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Profound AI Search Audit Fit Review for Companies Losing Google Traffic

Profound is a good fit for companies losing Google traffic that need an enterprise-grade audit of AI-search visibility, but it is not a complete diagnosis on its own.

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

Answer Capsule

Profound is a good fit for companies losing Google traffic that need an enterprise-grade audit of AI-search visibility, but it is not a complete diagnosis on its own. Two of seven platforms named Profound during ranking discovery — a 28.6% share of included platform responses — at an average listed rank of 1.5 and a best rank of 1. The strongest reason to consider it is Answer Engine Insights, which tracks brand visibility, competitors, prompts, and cited sources across major AI answer engines [1]. The main limitation is that Profound monitors rather than executes, does not attribute AI sessions to conversions, and gates full multi-engine coverage behind undisclosed Enterprise pricing [3].

Research Snapshot

FieldValue
Platform mentions in ranking stage2 of 7 platforms (deepseek, openai)
Share of included platform responses28.6%
Average listed rank1.5
Best listed rank1
Relevant product/model/planProfound Enterprise / Answer Engine Insights platform; exact plan and commercial scope should be confirmed through a sales evaluation
Overall use-case fitGood, with an enterprise bias
Research date2026-09-18

Why Profound Qualified for This Study

Questions This Section Answers

  • Is Profound a good choice for AI Search Audits for Companies Losing Google Traffic?
  • Why did only two of seven AI platforms name Profound during ranking discovery?

Profound qualified because it is a purpose-built AI answer-engine visibility and analytics platform, which maps directly to the audit's core requirement: comparing traditional search visibility with AI recommendations, citations, competitor performance, high-intent prompts, source patterns, and GEO opportunities [6].

Two of seven included platforms — deepseek and openai — named Profound during ranking discovery, a 28.6% share of included platform responses. It ranked first on deepseek and second on openai, producing an average listed rank of 1.5 and a best rank of 1. The remaining five platforms evaluated Profound's fit but did not name it in the ranking stage, so the mention count should not be read as broader platform endorsement.

Fit ratings across the seven platforms were split: google and grok rated it a strong fit; openai, anthropic, and deepseek rated it good; perplexity rated it mixed; and kimi rated it uncertain. That spread is itself a finding — the disagreement centers on identity verification, pricing opacity, and whether a monitoring platform counts as an "audit."

The Product, Model, Plan, or Service Most Relevant to AI Search Audits for Companies Losing Google Traffic

Questions This Section Answers

  • Which Profound plan is the effective minimum for a multi-engine AI search audit?
  • Does Profound Answer Engine Insights compare traditional Google visibility with AI recommendations in one view?

The relevant product is Profound's Answer Engine Insights platform, with the Growth plan ($399/month) as the practical minimum for a meaningful multi-engine audit and Enterprise as the tier for full coverage [8].

Answer Engine Insights sends prompts to answer engines and captures generated responses as data points, then presents analytical views for interpreting visibility [10]. Company materials state it analyzes brand performance across AI answer engines and lists coverage including ChatGPT, Perplexity, Claude, Copilot, Google AI Overviews, Google AI Mode, Google Gemini, Grok, and DeepSeek [11]. Independent coverage describes competitor benchmarking, visibility analytics, and source/citation analysis, while characterizing the platform as primarily an AI-search visibility tool rather than a complete execution service [12].

Plan-level coverage is where the audit scope narrows sharply. Starter at $99/month is reported as ChatGPT-only with 50 prompts and 1,500 responses per month [13]. Growth at $399/month is reported as covering three engines — ChatGPT, Perplexity, and Google AI Overviews — with 100 prompts and 9,000 responses [15]. Full coverage of all ten engines, adding Google AI Mode, Gemini, Copilot, Meta AI, Grok, DeepSeek, and Claude, is reported to arrive only on custom Enterprise [17].

For a company losing Google traffic, this matters: the engines most likely to explain a discovery shift may sit behind the Enterprise tier, and Enterprise pricing is not publicly disclosed.

