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Scrunch AI AI Citation Solution Fit Review for Competitive Citation Analysis

Scrunch AI is a good fit for competitive citation analysis, with four of six platforms naming it in the ranking stage and rating it "good." The strongest reason to consider it is direct cited-domain and URL visibility: Scrunch reports which sources AI models cite, separates…

Research: 2026-09-176 usable platform responsesRead the methodology ↗

Answer Capsule

Scrunch AI is a good fit for competitive citation analysis, with four of six platforms naming it in the ranking stage and rating it "good." The strongest reason to consider it is direct cited-domain and URL visibility: Scrunch reports which sources AI models cite, separates branded, competitor, and third-party citations, and prioritizes sources with an Influence Score [1]. The main limitation is that the lowest-cost Core plan covers only four AI platforms with capped prompts and competitors, while expanded coverage, APIs, and the Agent Experience Platform require custom-priced Enterprise [4]. Independent validation of citation accuracy was not established in the reviewed sources.

Research Snapshot

FieldValue
Platform mentions in ranking stage4 of 6 platforms (anthropic, grok, openai, perplexity)
Share of included platform responses66.7%
Average listed rank4.75
Best listed rank2 (perplexity)
Relevant product/model/planScrunch Core platform; Scrunch AI citation monitoring and competitive analysis platform; Enterprise platform with expanded model coverage, APIs, and Agent Experience Platform
Overall use-case fitGood (4 platforms); Mixed (1 platform); Uncertain (1 platform) — 6 platforms analyzed
Research date2026-09-17

Why Scrunch AI Qualified for This Study

Questions This Section Answers

  • Is Scrunch AI a good choice for AI Citation Solutions for Competitive Citation Analysis?
  • How many AI platforms named Scrunch AI during the ranking stage for competitive citation analysis?

Scrunch AI qualified because four of the six included platforms named it during ranking discovery, and all four rated it a good fit for competitive citation analysis [7]. Its average listed rank was 4.75, with a best rank of 2 from perplexity.

The qualification rests on documented capability rather than brand recognition. Scrunch's own help and product pages describe a Citations feature that identifies which sources AI models cite, including branded, competitive, and third-party sources [8]. Independent reviewers describe the same workflow: switching the Citation Owner filter from Third-Party to Competitor to see exactly which URLs drive citations for competitors [11].

Two platforms diverged. DeepSeek rated the fit "mixed" and reported that its research could not verify the specific competitive citation-comparison workflow, pricing, or independent performance evidence [13]. Kimi rated the fit "uncertain," stating that no independent source in its results confirmed Scrunch AI's existence, feature set, or pricing, and that the domain was recovered by search but remained unverified in content [15]. These are platform-reported positions, not verified findings, and they conflict with the four platforms that retrieved Scrunch-owned documentation directly.

This review sits inside a broader comparison of AI Citation Solutions for Competitive Citation Analysis, where Scrunch is one of several evaluated providers.

The Product, Model, Plan, or Service Most Relevant to AI Citation Solutions for Competitive Citation Analysis

Questions This Section Answers

  • Which Scrunch AI plan should a buyer choose for competitive citation analysis across more than four AI platforms?
  • Does Scrunch AI's Core plan include competitor citation tracking and source filtering for competitive analysis?

The most relevant offering is the Scrunch AI citation monitoring and competitive analysis platform, sold as a Core plan at $250 per month and an Enterprise plan at custom pricing [17]. Core is the entry point for competitive citation work; Enterprise is the tier that unlocks the coverage most competitive programs eventually need.

Core publicly lists four AI platforms — ChatGPT, Perplexity, Google AI Overviews, and Microsoft Copilot — with 125 unique prompts, five competitors, three topics, one country, one brand workspace, five user licenses, and five site audits per month [17]. Enterprise publicly lists nine platforms, adding Claude, Gemini, Meta AI, Google AI Mode, and Grok, plus custom prompt volume, full site audits, API and integrations, Looker Studio, SSO, and a dedicated team [21].

Platforms described the relevant product differently. OpenAI named the Core platform, the citation monitoring and competitive analysis platform, and the Enterprise platform with expanded model coverage, APIs, and AXP. Anthropic named the Citation Trend Analysis Platform and the Core plan at $250 per month brand and $500 per month agency. Perplexity described self-serve Starter/Growth plans plus Enterprise. These naming differences reflect packaging changes over time and should be confirmed with the vendor rather than resolved by assumption.

