, and change tracking may prefer MonitorAEO's own Full Monitoring subscription over the one-off Full Audit [75].

Questions to Verify Before Buying

Questions This Section Answers

  • What should a mid-market buyer confirm with MonitorAEO before purchasing the Full Audit?
  • Can a buyer customize MonitorAEO's 40 audit queries and export raw engine evidence?

Several verification items recur across platforms. Confirm whether the 40 queries, locations, personas, products, and competitors can be customized before or after the Full Audit, since the 40-query matrix may be insufficient for companies with many products, regions, segments, or languages [76]. Confirm whether Google AI Overviews, ChatGPT, Claude, Perplexity, and Gemini results are captured consistently for the buyer's US locations and device context [76].

Ask how competitor share of voice, citation rate, sentiment, hallucination risk, and accuracy are calculated and normalized, and whether the buyer can export raw answers, URLs, timestamps, engine and model identifiers, and all scoring inputs rather than summarized CSV fields [76]. Ask whether the service retains submitted domains, prompts, answers, or reports, and what privacy and deletion controls apply [76].

Clarify operational edge cases: what happens if one engine is unavailable, rate-limited, or changes its search behavior during the audit, and whether model or search-provider changes are version-pinned during a customer's run [76]. Ask whether SSO, role-based access, API access, procurement documentation, and support response targets are available [76].

Finally, request a sample report for a comparable mid-market company and ask the provider to explain the evidence behind the prioritized roadmap, including how expected impact is calculated [76]. Confirm whether the 15 GEO-foundation checks are included in the Full Audit or sold separately, and whether monitoring includes automated alerts or snapshot-only monthly reports [78].

Final AI Consensus Verdict

MonitorAEO's Full Audit is a good fit for mid-market companies seeking a low-cost, multi-engine AI search snapshot with competitor, citation-source, and prioritized-action analysis. Five of seven platforms rated the fit "good" and two rated it "strong," with no platform rating it poor. The strongest consensus points are the $79 one-time price, five-engine coverage, 40-query and 200-answer scope, and the included action plan [79].

The consensus is not unanimous on depth. Platforms split on whether competitor benchmarking and source-domain analysis are genuinely delivered or only loosely documented, and on whether monitoring includes alerts and comparative baselines [85]. Company-owned citations materially outnumber independent ones, and no independent validation of accuracy, repeatability, or customer outcomes was found [79].

Treat the Full Audit as a fast diagnostic and prioritization tool, not as independently validated market intelligence or a complete content-authority audit. Verify query customization, methodology, data handling, and raw-evidence export before purchase [79]. Buyers who need sustained competitive positioning should compare it against the monitoring-first alternatives platforms named, and can review the broader AI Search Audits for Mid-Market Companies index for context across providers.

How This Review Was Produced

This review synthesizes fit-research responses from seven AI platforms — openai, anthropic, deepseek, grok, kimi, perplexity, and google — collected for the prompt: "A mid-market company wants a commercially practical AI search audit that identifies where it is being mentioned, cited, and recommended across major AI platforms, how competitors compare, which high-intent prompts matter most, and what actions would likely have the greatest strategic value. Which AI search audit providers would you recommend, and why?" The authoritative research date is 2026-09-18. MonitorAEO was named during ranking discovery by two of the seven platforms, and all seven evaluated its fit for this use case. No personal testing, customer interviews, or independent verification was performed. All product claims trace to the cited platform responses or the company-owned pages those responses referenced. This report is part of a wider ai search audits market intelligence collection.

Methodology Limitations

Several limitations apply. First, platform-reported research dates differ from the authoritative run date: deepseek's response is dated 2026-04-11, roughly five months earlier, while the other six platforms are dated 2026-09-18. Platform-reported dates are provenance metadata and do not independently prove freshness.

Second, company-owned citations materially outnumber independent citations in the supplied evidence. MonitorAEO's own product, pricing, monitoring, comparison, and terms pages account for the majority of citations; independent sources are limited to Trustmary, Windgrove AI, Stork.AI, and Useomnia. Company claims should not be described as independently verified.

Third, the supplied URLs were collected from platform responses and were not independently validated by the writer stage. Citations are platform-reported evidence, not independently verified facts.

Fourth, the reviewed terms page states it was last updated in May 2026, but product specifications and prices can change after the research date. The public materials also do not explain whether model or search-provider changes are version-pinned during a customer's run.

Fifth, no independent evidence was found to validate accuracy, repeatability, customer outcomes, or competitive superiority. The public pages describe expected impact in the action plan but do not define how expected impact is calculated. Where platforms disagreed — notably on competitor benchmarking, source-domain analysis, and monitoring alerting — this review preserves the conflict rather than resolving it.