What the AI Platforms Agreed About

Questions This Section Answers

  • What do the AI platforms agree Profound does well for companies losing Google traffic?
  • Is Profound's prompt-volume data considered a genuine differentiator for AI search audits?

The platforms broadly agreed on three capabilities: multi-engine visibility tracking, competitor and citation benchmarking, and real-user prompt-volume data.

On visibility tracking, company materials state the platform queries front-end experiences used by ordinary users rather than API outputs [19], and independent coverage confirms it monitors brand representation across ChatGPT, Perplexity, Claude, and Google AI Overviews [20]. One independent review reports tracking across 10+ platforms including ChatGPT, Perplexity, Claude, Gemini, Grok, Copilot, Meta AI, DeepSeek, Google AI Overviews, and ChatGPT Shopping [21].

On competitive benchmarking, company materials describe prompt-level competitive insights showing which competitors outrank on specific prompts, plus a head-to-head content optimization feature that compares a page against a winning competitor page [22]. Independent coverage describes identifying which pages AI engines reference most for given prompts [24] and which citation sources drive competitor visibility [25].

On prompt data, company materials state Prompt Volumes draws on 1.3B+ real user conversations [26], with prompt discovery powered by hundreds of millions of real user queries per month [27]. Independent reviews call this data "genuinely unmatched" and "the strongest in the category" [28], and one review notes it is a major reason enterprises pay Profound's premium [30].

Agreement among AI platforms does not prove product quality. These are platform-reported and independently published observations, not verified performance outcomes.

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Why do AI platforms disagree about whether Profound counts as an audit provider?
  • Is Profound's official domain verified, and does that affect a purchase decision?

The sharpest disagreement is categorical: is Profound an audit provider or a monitoring tool? One independent source categorizes it as an "AI-visibility monitoring tool — it measures, and it writes nothing," distinguishing it from audit services and done-for-you agencies [31]. Independent reviews echo the monitoring-only framing, stating Profound "won't push a content fix to CMS, source a backlink, or execute a technical SEO change" [32]. The kimi platform therefore rated fit uncertain, while google and grok rated it strong.

Identity is unresolved. The supplied canonical website is [34], but the product sources reviewed use tryprofound.com and help.tryprofound.com, and the relationship between these domains should be verified before purchase [34]. The official-site retrieval for profound.so failed during this research cycle, so no fetched page confirmed the domain. The deepseek platform flagged this as an exact-name fallback match and rated fit good only provisionally.

Pricing is inconsistent. Public sources report Starter at $99/month and Growth at $399/month, with Enterprise as contact-sales [35]. Third-party reviews put enterprise deployments anywhere from $2,000 to $5,000+ per month depending on platform count, seats, and features [37]. One source reports the Growth tier at $499/month rather than $399 [40]. Engine counts also vary: sources describe 9, 10, and "10+" engines [41].

Attribution is a consistent limitation across platforms. Independent coverage states Profound tells you where you appear in AI answers, not which AI sessions landed on your site, which pages they hit, or whether they converted [44]. No source reviewed establishes that Profound can causally attribute a company's Google traffic loss to AI-search visibility changes.

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • Which Profound features directly address a Google traffic decline rather than general AI visibility?
  • Does Profound track AI crawler behavior that could explain lost AI visibility?

For a company losing Google traffic, the most decision-relevant capabilities are prompt-level gap analysis, citation source patterns, and crawler-level diagnostics.

Prompt and response auditing captures answer-engine responses as data points for tracked prompts [46]. Company materials state the platform finds high-volume prompts where competitors get cited over the buyer, then helps prioritize content to close the gap [47]. Independent coverage describes surfacing which specific prompts surface competitors but not the buyer's brand as direct acquisition gaps [48].

Citation and source-pattern analysis identifies which domains AI platforms trust most in a category [49] and which third-party publications power competitor mentions, informing earned media and content priorities [50]. Independent coverage describes tracking which other brands appear alongside yours in AI answers and comparing visibility, links, and citation trends side by side [51].