What the AI Platforms Agreed About

Questions This Section Answers

  • What do AI platforms agree Scrunch AI does well for competitive citation analysis?
  • Does Scrunch AI show which URLs and domains competitors are cited for in AI answers?

The clearest agreement is that Scrunch exposes cited domains and URLs and supports competitor-specific citation analysis. Four platforms — openai, anthropic, grok, and perplexity — independently described citation tracking that identifies which sources AI models cite, with competitor benchmarking layered on top [23].

Platforms also agreed on the mechanics of the citation workflow. Scrunch reports citations as source URLs and allows filtering by AI platform, citation owner, topic, persona, funnel stage, country, and branded versus non-branded prompts [27]. Independent reviewers confirm the Citation Owner filter can be flipped from Third-Party to Competitor to isolate competitor-driving URLs [29].

A third area of agreement is source prioritization. Scrunch's Influence Score multiplies the percentage of AI responses citing a source by the number of unique prompts, and is intended to rank influential sources [31]. Independent directory coverage describes the same metric as quantifying how broadly and consistently individual sources influence tracked AI responses [33].

Platforms also agreed on pricing structure: a publicly listed Core plan at $250 per month and custom-priced Enterprise, with a 7-day trial [34]. Agreement among AI platforms reflects overlapping retrieved documentation, not independent proof of product quality.

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Is Scrunch AI's citation data independently validated for accuracy and completeness?
  • Does Scrunch AI capture real-time RAG retrieval results or convert keyword data into synthetic prompts?

The sharpest disagreement is about verification. Four platforms rated Scrunch a good fit; deepseek rated it mixed and kimi rated it uncertain. Kimi stated that no independent source confirmed Scrunch AI's existence, features, or pricing, and that the domain was recovered by search but unverified in content [38]. DeepSeek reported that no retrieved source documented competitor-side citation comparison, source-overlap measurement, or authority-gap discovery [40]. Both positions are platform-reported and conflict with the Scrunch-owned documentation other platforms retrieved.

Independent validation of citation accuracy was not established in the reviewed sources. OpenAI stated explicitly that independent evidence confirming citation completeness, accuracy, or competitive performance was not established, and that a recent independent technology publication reported Core pricing and basic platform coverage without validating citation completeness or accuracy [42].

Real-time retrieval is unresolved. An independent review reported that Scrunch "converts keyword data to prompts" rather than tracking actual user prompts, which the reviewer suggested may not always reflect real-world AI search behavior [43]. No official Scrunch statement confirms or denies real-time RAG capture, so buyers should ask directly.

Data freshness is a documented constraint rather than a disagreement. Scrunch refreshes data every three days as standard, with prompts newer than 14 days updating daily, and offers instant collection for time-sensitive monitoring [44]. An independent comparison states Peec AI offers daily refresh standard on all plans [45].

Several capabilities are described inconsistently across sources. A dedicated source-overlap matrix, formal authority-gap scoring, and citation-architecture visualization were not clearly documented publicly [46]. API data retention is reported at 90 days by independent reviewers, with no recent official documentation confirming or refuting the limit [49]. AXP launched as a pilot in mid-2025 and remained in limited availability as of early 2026, gated to Enterprise [50].

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • Does Scrunch AI identify missing authority sources where competitors are cited but the buyer's brand is not?
  • Can Scrunch AI segment competitor citation data by persona, topic, and funnel stage?

Scrunch's competitive citation capabilities center on four documented functions: cited-source identification, competitor citation filtering, trend tracking, and source prioritization.

Cited-source identification is the foundation. Scrunch reports citations as URLs or pages cited by AI assistants, and the Citations tab supports filtering by platform, owner, topic, persona, funnel stage, and country [51]. Independent coverage describes a Top Domains Cited panel showing the most-cited sources for tracked prompts [53].

Competitor citation architecture is supported through Citation Owner filters. Scrunch reports competitor visibility, the webpages most influential in AI responses, citation frequency and distribution, and changes over time [54]. Independent reviewers describe flipping the Citation Owner filter to Competitor to see exactly which URLs drive citations for competitors [56].

Gap detection converts citation data into content briefs. An independent review describes a Content Gaps feature that auto-detects missing content for tracked prompts where competitors are cited but the buyer is not [58]. Citation trend analysis tracks rising, declining, and emerging citations, which the reviewer says enables teams to detect citation gains or losses before they appear in aggregate metrics [59].

