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Profound AI Visibility Platform Fit Review for Citation Tracking

Profound is a good fit for enterprise buyers that need citation-frequency tracking, source-level analysis, competitor citation benchmarking, and prompt-linked AI answer monitoring across multiple answer engines.

Research: 2026-09-197 usable platform responsesRead the methodology ↗

Answer Capsule

Profound is a good fit for enterprise buyers that need citation-frequency tracking, source-level analysis, competitor citation benchmarking, and prompt-linked AI answer monitoring across multiple answer engines. Six of the seven platforms in this study named Profound during ranking discovery, and it finished first overall with an average listed rank of 1.17. Its strongest advantage is prompt-driven citation tracking that connects tracked questions to generated answers and cited sources, backed by daily tracking and enterprise controls. The main limitation is commercial and methodological opacity: multi-engine coverage is gated behind higher tiers, enterprise pricing is quote-only, and public materials do not fully document sampling design, citation-attribution logic, or audited precision/recall.

Research Snapshot

FieldDetail
Platform mentions in ranking stage6 of 7 platforms
Share of included platform responses85.7%
Average listed rank1.17
Best listed rank1
Relevant product/model/planProfound Answer Engine Insights on the Enterprise plan / custom enterprise package; Growth or Enterprise tier for multi-engine citation tracking
Overall use-case fitGood for enterprise citation tracking; mixed-to-uncertain on pricing transparency and independent validation
Research date2026-09-19

Why Profound Qualified for This Study

Questions This Section Answers

  • Is Profound a good choice for AI Visibility Platforms for Citation Tracking?
  • How many AI platforms named Profound in this citation-tracking study?

Profound qualified because it was named by six of the seven platforms in the ranking stage — anthropic, deepseek, google, grok, openai, and perplexity — and finished first overall with an average listed rank of 1.17 and a best rank of 1 [1]. Only kimi did not name Profound during ranking discovery, and kimi's response explicitly stated that no independent source in its retrieved results verified Profound's capabilities, pricing, or identity [4].

The platforms converged on Profound because its documented feature set maps directly to the study's criteria: citation-frequency tracking, source-level analysis, platform comparisons, competitor citation benchmarking, historical trends, and prompt-to-answer-to-citation linkage [1]. Profound's own documentation defines a citation as a webpage, article, or resource referenced in an answer-engine response, and organizes tracked prompts into topics and tags that run daily on configured plans [5].

Qualification is not the same as verified quality. Every platform that named Profound relied heavily on company-owned pages hosted on tryprofound.com, plus independent review sites of varying rigor. The deterministic identity audit for this run flagged an unresolved domain conflict: profound.com was retained as the official website by multi-provider consensus, but the current product documentation lives on tryprofound.com, and the supplied profound.com URL resolved to an unrelated market research provider's page [9]. Buyers should treat the domain relationship as an open verification item, not a settled fact.

The Product, Model, Plan, or Service Most Relevant to AI Visibility Platforms for Citation Tracking

Questions This Section Answers

  • Which Profound plan should a buyer choose if they need multi-engine citation tracking?
  • Does Profound's Growth plan include Claude and Gemini citation tracking, or is Enterprise required?

The relevant product is Profound Answer Engine Insights, delivered on the Growth or Enterprise tier depending on how many engines the buyer needs [10]. Answer Engine Insights queries answer engines, captures responses into a prompt-driven dataset, and tracks brand presence, citations, sentiment, share of voice, and average position [13].

Plan boundaries matter for this use case. Independent pricing reviews report that the Starter plan at $99/month covers ChatGPT only with 50 prompts and one seat; the Growth plan at $399/month expands to three engines — ChatGPT, Perplexity, and Google AI Overviews — with 100 prompts and three seats; and the Enterprise plan is custom-priced and unlocks up to nine or ten engines depending on the source, plus API access, unlimited exports, SSO, and a dedicated strategist [14]. Multiple independent sources state that Claude and Gemini coverage requires the custom-priced Enterprise tier [19].