Crawler-level analytics is the closest thing to a technical diagnostic. Company materials state Agent Analytics reads server logs through CDN integrations with Akamai, AWS, Cloudflare, and Fastly to show which AI crawlers hit a site and what they pull, tying through GA4 to human traffic and conversions [52]. Independent coverage states the platform tracks GPTBot, PerplexityBot, ClaudeBot, and GoogleOther and cross-references IPs to filter spoofed bots [53], and that if GPTBot stops crawling a key page, the buyer sees it before a visibility drop appears in prompt tracking [54]. Note that Agent Analytics is described in one platform's research as an Enterprise feature [52], while another describes crawler tracking as available with GA4 integration — the tier entitlement should be confirmed.

Multi-region and multi-language monitoring is reported at 30+ languages and 150+ regions [55], though one source states the Growth tier restricts tracking to a single region and language [56].

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does Profound cost per month, and is Enterprise pricing published?
  • Are there setup, credit, or workspace fees beyond the base Profound subscription?

Published self-serve pricing is reported as Starter at $99/month and Growth at $399/month, with Enterprise as contact-sales or custom-priced [57]. Pricing confidence is low to moderate across platforms because Enterprise cost is not officially published.

TierReported priceReported coverageReported limits
Starter$99/monthChatGPT only50 prompts, 1,500 responses/month, single region/language, one seat
Growth$399/monthChatGPT, Perplexity, Google AI Overviews100 prompts, 9,000 responses/month, 6 AEO-optimized articles/month
EnterpriseCustom / contact salesUp to 10 engines including Gemini, Claude, Copilot, Grok, Meta AI, DeepSeek, Google AI ModeUnlimited prompts, multiple brands, SSO/SAML, API access, dedicated support

Third-party reviews put enterprise deployments at $2,000–$5,000+ per month depending on platform count, seats, and features [60]. One source reports annual billing discounts of roughly two months free on Starter and Growth [63]. Agency pricing is reported separately: $99/month with 10 pitch workspaces, and additional client workspaces at $399/month each [65].

Additional fees are unclear. Sources flag potential overages on prompts, credits, or agents [64], credit-metered agent work on top of the base subscription [66], and possible charges for additional prompts, companies, domains, regions, languages, data retention, implementation, integrations, premium support, or professional services [57]. Contract length, renewal, cancellation, refund, service-level, and implementation terms are not established in the public sources reviewed [57].

Best Suited For

Questions This Section Answers

  • Who gets the most value from Profound for an AI search audit after a Google traffic decline?
  • Does Profound suit a company that needs recurring competitive monitoring rather than a one-time audit?

Profound is best suited to enterprise and mid-market marketing, SEO, content, PR, or digital-intelligence teams that need recurring competitive monitoring across multiple answer engines rather than a single manual audit [68].

It fits buyers that require prompt-level visibility, citation and source analysis, prompt-volume data, exports, API access, and enterprise controls [68]. It fits brands in high-intent categories that need competitor citation analysis and prompt benchmarking [69]. It fits teams with in-house content or SEO execution capacity to act on audit findings, since the platform diagnoses rather than implements [71]. It also fits agencies running multi-client AI audits on demand, given the reported agency workspace structure [73].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose Profound for AI Search Audits for Companies Losing Google Traffic?
  • Is Profound a poor fit for a small company wanting an inexpensive one-time diagnostic?

Profound is probably not the best fit for small companies wanting an inexpensive, one-time diagnostic [74]. The $99 Starter tier tracks ChatGPT only, which is insufficient for a multi-engine audit of Google traffic loss that may be distributed across Perplexity, Gemini, Claude, and other engines [75].

It is also a weak fit for teams needing a complete traditional Google SEO forensic audit, backlink recovery program, or guaranteed traffic remediation [74]. Public evidence does not establish that Profound independently diagnoses algorithmic penalties, technical SEO defects, backlink changes, indexing problems, or conversion-impact attribution [77]. It is a poor fit for buyers needing execution services rather than analytics and recommendations [78], and for buyers who need to track Claude, Gemini, or Grok without a sales conversation, since those engines are reported as Enterprise-only [80].