Crawler analytics connect citation inputs to AI behavior. Scrunch integrates with GA4 and Cloudflare to track AI crawler visits categorized as Citations, Training, and Indexing [60]. An independent review describes the named crawler and agent-traffic analytics paired with a GA4 view of AI referral traffic as among the best in the category for teams that think in logs and crawl budgets [61].

Data export is available via CSV and API, and Enterprise APIs can return full AI answers, citations, competitors, sentiment, and metadata [62]. Scrunch states that general-purpose AI content generation is not currently offered, so the platform monitors and prioritizes rather than produces remediation content [64].

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does Scrunch AI cost per month, and are there setup or cancellation fees?
  • What happens at the end of the Scrunch AI 7-day free trial if the buyer does not cancel?

Publicly listed pricing is $250 per month for Core and custom pricing for Enterprise [65]. Core includes 125 unique prompts, five site audits per month, one brand workspace, five user licenses, three topics, five competitors, and four AI platforms [65].

Pricing reports conflict across sources. Perplexity reported Core/Starter at $250 per month billed annually or $300 month-to-month, Growth at $417 per month billed annually or $500 month-to-month, and Agency Core at $500 per month [69]. Anthropic reported Agency Core at $500 per month and additional seats at $25 per user per month, or five seats for $75 per month [71]. Geotoolbox confirmed Core at $250 as of August 2026 and noted a prior Starter/Growth ladder that has since been retired [68]. Buyers should verify current pricing directly.

Trial terms carry an automatic upgrade. The free trial is seven days and may automatically upgrade unless canceled, with data remaining accessible through the current billing cycle after cancellation [72]. Independent sources conflict on trial availability: one April 2026 review stated no free trial was available, while Capterra and Scrunch's own FAQ confirm a 7-day trial with no credit card required [73].

Additional costs exist outside the plan. External Cloudflare Workers usage may create costs outside the Scrunch plan for Agent Traffic integrations [74]. API usage is billed by the number of AI responses collected rather than API-call count [75]. Enterprise API, expanded coverage, AXP, additional workspaces, prompts, users, and support pricing is not publicly itemized [65].

Contract terms are largely unpublished. Public materials reviewed did not establish minimum enterprise contract length, renewal terms, refund policy, prompt overage fees, or exact cancellation notice requirements [65]. Independent sources report that annual agreements paid upfront receive the equivalent of two months free [77].

Best Suited For

Questions This Section Answers

  • Who gets the most value from Scrunch AI for competitive citation analysis?
  • Is Scrunch AI a good fit for agencies managing competitive citation analysis across multiple brands?

Scrunch is best suited to companies that need prompt-level and URL-level visibility into which sources support competitors across major AI answer platforms [78]. Teams that want competitor benchmarking, citation trend monitoring, source prioritization, and broader AI-search optimization in one platform fit the documented feature set [80].

Agencies are a documented segment. Anthropic lists enterprises and agencies needing citation-level competitive benchmarking across four to nine AI platforms as a best-fit group, and notes multi-brand operations requiring separate workspaces for competitive brand comparison [82]. Perplexity lists competitive intelligence teams that can validate whether the platform's trends and observability outputs support source-level citation analysis [84].

Enterprise buyers willing to purchase custom coverage, integrations, and Agent Experience Platform capabilities are the strongest fit for the top tier [86]. Organizations with GA4 integration requirements for AI referral attribution and crawler analytics also align with documented capabilities [87].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose Scrunch AI for competitive citation analysis?
  • Is Scrunch AI a poor fit for buyers who need built-in AI content generation?

Buyers needing transparent, unlimited, or highly customized cross-platform citation datasets at a low fixed price are not well served, because Core caps platforms, prompts, competitors, topics, countries, and workspaces [89]. Teams requiring built-in general-purpose AI content generation should look elsewhere; Scrunch states this is not currently offered [91].

Buyers whose priority is independent validation of citation quality rather than vendor-defined visibility and Influence Score metrics are also a weaker fit, since independent validation was not established in the reviewed sources [92]. Teams requiring real-time or daily data refresh should note that Core refreshes every three days, while an independent comparison states Peec AI offers daily refresh standard [94].

Organizations requiring historical data beyond 90 days via API export face a documented retention limit reported by independent reviewers [96]. Buyers seeking proprietary AI search demand or prompt-volume data will not find it here; an independent review states Scrunch does not share prompt volume data and its prompt trend feature is too basic to be actionable [93].