Profound's own pricing page lists tailored prompt tracking, daily frequency, multi-engine capability, CSV/JSON exports, API access, SSO, and dedicated support for the enterprise package, but publishes no numeric subscription price [20]. The platform also includes Conversation Explorer, described in independent reviews as revealing how often topics are discussed across AI platforms — the closest thing to search volume for conversational queries [22].

What the AI Platforms Agreed About

Questions This Section Answers

  • What citation-tracking features do AI platforms agree Profound provides?
  • Is Profound's citation tracking strong enough for enterprise competitor benchmarking?

The platforms agreed strongly on four capabilities. First, citation-frequency tracking: Profound runs tracked prompts daily and processes large citation volumes, with company-reported figures of 5M+ citations and 10M+ prompts analyzed daily [24]. Second, source-level analysis: every cited source is classified as Owned, Competitor, Earned Media, PR Wire, Social, or Institution, with drill-down by platform, topic, or prompt [26]. Third, competitor citation benchmarking: Citation Rank lists and share-of-voice comparisons by platform, topic, and prompt let buyers see where competitors earn citations and the tracked brand does not [28]. Fourth, prompt-linked monitoring: the platform records which prompts surface a brand or competitor and where content is pulled from or missed [30].

Agreement was also strong on methodology positioning. Profound states it captures responses directly from the browser rather than pulling from APIs, arguing that what appears in Profound matches what customers see when they query AI [31]. Independent reviews repeat this browser-level capture claim and note that ChatGPT's API and web interface share only about 4% overlap in sourced citations, which is the stated rationale for frontend tracking [32]. This is a platform-reported and review-reported claim, not an independently audited benchmark.

The platforms further agreed that Profound is enterprise-oriented, with SOC 2 Type II compliance, SSO/SAML, role-based access control, daily backups, API access, and integrations with common infrastructure and analytics platforms [34]. These are company claims that should be validated through security documentation and contract terms.

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Why do AI platforms disagree about Profound's fit rating for citation tracking?
  • Is Profound's citation-attribution accuracy independently verified?

Fit ratings diverged sharply. Google and grok rated Profound a strong fit; openai and anthropic rated it good; deepseek and perplexity rated it mixed; and kimi rated it uncertain [35]. The disagreement tracks how much weight each platform gave to public documentation versus pricing and methodology transparency.

Three specific uncertainties recur. First, measurement transparency: an independent Aiso review reports that Profound does not publicly document its prompt-sampling design, refresh cadence, citation-attribution logic, or audited precision/recall benchmarks, and recommends requesting methodology documentation before relying on point estimates for executive or client reporting [35]. Second, citation accuracy limits: one independent review states Profound is highly accurate at identifying website citations when AI platforms provide explicit links or referenced domains, but accuracy becomes limited with general brand mentions, and notes that 60%+ of AI-generated answers fail to cite sources correctly [42]. Third, engine-count conflicts: sources describe nine engines, ten engines, or "up to 10+" depending on the review, and the exact current coverage should be confirmed contractually [43].

Pricing conflicts are material. Independent sources report Starter at $99/month and Growth at $399/month with annual-only billing, while one review references a $499/month figure and grok's research cites enterprise estimates ranging from $2,000 to $8,000 per month [45]. Profound's own pricing page publishes no numeric enterprise price [43]. Contract length, renewal, cancellation, retention, overage, and price-escalation terms are not publicly disclosed [35].

Identity remains unresolved. The normalization context reports conflicting official domains, retains profound.com by strict multi-provider consensus, and notes the matching domain "remains unverified" [48]. Kimi's research found Profound absent from all eight independent source domains it retrieved, and treated the entity as unverified [41].

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • Does Profound connect citations to the specific prompts and answers where they appear?
  • Can Profound track page-level citations rather than just domain-level mentions?