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to Profound when the buyer needs AI traffic attribution to conversions?
  • When is a traditional SEO suite or a lower-cost AI visibility tool a better choice than Profound?

Another option may be better in several specific situations, and the platforms named alternatives directly.

When the primary question is why Google organic sessions, rankings, indexing, links, or conversions declined, a traditional SEO suite or specialist forensic SEO agency is the better choice [82]. When the buyer needs AI traffic attribution to on-site conversions and revenue KPIs, tools with GA4 integration for conversion tracking are suggested [83]. When the budget is under $400/month and only single-engine ChatGPT tracking is needed, lower-cost alternatives are suggested [83]. When the buyer needs traditional SEO and AI visibility combined in one tool, unified SEO+AEO stacks are suggested [83]. When the buyer needs Gemini, Claude, or Copilot tracking without a sales call, self-serve multi-engine options are suggested [83]. When the buyer needs a one-time audit with an actionable fix plan, one-time scored audit services are suggested [84]. When the buyer lacks internal capacity to implement technical, content, publisher, or digital-PR recommendations, an execution-oriented GEO or content agency is the better choice [82].

A combined stack is the recommended path when the buyer needs both Google Search Console or analytics-based traffic attribution and multi-engine AI recommendation monitoring [82].

Questions to Verify Before Buying

Questions This Section Answers

  • What should a buyer confirm with Profound before signing an Enterprise contract?
  • Does Profound connect to Google Search Console or GA4 to correlate AI visibility with actual traffic?

The platforms converged on a verification checklist. Buyers should confirm the legal entity, domain, and contracting party, since the supplied identity uses profound.so while product sources use tryprofound.com and help.tryprofound.com [85].

Buyers should confirm which exact answer engines, Google surfaces, countries, languages, devices, and browsing modes are included in the proposed Enterprise package, and how many prompts, prompt refreshes, tracked competitors, domains, brands, users, and historical months are included [85]. They should confirm whether the audit includes source URLs, citation-level exports, competitor gaps, prompt-volume estimates, and prioritized GEO recommendations [85].

Buyers should confirm whether Profound can ingest or connect Google Search Console, Google Analytics, rank-tracking, CRM, CDN, or server-log data to correlate AI visibility with actual traffic and conversions [85]. They should confirm the methodology, sampling frequency, confidence controls, and change-detection rules used for volatile AI answers [85].

Buyers should confirm whether API access, SSO/SAML, data exports, integrations, dedicated support, and strategic services are included or separately priced, and what the annual commitment, renewal, cancellation, refund, data-retention, security, and service-level terms are [85]. They should confirm whether Profound provides implementation assistance or whether the buyer must separately staff technical SEO, content, PR, and engineering work [85]. Finally, buyers should ask whether the vendor can demonstrate a before-and-after audit for a company that lost Google traffic and distinguish AI-search opportunity from ordinary SEO causes [85].

Final AI Consensus Verdict

Profound is a good fit, with an enterprise bias, for AI Search Audits for Companies Losing Google Traffic. It is well aligned to the AI-search portion of an audit: multi-engine visibility, prompt analysis, competitor benchmarking, and cited-source patterns [87]. It is not sufficient by itself for a complete diagnosis of declining Google traffic, and the recommended Enterprise plan has opaque pricing and unresolved scope details [90].

The consensus is not unanimous. Two of seven platforms named Profound in ranking discovery, and fit ratings ranged from strong (google, grok) to good (openai, anthropic, deepseek) to mixed (perplexity) to uncertain (kimi). The uncertainty is concentrated in three places: unresolved domain identity, undisclosed Enterprise pricing, and the monitoring-versus-execution distinction.

Buy only after confirming domain identity, current engine coverage, data methodology, Google and analytics integrations, implementation responsibility, and total contract cost. The full comparison of providers for this use case is available in the AI Search Audits for Companies Losing Google Traffic consensus index, and related provider research sits in the ai search audits market intelligence directory.