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to Scrunch AI for a buyer who needs daily citation refresh under $250 per month?
  • Which alternative to Scrunch AI is better for URL-level competitor source overlap analysis?

Lower-cost specialists may be better when budget is the binding constraint. Independent sources describe Gauge at roughly $99 per month, Peec AI at roughly €85 per month, and LLM Pulse as lower entry-cost options [98]. Web Cited publishes $49 to $99 per month with competitor landscape rankings and per-prompt citation share [99]. Cited publishes tiers from $79 to $499 per month with competitor tracking, share of voice, and gap analysis [101].

URL-level source overlap may favor a different tool. Vercite tracks exact cited URLs, competitor source overlap, citation gaps, and covers five AI engines [103]. CiteMetrix offers competition tracking with share of voice, though it requires a Professional plan upgrade [104]. Viali captures actual URLs and classifies sources by type [105].

Content execution is a different category. Buyers needing integrated content workflows alongside citation analysis are directed by one platform toward AirOps, Scalenut, or Conductor, which embed content workflows, optimization, and publishing. Enterprise-scale prompt volume may favor Evertune, described as serving Fortune 500 with 11 AI engines and a 25M US consumer panel. Proprietary AI search demand intelligence may favor Profound, described as providing 400M+ anonymized conversations and daily data refresh [106].

Questions to Verify Before Buying

Questions This Section Answers

  • What should a buyer confirm with Scrunch AI before signing a contract for competitive citation analysis?
  • Does Scrunch AI export raw prompt, answer, citation URL, and cited-domain data?

Confirm that the contracted product compares cited domains and exact URLs across all required platforms, including Claude, Gemini, Google AI Mode, Meta AI, and Grok [107]. Ask whether model versions, locations, languages, personalization settings, and retrieval modes are disclosed and held consistent across measurements [109].

Verify whether the platform captures real-time RAG retrieval results with live citations or converts keyword data into synthetic prompts, and how that affects competitive citation accuracy [110]. Ask whether a native source-overlap matrix exists showing sources shared by competitors and sources missing from the buyer's citation profile [109].

Request the exact API data retention policy and whether historical citations are available beyond 90 days via direct query or only manual CSV export [112]. Ask how Influence Score is defined and updated, and whether buyers can access the underlying denominator and prompt-level calculations [114].

Clarify enterprise minimum term, renewal, cancellation, overage, API-response, user, workspace, and historical-retention terms, since public materials did not establish these [116]. Confirm whether AXP and content-delivery features are included in the quoted plan and what technical changes, implementation work, or hosting costs are required [118]. Ask what happens when a cited page is blocked, JavaScript-rendered, removed, redirected, or unavailable [120].

Finally, confirm whether the buyer can run a representative trial using its own competitors, prompts, countries, and required AI platforms before signing [121].

Final AI Consensus Verdict

Scrunch AI is a good fit for competitive citation analysis, with four of six platforms rating it good and two rating it mixed or uncertain. The consensus rests on documented cited-domain and URL visibility, competitor citation filtering, trend tracking, and Influence Score prioritization [123]. The strongest limitation is that Core covers only four AI platforms with capped prompts and competitors, while expanded coverage, APIs, and AXP require custom-priced Enterprise [126].

Treat Scrunch as a vendor-reported analytics platform rather than independently validated citation intelligence. Independent validation of citation completeness, accuracy, or competitive outcomes was not established in the reviewed sources [129]. Buyers should verify real-time RAG capture, source-overlap reporting, API retention, and enterprise contract terms before committing.

How This Review Was Produced

This review synthesizes fit-research responses from six AI platforms — anthropic, deepseek, grok, kimi, openai, and perplexity — each evaluating Scrunch AI against the same competitive citation analysis use case. Four platforms named Scrunch AI during ranking discovery; all six produced fit assessments. Platform-reported research dates differ: deepseek reported 2026-02-14, while the other five reported 2026-09-17. The authoritative study date is 2026-09-17.

Citations are platform-reported evidence, not independently verified facts. Company-owned sources are labeled as such; independent sources include reviews, directories, and journalism. Where platforms disagreed, both positions are preserved. No personal testing, customer experience, or independent verification was performed.