Profound's citation workflow covers the study's six criteria with varying depth. Citation-frequency tracking is an advantage: tracked prompts run daily, and citation share is reported across answer engines [49]. Source-level analysis is an advantage: sources are categorized and drillable by platform, topic, or prompt, and page-level tracking identifies which specific URLs are cited rather than only domain-level mentions [52]. Competitor benchmarking is an advantage: Citation Rank lists and share-of-voice comparisons by platform, topic, and prompt support direct positioning against competitors [54]. Historical trends are an advantage with a caveat: citation volume changes to individual pages are tracked over time, but gated historical data and API access sit behind Enterprise pricing per G2 reviewers [56].

Prompt-to-answer-to-citation linkage is the most nuanced area. Profound's documentation supports prompt-linked answer and citation analysis, and Conversation Explorer maps prompts and topics to brand mentions and citations [58]. However, one independent review states citation data is aggregated and does not natively preserve sentence-level citation placement within the specific generated answer text for forensic validation [59]. Buyers who need to prove exactly which sentence in an answer triggered a citation should verify export granularity before purchase.

Platform comparisons are constrained by tier. Starter covers ChatGPT only; Growth covers three engines; Enterprise covers the full suite [61]. Agent Analytics requires CDN integration through partners such as Cloudflare or Shopify, so not all hosting platforms are supported [64]. Configuration requires manual prompt curation — prompts the buyer does not define will not be tracked [64].

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does Profound cost per month, and is annual billing required?
  • What enterprise pricing and contract terms should a buyer confirm before signing with Profound?

Published self-serve pricing is $99/month for Starter and $399/month for Growth, both displayed with yearly billing, working out to roughly $1,188 and $4,788 per year [65]. Independent reviews state self-serve plans are billed annually only, with no monthly option and a "billed yearly · 2 months free" framing [68]. Google's research reports annual discounts bringing Starter to $82.50/month and Growth to $332.50/month, plus an Agency Growth plan at $99/month with a $399/month per-client workspace add-on [69].

Enterprise pricing is quote-only. Grok's research cites independent estimates of $2,000–$8,000 per month depending on prompt volume and depth, but these are estimates, not published rates [71]. One review references a $499/month figure, which conflicts with the $399 Growth price and may reflect a different tier or an outdated number [72]. Profound's official pricing page lists no numeric enterprise price [73].

Additional costs and terms are largely undisclosed. No separately published fees were identified for extra engines, regions, prompt volume, API usage, exports, support, or overage [74]. Agent usage is credit-based, with credit consumption depending on agent complexity and additional thresholds requiring an enterprise package [73]. Contract length, renewal, cancellation, refund, data-retention, and service-credit terms are not published; one independent review reports annual contracts are typical, but this is not confirmed by an official disclosure [74]. A 7-day free trial is reported on the Growth tier only [70].

Best Suited For

Questions This Section Answers

  • Who gets the most value from Profound for citation tracking?
  • Is Profound best for enterprise brands or small teams?

Profound is best suited to large companies running recurring AI visibility programs across multiple answer engines, regions, topics, and competitors [75]. Marketing, SEO, communications, or insights teams that need citation, visibility, sentiment, share-of-voice, and prompt-level reporting in one platform are a strong match [75]. Organizations that can support a sales-led enterprise procurement process and validate methodology during due diligence are also well positioned [75].

Independent reviews add specificity: enterprise brands with roughly $10M–$500M revenue requiring daily citation tracking across ChatGPT, Perplexity, Google AI Overviews, and additional engines; teams already resourced with SEO analysts and strategists who can interpret citation data and execute content strategy; and single-brand organizations seeking historical visibility trends and competitive share-of-voice benchmarking [77]. Digital-first businesses where AI visibility has measurable revenue impact are the clearest fit [77].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose Profound for AI Visibility Platforms for Citation Tracking?
  • Is Profound a poor fit for agencies managing multiple client brands?

Profound is probably not best suited to small teams requiring low-cost self-service pricing or a lightweight trial with broad engine coverage [79]. The $99 Starter tier covers ChatGPT only, so buyers who need multi-engine citation tracking face a jump to $399/month or a custom enterprise contract [80].