How This Review Was Produced

This review was produced from seven AI platform research responses collected for the use case "AI Search Audits for Companies Losing Google Traffic," with a research date of 2026-09-18. Each platform independently evaluated Profound's fit and, where applicable, named it during ranking discovery. Two of seven platforms named Profound in the ranking stage. Fit ratings, strengths, limitations, pricing observations, and verification questions were aggregated from the supplied platform outputs.

Citations are platform-reported evidence, not independently verified facts. Company-owned sources are labeled as owned; independent sources are labeled as independent. Where a platform supplied no citation for a factual claim, the claim is labeled platform-reported or unverified.

Methodology Limitations

Several limitations apply. The supplied URLs were collected from platform responses and were not independently validated by the writer stage. Platform-reported research dates differ from the authoritative run date: deepseek reported 2026-06-30 while the remaining platforms reported 2026-09-18, so deepseek's observations may be less current.

The deterministic identity audit flagged that conflicting official domains forced an unresolved identity, that official-site retrieval failed for one or more mentions, and that identity was resolved by exact-name fallback. The matching reported domain was retained for downstream research but remains unverified. The official-site retrieval for profound.so failed during this cycle, so no fetched page confirmed the domain.

Public sources disagree or are incomplete on exact engine counts, plan entitlements, prompt limits, API availability, and Enterprise feature packaging. Enterprise pricing is not publicly disclosed in the sources reviewed. Independent reviews provide useful product and pricing observations but are not contractual evidence and may reflect different dates, plan configurations, or testing access. No source reviewed establishes that Profound can causally attribute a company's Google traffic loss to AI-search visibility changes. AI answers vary by model, time, location, personalization, browsing state, and prompt formulation; measured visibility is not equivalent to actual traffic, revenue, or causation.

Explore more ai search audits market intelligence guidance in the category directory.

Sources

Company-Owned Sources

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  • The Complete AEO Platform | Profound: https://www.tryprofound.com/
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  • How To Run a Technical SEO Audit for AI Search Visibility: https://www.tryprofound.com/blog/technical-seo-audit-ai
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  • Additional AI research evidence91 records
    1. AI research evidence record openai:c2
    2. AI research evidence record anthropic:11-6
    3. AI research evidence record anthropic:4-12
    4. AI research evidence record anthropic:8-3
    5. AI research evidence record anthropic:35-1
    6. AI research evidence record deepseek:c1
    7. AI research evidence record openai:c2
    8. AI research evidence record anthropic:33-1
    9. AI research evidence record anthropic:36-5
    10. AI research evidence record openai:c3
    11. AI research evidence record openai:c2
    12. AI research evidence record openai:c4
    13. AI research evidence record anthropic:36-1
    14. AI research evidence record anthropic:34-12
    15. AI research evidence record anthropic:33-2
    16. AI research evidence record anthropic:34-13
    17. AI research evidence record anthropic:34-14
    18. AI research evidence record anthropic:33-3
    19. AI research evidence record anthropic:10-2
    20. AI research evidence record anthropic:13-1
    21. AI research evidence record anthropic:2-6
    22. AI research evidence record anthropic:19-4
    23. AI research evidence record anthropic:19-5
    24. AI research evidence record anthropic:21-2
    25. AI research evidence record anthropic:26-22
    26. AI research evidence record anthropic:10-5
    27. AI research evidence record anthropic:10-6
    28. AI research evidence record anthropic:34-2
    29. AI research evidence record anthropic:34-8
    30. AI research evidence record anthropic:31-11
    31. AI research evidence record kimi:trirank_a
    32. AI research evidence record anthropic:8-3
    33. AI research evidence record anthropic:35-18
    34. AI research evidence record deepseek:c1
    35. AI research evidence record openai:c1
    36. AI research evidence record anthropic:29-1
    37. AI research evidence record anthropic:1-9
    38. AI research evidence record anthropic:31-1
    39. AI research evidence record anthropic:35-1
    40. AI research evidence record google:1.2.3
    41. AI research evidence record grok:5
    42. AI research evidence record anthropic:34-14
    43. AI research evidence record anthropic:2-6
    44. AI research evidence record anthropic:4-12
    45. AI research evidence record anthropic:4-13
    46. AI research evidence record openai:c3
    47. AI research evidence record anthropic:10-7
    48. AI research evidence record anthropic:26-20
    49. AI research evidence record anthropic:3-10
    50. AI research evidence record anthropic:3-11
    51. AI research evidence record anthropic:21-1
    52. AI research evidence record anthropic:14-14
    53. AI research evidence record anthropic:16-1
    54. AI research evidence record anthropic:16-2
    55. AI research evidence record anthropic:11-7
    56. AI research evidence record google:1.2.6
    57. AI research evidence record openai:c1
    58. AI research evidence record anthropic:29-1
    59. AI research evidence record anthropic:36-1
    60. AI research evidence record anthropic:1-9
    61. AI research evidence record anthropic:31-1
    62. AI research evidence record anthropic:35-1
    63. AI research evidence record anthropic:36-5
    64. AI research evidence record grok:9
    65. AI research evidence record anthropic:33-5
    66. AI research evidence record google:1.2.7
    67. AI research evidence record anthropic:1-1
    68. AI research evidence record openai:c1
    69. AI research evidence record anthropic:1-1
    70. AI research evidence record anthropic:29-8
    71. AI research evidence record anthropic:8-3
    72. AI research evidence record google:1.1.7
    73. AI research evidence record anthropic:33-5
    74. AI research evidence record openai:c1
    75. AI research evidence record anthropic:34-12
    76. AI research evidence record anthropic:1-7
    77. AI research evidence record openai:c5
    78. AI research evidence record anthropic:8-3
    79. AI research evidence record anthropic:35-18
    80. AI research evidence record anthropic:2-2
    81. AI research evidence record anthropic:34-14
    82. AI research evidence record openai:c1
    83. AI research evidence record anthropic:1-1
    84. AI research evidence record kimi:trirank_a
    85. AI research evidence record openai:c1
    86. AI research evidence record deepseek:c1
    87. AI research evidence record openai:c2
    88. AI research evidence record anthropic:19-4
    89. AI research evidence record anthropic:3-10
    90. AI research evidence record openai:c1
    91. AI research evidence record anthropic:35-1