Methodology Limitations

The supplied URLs were collected from platform responses and were not independently validated. Platform-reported research dates differ from the authoritative run date, so some platform findings may be stale. The deterministic identity audit noted conflicting official domains, an official-site retrieval failure for at least one mention, and an exact-name fallback that left the matching domain unverified. The supplied identity uses scrunch.ai, while retrieved pricing, product, and help materials primarily use scrunch.com and scrunchai.com/helpcenter; the relationship among these domains should be verified.

Public platform pages and help materials report different platform-count presentations depending on plan and page. Public materials describe source prioritization and gap detection but do not clearly establish a dedicated source-overlap metric, citation-architecture map, or authority-source score. Independent evidence confirming citation completeness, accuracy, or competitive performance was not established. Any future-facing or 2026 product claims should be rechecked at purchase because coverage, pricing, and product packaging may change. Kimi's research reported no independent confirmation of Scrunch AI's existence, which conflicts with the Scrunch-owned documentation other platforms retrieved; this conflict is preserved rather than resolved.

Explore more ai citation authority building guidance in the category directory.

Sources

Company-Owned Sources

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  • Scrunch | The AI Customer Experience Platform | AI search: https://scrunch.com/
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    9. AI research evidence record grok:1
    10. AI research evidence record perplexity:c1
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    12. AI research evidence record anthropic:20-2
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    69. AI research evidence record perplexity:c2
    70. AI research evidence record perplexity:c15
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    72. AI research evidence record openai:c14
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    74. AI research evidence record openai:c15
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    80. AI research evidence record openai:c3
    81. AI research evidence record anthropic:26-11
    82. AI research evidence record anthropic:14-3
    83. AI research evidence record anthropic:14-4
    84. AI research evidence record perplexity:c1
    85. AI research evidence record perplexity:c9
    86. AI research evidence record openai:c8
    87. AI research evidence record anthropic:26-2
    88. AI research evidence record anthropic:18-4
    89. AI research evidence record openai:c7
    90. AI research evidence record anthropic:14-3
    91. AI research evidence record openai:c12
    92. AI research evidence record openai:c11
    93. AI research evidence record anthropic:4-1
    94. AI research evidence record anthropic:7-7
    95. AI research evidence record anthropic:30-6
    96. AI research evidence record anthropic:35-7
    97. AI research evidence record anthropic:37-11
    98. AI research evidence record anthropic:30-6
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    116. AI research evidence record openai:c7
    117. AI research evidence record anthropic:12-1
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    119. AI research evidence record anthropic:8-9
    120. AI research evidence record openai:c13
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Independent Sources