Agencies are a documented poor fit. One independent review states Profound does not support multi-account management, and another notes a one-workspace limit that blocks agency use and multi-brand management, requiring separate accounts per client with no consolidated reporting [83]. Google's research reports agency pricing scales rapidly per client workspace [85].

Buyers who need publicly documented sampling, attribution, precision/recall, and historical-retention methodology before purchase are also poorly served, as are programs requiring guaranteed coverage of specific models, channels, geographies, or long-tail prompts without contractual confirmation [79]. Teams needing Claude or Gemini coverage without committing to custom Enterprise pricing should look elsewhere or negotiate explicitly [86].

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to Profound for a buyer who needs published pricing under $500 per month?
  • When is a broader SEO suite a better choice than Profound for citation tracking?

Consider Aiso when transparent methodology, reproducibility, real-user prompt coverage, and self-service access matter more than enterprise workflow breadth [88]. Consider a broader SEO suite such as Semrush when the buyer already operates Semrush and wants AI visibility data integrated with existing keyword, backlink, and site-audit workflows [88]. Consider another platform when published pricing, a free trial with broad engine coverage, or independently audited citation accuracy is a procurement requirement [88].

Anthropic's research lists additional alternatives by scenario: Scrunch AI, Peec AI, or Otterly AI for agencies needing multi-client dashboards; LLM Pulse at $49–€99/month for Claude or Gemini coverage at known self-serve pricing; Ahrefs or Semrush for AI visibility alongside keyword rankings and backlink context; rank.ai for sentence-level forensic citation placement; Otterly or Peec at $29–$295/month for lower entry cost; Yext for multi-location AI visibility; and Goodie AI, SE Ranking, or Indexly for lightweight GEO with content execution bundled [89]. Google's research names RadarKit.ai and Maintouch as budget alternatives with multi-engine coverage including Claude and Gemini, and ContentMonk or Surfer AI Tracker for unified organic SEO and AI citation monitoring [91].

Questions to Verify Before Buying

Questions This Section Answers

  • What should a buyer confirm with Profound before signing a contract?
  • Can Profound export joined prompt, answer, citation, and competitor records?

Ask which exact answer engines, model versions, channels, regions, languages, and result types are included in the quoted package [93]. Ask whether the platform can export each prompt, answer, cited URL, citation position, timestamp, engine, model, competitor, and sentiment result as joined records [93]. Ask for the documented prompt-sampling design, refresh cadence, deduplication method, and citation-attribution logic [93]. Ask what precision, recall, false-positive, and false-negative validation data Profound can provide and how it was measured [93].

Confirm how many custom prompts, topics, competitors, domains, users, API calls, exports, and historical months are included [93]. Confirm data-retention, renewal, cancellation, refund, service-level, support, overage, and price-escalation terms [93]. Confirm whether FactCheck is included in the quoted plan and whether it can show the exact source URL responsible for each inaccurate claim [93]. Request current SOC 2 documentation, subprocessors, data-processing terms, and confirmation of the legal relationship between profound.com and tryprofound.com [93].

Additional verification items from other platforms: whether the Growth plan provides actionable multi-engine citation tracking or whether practical depth requires Enterprise; whether brand mentions without explicit citations can be distinguished from cited sources without manual review; whether CDN or hosting infrastructure supports Agent Analytics; the lag between content publication and visible citation changes; and whether annual plans carry contract minimums, auto-renewal, or cancellation fees [95].

Final AI Consensus Verdict

Profound is a good fit for enterprise buyers pursuing AI Visibility Platforms for Citation Tracking, with the caveat that fit quality depends on budget and tolerance for quote-only procurement. Six of seven platforms named it, it ranked first overall, and the platforms agreed strongly on citation-frequency tracking, source-level analysis, competitor benchmarking, and prompt-linked monitoring [98]. The principal purchase risks are quote-only enterprise pricing, unresolved public-domain identity, tier-gated multi-engine coverage, and limited public transparency into sampling and citation-attribution methodology [102]. Buy only after validating required engines, export granularity, methodology, historical retention, and commercial terms.