Sources

Company-Owned Sources

  • Monitoraeo — see how AI engines describe your brand: https://www.monitoraeo.com/
  • AEO tools comparison (2026): honest pros and cons | monitoraeo: https://www.monitoraeo.com/aeo-tools
  • Pricing — monitoraeo: https://www.monitoraeo.com/pricing
  • Audit — AI visibility diagnostic | monitoraeo: https://www.monitoraeo.com/product/audit
  • Monitoring — track AI visibility every month | monitoraeo: https://www.monitoraeo.com/product/monitoring
  • Terms of Service — monitoraeo: https://www.monitoraeo.com/terms
  • Additional AI research evidence88 records
    1. AI research evidence record openai:c1
    2. AI research evidence record openai:c2
    3. AI research evidence record openai:c3
    4. AI research evidence record openai:c1
    5. AI research evidence record grok:0
    6. AI research evidence record anthropic:21-1
    7. AI research evidence record perplexity:c7
    8. AI research evidence record openai:c1
    9. AI research evidence record openai:c2
    10. AI research evidence record anthropic:11-2
    11. AI research evidence record google:1.2.1
    12. AI research evidence record anthropic:28-2
    13. AI research evidence record openai:c4
    14. AI research evidence record openai:c1
    15. AI research evidence record perplexity:c2
    16. AI research evidence record kimi:monitoraeo-audit-1
    17. AI research evidence record google:1.1.1
    18. AI research evidence record grok:0
    19. AI research evidence record google:1.2.1
    20. AI research evidence record anthropic:28-5
    21. AI research evidence record perplexity:c1
    22. AI research evidence record openai:c1
    23. AI research evidence record grok:0
    24. AI research evidence record kimi:monitoraeo-audit-1
    25. AI research evidence record google:1.2.1
    26. AI research evidence record anthropic:45-1
    27. AI research evidence record anthropic:45-3
    28. AI research evidence record perplexity:c2
    29. AI research evidence record perplexity:c4
    30. AI research evidence record perplexity:c7
    31. AI research evidence record anthropic:7-2
    32. AI research evidence record openai:c4
    33. AI research evidence record deepseek:c1
    34. AI research evidence record openai:c2
    35. AI research evidence record perplexity:c1
    36. AI research evidence record anthropic:11-2
    37. AI research evidence record google:1.1.8
    38. AI research evidence record openai:c1
    39. AI research evidence record anthropic:7-8
    40. AI research evidence record openai:c2
    41. AI research evidence record perplexity:c2
    42. AI research evidence record kimi:monitoraeo-audit-1
    43. AI research evidence record anthropic:45-1
    44. AI research evidence record perplexity:c4
    45. AI research evidence record google:1.4.6
    46. AI research evidence record anthropic:7-5
    47. AI research evidence record openai:c3
    48. AI research evidence record anthropic:28-5
    49. AI research evidence record openai:c2
    50. AI research evidence record openai:c4
    51. AI research evidence record anthropic:11-2
    52. AI research evidence record openai:c3
    53. AI research evidence record perplexity:c8
    54. AI research evidence record deepseek:c1
    55. AI research evidence record kimi:monitoraeo-audit-1
    56. AI research evidence record openai:c1
    57. AI research evidence record anthropic:28-2
    58. AI research evidence record google:1.4.6
    59. AI research evidence record kimi:monitoraeo-audit-1
    60. AI research evidence record openai:c2
    61. AI research evidence record perplexity:c2
    62. AI research evidence record grok:0
    63. AI research evidence record openai:c1
    64. AI research evidence record openai:c2
    65. AI research evidence record openai:c3
    66. AI research evidence record anthropic:1-13
    67. AI research evidence record anthropic:7-2
    68. AI research evidence record kimi:monitoraeo-audit-1
    69. AI research evidence record perplexity:c2
    70. AI research evidence record perplexity:c4
    71. AI research evidence record anthropic:45-1
    72. AI research evidence record openai:c1
    73. AI research evidence record anthropic:21-1
    74. AI research evidence record kimi:monitoraeo-audit-1
    75. AI research evidence record openai:c4
    76. AI research evidence record openai:c1
    77. AI research evidence record anthropic:7-2
    78. AI research evidence record kimi:monitoraeo-audit-1
    79. AI research evidence record openai:c1
    80. AI research evidence record openai:c2
    81. AI research evidence record grok:0
    82. AI research evidence record perplexity:c2
    83. AI research evidence record kimi:monitoraeo-audit-1
    84. AI research evidence record google:1.1.1
    85. AI research evidence record anthropic:45-1
    86. AI research evidence record perplexity:c4
    87. AI research evidence record anthropic:7-2
    88. AI research evidence record openai:c3