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  • Additional AI research evidence130 records
    1. AI research evidence record openai:c1
    2. AI research evidence record anthropic:1-1
    3. AI research evidence record anthropic:5-14
    4. AI research evidence record openai:c7
    5. AI research evidence record anthropic:14-3
    6. AI research evidence record anthropic:14-4
    7. AI research evidence record openai:c1
    8. AI research evidence record anthropic:1-1
    9. AI research evidence record grok:1
    10. AI research evidence record perplexity:c1
    11. AI research evidence record anthropic:20-1
    12. AI research evidence record anthropic:20-2
    13. AI research evidence record deepseek:c1
    14. AI research evidence record deepseek:c2
    15. AI research evidence record kimi:web-cited-2024
    16. AI research evidence record kimi:getcited-in-2024
    17. AI research evidence record openai:c7
    18. AI research evidence record anthropic:12-1
    19. AI research evidence record perplexity:c5
    20. AI research evidence record anthropic:14-3
    21. AI research evidence record openai:c8
    22. AI research evidence record anthropic:14-4
    23. AI research evidence record openai:c1
    24. AI research evidence record anthropic:1-1
    25. AI research evidence record grok:1
    26. AI research evidence record perplexity:c1
    27. AI research evidence record openai:c2
    28. AI research evidence record anthropic:5-9
    29. AI research evidence record anthropic:20-1
    30. AI research evidence record anthropic:20-2
    31. AI research evidence record openai:c5
    32. AI research evidence record anthropic:5-14
    33. AI research evidence record anthropic:27-2
    34. AI research evidence record openai:c7
    35. AI research evidence record anthropic:12-1
    36. AI research evidence record perplexity:c2
    37. AI research evidence record openai:c14
    38. AI research evidence record kimi:web-cited-2024
    39. AI research evidence record kimi:getcited-in-2024
    40. AI research evidence record deepseek:c1
    41. AI research evidence record deepseek:c2
    42. AI research evidence record openai:c11
    43. AI research evidence record anthropic:7-9
    44. AI research evidence record anthropic:7-7
    45. AI research evidence record anthropic:30-6
    46. AI research evidence record openai:c2
    47. AI research evidence record openai:c4
    48. AI research evidence record openai:c5
    49. AI research evidence record anthropic:35-7
    50. AI research evidence record anthropic:8-9
    51. AI research evidence record openai:c1
    52. AI research evidence record openai:c2
    53. AI research evidence record anthropic:2-1
    54. AI research evidence record openai:c3
    55. AI research evidence record openai:c4
    56. AI research evidence record anthropic:20-1
    57. AI research evidence record anthropic:20-2
    58. AI research evidence record anthropic:26-4
    59. AI research evidence record anthropic:26-11
    60. AI research evidence record anthropic:26-2
    61. AI research evidence record anthropic:18-4
    62. AI research evidence record anthropic:1-5
    63. AI research evidence record openai:c9
    64. AI research evidence record openai:c12
    65. AI research evidence record openai:c7
    66. AI research evidence record anthropic:12-1
    67. AI research evidence record perplexity:c5
    68. AI research evidence record anthropic:14-3
    69. AI research evidence record perplexity:c2
    70. AI research evidence record perplexity:c15
    71. AI research evidence record anthropic:10-2
    72. AI research evidence record openai:c14
    73. AI research evidence record anthropic:10-1
    74. AI research evidence record openai:c15
    75. AI research evidence record openai:c9
    76. AI research evidence record openai:c8
    77. AI research evidence record anthropic:14-4
    78. AI research evidence record openai:c1
    79. AI research evidence record anthropic:1-1
    80. AI research evidence record openai:c3
    81. AI research evidence record anthropic:26-11
    82. AI research evidence record anthropic:14-3
    83. AI research evidence record anthropic:14-4
    84. AI research evidence record perplexity:c1
    85. AI research evidence record perplexity:c9
    86. AI research evidence record openai:c8
    87. AI research evidence record anthropic:26-2
    88. AI research evidence record anthropic:18-4
    89. AI research evidence record openai:c7
    90. AI research evidence record anthropic:14-3
    91. AI research evidence record openai:c12
    92. AI research evidence record openai:c11
    93. AI research evidence record anthropic:4-1
    94. AI research evidence record anthropic:7-7
    95. AI research evidence record anthropic:30-6
    96. AI research evidence record anthropic:35-7
    97. AI research evidence record anthropic:37-11
    98. AI research evidence record anthropic:30-6
    99. AI research evidence record kimi:web-cited-2024
    100. AI research evidence record kimi:web-cited-monitor-2024
    101. AI research evidence record kimi:getcited-in-2024
    102. AI research evidence record kimi:getcited-pricing-2024
    103. AI research evidence record kimi:vercite-2024
    104. AI research evidence record kimi:citemetrix-2024
    105. AI research evidence record kimi:viali-2024
    106. AI research evidence record anthropic:35-24
    107. AI research evidence record openai:c8
    108. AI research evidence record anthropic:14-4
    109. AI research evidence record openai:c2
    110. AI research evidence record anthropic:7-9
    111. AI research evidence record openai:c4
    112. AI research evidence record anthropic:35-7
    113. AI research evidence record anthropic:1-5
    114. AI research evidence record openai:c5
    115. AI research evidence record anthropic:5-14
    116. AI research evidence record openai:c7
    117. AI research evidence record anthropic:12-1
    118. AI research evidence record openai:c15
    119. AI research evidence record anthropic:8-9
    120. AI research evidence record openai:c13
    121. AI research evidence record openai:c14
    122. AI research evidence record anthropic:14-3
    123. AI research evidence record openai:c1
    124. AI research evidence record anthropic:1-1
    125. AI research evidence record anthropic:5-14
    126. AI research evidence record openai:c7
    127. AI research evidence record anthropic:14-3
    128. AI research evidence record anthropic:14-4
    129. AI research evidence record openai:c11
    130. AI research evidence record anthropic:4-1

Verify this research

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

Study date
September 17, 2026
Platforms analyzed
6
Source records
45
Ranking mentions
4 of 6
Platform share
67%
Final consensus rank
#5

Research trail and source mix

Configured platforms

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

Source mix

27 independent · 18 company-owned

Evidence support

35 direct · 9 partial

Important limitation

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

Source snapshot SHA-256 0ae39d1af490d55dddce3171e010309abd67e5a35c0441774ce329b7e67ab35a