How This Review Was Produced

This review synthesizes fit-research responses from seven AI platforms — anthropic, deepseek, google, grok, kimi, openai, and perplexity — collected for the research date 2026-09-19. Each platform independently evaluated Profound against the citation-tracking use case, supplied citations, and rated fit. The ranking stage counted only platforms that named Profound during discovery; six of seven did. Fit ratings, feature findings, pricing details, and limitations are reported as the platforms supplied them. Company-owned sources are distinguished from independent sources throughout. No personal testing, customer interviews, or independent verification was performed at the writing stage.

Methodology Limitations

Platform-reported research dates differ from the authoritative run date: deepseek's response is dated 2026-04-10 while the remaining six platforms are dated 2026-09-19 [105]. Platform-reported dates are provenance metadata and do not independently prove freshness.

The supplied URLs were collected from platform responses and were not independently validated at the writing stage. Citations are platform-reported evidence, not independently verified facts. Company-reported scale figures — including 5M+ citations daily, 10M+ prompts daily, 1B+ citations analyzed daily, and 100M+ queries per month — are company claims and are not independently audited in the sources reviewed [106].

The deterministic identity audit flagged an unresolved domain conflict: profound.com was retained as the official website by multi-provider consensus but remains unverified, and the supplied profound.com URL resolved to an unrelated market research provider's page [109]. Kimi's research found no independent verification of Profound's capabilities, pricing, or identity [110]. Pricing conflicts across sources — $99/$399 self-serve versus a $499 reference versus $2,000–$8,000 enterprise estimates — are disclosed rather than resolved [111]. Contract length, renewal, cancellation, retention, overage, and exact pricing terms are not publicly disclosed [113].

Explore more ai visibility llm monitoring guidance in the category directory.