Independent Sources

  • Best AI Search Visibility Tools for Businesses in 2026: The Complete List - Trustmary: https://trustmary.com/ai-visibility/best-ai-search-visibility-tools/
  • How to Do Competitor Benchmarking for AEO (With Concrete Examples) | Windgrove AI: https://windgrove.ai/blog/aeo-competitor-benchmarking
  • Best AI Reputation & Visibility Tools (2026), Reviewed | Stork.AI: https://www.stork.ai/blog/best-ai-reputation-tools-2026
  • AI Search Monitoring Tools 2026: The Best Platforms to Track Mentions, Citations, and Visibility: https://www.useomnia.com/blog/ai-search-monitoring-tools
  • Additional AI research evidence88 records
    1. AI research evidence record openai:c1
    2. AI research evidence record openai:c2
    3. AI research evidence record openai:c3
    4. AI research evidence record openai:c1
    5. AI research evidence record grok:0
    6. AI research evidence record anthropic:21-1
    7. AI research evidence record perplexity:c7
    8. AI research evidence record openai:c1
    9. AI research evidence record openai:c2
    10. AI research evidence record anthropic:11-2
    11. AI research evidence record google:1.2.1
    12. AI research evidence record anthropic:28-2
    13. AI research evidence record openai:c4
    14. AI research evidence record openai:c1
    15. AI research evidence record perplexity:c2
    16. AI research evidence record kimi:monitoraeo-audit-1
    17. AI research evidence record google:1.1.1
    18. AI research evidence record grok:0
    19. AI research evidence record google:1.2.1
    20. AI research evidence record anthropic:28-5
    21. AI research evidence record perplexity:c1
    22. AI research evidence record openai:c1
    23. AI research evidence record grok:0
    24. AI research evidence record kimi:monitoraeo-audit-1
    25. AI research evidence record google:1.2.1
    26. AI research evidence record anthropic:45-1
    27. AI research evidence record anthropic:45-3
    28. AI research evidence record perplexity:c2
    29. AI research evidence record perplexity:c4
    30. AI research evidence record perplexity:c7
    31. AI research evidence record anthropic:7-2
    32. AI research evidence record openai:c4
    33. AI research evidence record deepseek:c1
    34. AI research evidence record openai:c2
    35. AI research evidence record perplexity:c1
    36. AI research evidence record anthropic:11-2
    37. AI research evidence record google:1.1.8
    38. AI research evidence record openai:c1
    39. AI research evidence record anthropic:7-8
    40. AI research evidence record openai:c2
    41. AI research evidence record perplexity:c2
    42. AI research evidence record kimi:monitoraeo-audit-1
    43. AI research evidence record anthropic:45-1
    44. AI research evidence record perplexity:c4
    45. AI research evidence record google:1.4.6
    46. AI research evidence record anthropic:7-5
    47. AI research evidence record openai:c3
    48. AI research evidence record anthropic:28-5
    49. AI research evidence record openai:c2
    50. AI research evidence record openai:c4
    51. AI research evidence record anthropic:11-2
    52. AI research evidence record openai:c3
    53. AI research evidence record perplexity:c8
    54. AI research evidence record deepseek:c1
    55. AI research evidence record kimi:monitoraeo-audit-1
    56. AI research evidence record openai:c1
    57. AI research evidence record anthropic:28-2
    58. AI research evidence record google:1.4.6
    59. AI research evidence record kimi:monitoraeo-audit-1
    60. AI research evidence record openai:c2
    61. AI research evidence record perplexity:c2
    62. AI research evidence record grok:0
    63. AI research evidence record openai:c1
    64. AI research evidence record openai:c2
    65. AI research evidence record openai:c3
    66. AI research evidence record anthropic:1-13
    67. AI research evidence record anthropic:7-2
    68. AI research evidence record kimi:monitoraeo-audit-1
    69. AI research evidence record perplexity:c2
    70. AI research evidence record perplexity:c4
    71. AI research evidence record anthropic:45-1
    72. AI research evidence record openai:c1
    73. AI research evidence record anthropic:21-1
    74. AI research evidence record kimi:monitoraeo-audit-1
    75. AI research evidence record openai:c4
    76. AI research evidence record openai:c1
    77. AI research evidence record anthropic:7-2
    78. AI research evidence record kimi:monitoraeo-audit-1
    79. AI research evidence record openai:c1
    80. AI research evidence record openai:c2
    81. AI research evidence record grok:0
    82. AI research evidence record perplexity:c2
    83. AI research evidence record kimi:monitoraeo-audit-1
    84. AI research evidence record google:1.1.1
    85. AI research evidence record anthropic:45-1
    86. AI research evidence record perplexity:c4
    87. AI research evidence record anthropic:7-2
    88. AI research evidence record openai:c3

Verify this research

Review the study details behind this page or download the public machine-readable verification record.

Study date
September 18, 2026
Platforms analyzed
7
Source records
10
Ranking mentions
2 of 7
Platform share
29%
Final consensus rank
#5

Research trail and source mix

Configured platforms

openai, anthropic, deepseek, grok, perplexity, kimi, google

Source mix

4 independent · 6 company-owned

Evidence support

8 direct · 2 partial

Important limitation

Use the run research_date as the study date. Platform-reported dates are provenance metadata and do not independently prove freshness.

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