Sources

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  • Additional AI research evidence113 records
    1. AI research evidence record openai:c1
    2. AI research evidence record anthropic:1-1
    3. AI research evidence record google:1.4.9
    4. AI research evidence record kimi:citany-comparison-2026
    5. AI research evidence record openai:c2
    6. AI research evidence record anthropic:3-5
    7. AI research evidence record anthropic:3-8
    8. AI research evidence record anthropic:22-6
    9. AI research evidence record openai:c7
    10. AI research evidence record openai:c1
    11. AI research evidence record anthropic:4-2
    12. AI research evidence record google:1.4.1
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    14. AI research evidence record anthropic:4-3
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    18. AI research evidence record google:1.3.5
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    32. AI research evidence record google:1.3.6
    33. AI research evidence record google:1.4.9
    34. AI research evidence record openai:c5
    35. AI research evidence record openai:c6
    36. AI research evidence record anthropic:4-2
    37. AI research evidence record google:1.4.9
    38. AI research evidence record grok:web:2
    39. AI research evidence record deepseek:c1
    40. AI research evidence record perplexity:c4
    41. AI research evidence record kimi:citany-comparison-2026
    42. AI research evidence record anthropic:34-1
    43. AI research evidence record openai:c4
    44. AI research evidence record anthropic:13-6
    45. AI research evidence record anthropic:13-1
    46. AI research evidence record anthropic:14-4
    47. AI research evidence record perplexity:c12
    48. AI research evidence record openai:c7
    49. AI research evidence record anthropic:1-1
    50. AI research evidence record anthropic:3-8
    51. AI research evidence record anthropic:22-6
    52. AI research evidence record anthropic:3-5
    53. AI research evidence record anthropic:26-1
    54. AI research evidence record anthropic:20-17
    55. AI research evidence record anthropic:21-6
    56. AI research evidence record anthropic:45-6
    57. AI research evidence record anthropic:10-12
    58. AI research evidence record openai:c2
    59. AI research evidence record anthropic:37-3
    60. AI research evidence record anthropic:38-1
    61. AI research evidence record anthropic:4-3
    62. AI research evidence record anthropic:10-11
    63. AI research evidence record anthropic:42-16
    64. AI research evidence record anthropic:4-2
    65. AI research evidence record anthropic:13-1
    66. AI research evidence record anthropic:10-11
    67. AI research evidence record anthropic:10-12
    68. AI research evidence record anthropic:14-4
    69. AI research evidence record google:1.3.5
    70. AI research evidence record google:1.4.1
    71. AI research evidence record grok:web:2
    72. AI research evidence record perplexity:c12
    73. AI research evidence record openai:c4
    74. AI research evidence record openai:c6
    75. AI research evidence record openai:c6
    76. AI research evidence record anthropic:3-5
    77. AI research evidence record anthropic:4-2
    78. AI research evidence record anthropic:45-6
    79. AI research evidence record openai:c6
    80. AI research evidence record anthropic:4-3
    81. AI research evidence record anthropic:10-11
    82. AI research evidence record anthropic:10-12
    83. AI research evidence record anthropic:31-5
    84. AI research evidence record anthropic:4-2
    85. AI research evidence record google:1.3.5
    86. AI research evidence record anthropic:13-6
    87. AI research evidence record anthropic:42-16
    88. AI research evidence record openai:c6
    89. AI research evidence record anthropic:4-2
    90. AI research evidence record anthropic:4-3
    91. AI research evidence record google:1.3.6
    92. AI research evidence record google:1.3.8
    93. AI research evidence record openai:c6
    94. AI research evidence record openai:c7
    95. AI research evidence record anthropic:4-2
    96. AI research evidence record anthropic:34-1
    97. AI research evidence record anthropic:14-4
    98. AI research evidence record openai:c1
    99. AI research evidence record anthropic:3-5
    100. AI research evidence record anthropic:20-17
    101. AI research evidence record anthropic:21-6
    102. AI research evidence record openai:c6
    103. AI research evidence record openai:c7
    104. AI research evidence record anthropic:13-6
    105. AI research evidence record deepseek:c1
    106. AI research evidence record anthropic:1-1
    107. AI research evidence record openai:c4
    108. AI research evidence record grok:web:2
    109. AI research evidence record openai:c7
    110. AI research evidence record kimi:citany-comparison-2026
    111. AI research evidence record anthropic:13-1
    112. AI research evidence record perplexity:c12
    113. AI research evidence record openai:c6

Other Sources

  • Profound official website redirect check: https://profound.com/
  • Additional AI research evidence113 records
    1. AI research evidence record openai:c1
    2. AI research evidence record anthropic:1-1
    3. AI research evidence record google:1.4.9
    4. AI research evidence record kimi:citany-comparison-2026
    5. AI research evidence record openai:c2
    6. AI research evidence record anthropic:3-5
    7. AI research evidence record anthropic:3-8
    8. AI research evidence record anthropic:22-6
    9. AI research evidence record openai:c7
    10. AI research evidence record openai:c1
    11. AI research evidence record anthropic:4-2
    12. AI research evidence record google:1.4.1
    13. AI research evidence record openai:c2
    14. AI research evidence record anthropic:4-3
    15. AI research evidence record anthropic:10-11
    16. AI research evidence record anthropic:10-12
    17. AI research evidence record anthropic:42-16
    18. AI research evidence record google:1.3.5
    19. AI research evidence record anthropic:13-6
    20. AI research evidence record openai:c4
    21. AI research evidence record grok:web:10
    22. AI research evidence record anthropic:39-5
    23. AI research evidence record anthropic:37-3
    24. AI research evidence record anthropic:1-1
    25. AI research evidence record openai:c4
    26. AI research evidence record anthropic:3-5
    27. AI research evidence record anthropic:3-8
    28. AI research evidence record anthropic:20-17
    29. AI research evidence record anthropic:21-6
    30. AI research evidence record openai:c3
    31. AI research evidence record anthropic:22-7
    32. AI research evidence record google:1.3.6
    33. AI research evidence record google:1.4.9
    34. AI research evidence record openai:c5
    35. AI research evidence record openai:c6
    36. AI research evidence record anthropic:4-2
    37. AI research evidence record google:1.4.9
    38. AI research evidence record grok:web:2
    39. AI research evidence record deepseek:c1
    40. AI research evidence record perplexity:c4
    41. AI research evidence record kimi:citany-comparison-2026
    42. AI research evidence record anthropic:34-1
    43. AI research evidence record openai:c4
    44. AI research evidence record anthropic:13-6
    45. AI research evidence record anthropic:13-1
    46. AI research evidence record anthropic:14-4
    47. AI research evidence record perplexity:c12
    48. AI research evidence record openai:c7
    49. AI research evidence record anthropic:1-1
    50. AI research evidence record anthropic:3-8
    51. AI research evidence record anthropic:22-6
    52. AI research evidence record anthropic:3-5
    53. AI research evidence record anthropic:26-1
    54. AI research evidence record anthropic:20-17
    55. AI research evidence record anthropic:21-6
    56. AI research evidence record anthropic:45-6
    57. AI research evidence record anthropic:10-12
    58. AI research evidence record openai:c2
    59. AI research evidence record anthropic:37-3
    60. AI research evidence record anthropic:38-1
    61. AI research evidence record anthropic:4-3
    62. AI research evidence record anthropic:10-11
    63. AI research evidence record anthropic:42-16
    64. AI research evidence record anthropic:4-2
    65. AI research evidence record anthropic:13-1
    66. AI research evidence record anthropic:10-11
    67. AI research evidence record anthropic:10-12
    68. AI research evidence record anthropic:14-4
    69. AI research evidence record google:1.3.5
    70. AI research evidence record google:1.4.1
    71. AI research evidence record grok:web:2
    72. AI research evidence record perplexity:c12
    73. AI research evidence record openai:c4
    74. AI research evidence record openai:c6
    75. AI research evidence record openai:c6
    76. AI research evidence record anthropic:3-5
    77. AI research evidence record anthropic:4-2
    78. AI research evidence record anthropic:45-6
    79. AI research evidence record openai:c6
    80. AI research evidence record anthropic:4-3
    81. AI research evidence record anthropic:10-11
    82. AI research evidence record anthropic:10-12
    83. AI research evidence record anthropic:31-5
    84. AI research evidence record anthropic:4-2
    85. AI research evidence record google:1.3.5
    86. AI research evidence record anthropic:13-6
    87. AI research evidence record anthropic:42-16
    88. AI research evidence record openai:c6
    89. AI research evidence record anthropic:4-2
    90. AI research evidence record anthropic:4-3
    91. AI research evidence record google:1.3.6
    92. AI research evidence record google:1.3.8
    93. AI research evidence record openai:c6
    94. AI research evidence record openai:c7
    95. AI research evidence record anthropic:4-2
    96. AI research evidence record anthropic:34-1
    97. AI research evidence record anthropic:14-4
    98. AI research evidence record openai:c1
    99. AI research evidence record anthropic:3-5
    100. AI research evidence record anthropic:20-17
    101. AI research evidence record anthropic:21-6
    102. AI research evidence record openai:c6
    103. AI research evidence record openai:c7
    104. AI research evidence record anthropic:13-6
    105. AI research evidence record deepseek:c1
    106. AI research evidence record anthropic:1-1
    107. AI research evidence record openai:c4
    108. AI research evidence record grok:web:2
    109. AI research evidence record openai:c7
    110. AI research evidence record kimi:citany-comparison-2026
    111. AI research evidence record anthropic:13-1
    112. AI research evidence record perplexity:c12
    113. AI research evidence record openai:c6

Verify this research

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

Study date
September 19, 2026
Platforms analyzed
7
Source records
45
Ranking mentions
6 of 7
Platform share
86%
Final consensus rank
#1

Research trail and source mix

Configured platforms

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

Source mix

26 independent · 18 company-owned · 1 unclear

Evidence support

21 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 1a18585d00b118ed8baadde8dbf49c1b875bef36d08d4be975e2c64d98663910