Independent Sources

  • Top 10 Tools for AI Search Competitor Analysis in 2026: https://airankchecker.net/blog/tools-for-ai-search-competitor-analysis/
  • Profound Pricing 2026: What It Actually Costs: https://arobis.ai/blog/profound-pricing
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  • Profound AI Review 2026: Strong Data, But Here's the Real Catch - Scalenut: https://www.scalenut.com/blog/profound-ai-review
  • Profound AI Review 2026: Limits, Pricing & Results - Analyze AI: https://www.tryanalyze.ai/blog/profound-ai-review
  • Searchable vs Profound (2026): Which AI Search Visibility Platform Wins? - YouTube: https://www.youtube.com/watch?v=Fj8eqvRDG3I
  • Additional AI research evidence91 records
    1. AI research evidence record openai:c2
    2. AI research evidence record anthropic:11-6
    3. AI research evidence record anthropic:4-12
    4. AI research evidence record anthropic:8-3
    5. AI research evidence record anthropic:35-1
    6. AI research evidence record deepseek:c1
    7. AI research evidence record openai:c2
    8. AI research evidence record anthropic:33-1
    9. AI research evidence record anthropic:36-5
    10. AI research evidence record openai:c3
    11. AI research evidence record openai:c2
    12. AI research evidence record openai:c4
    13. AI research evidence record anthropic:36-1
    14. AI research evidence record anthropic:34-12
    15. AI research evidence record anthropic:33-2
    16. AI research evidence record anthropic:34-13
    17. AI research evidence record anthropic:34-14
    18. AI research evidence record anthropic:33-3
    19. AI research evidence record anthropic:10-2
    20. AI research evidence record anthropic:13-1
    21. AI research evidence record anthropic:2-6
    22. AI research evidence record anthropic:19-4
    23. AI research evidence record anthropic:19-5
    24. AI research evidence record anthropic:21-2
    25. AI research evidence record anthropic:26-22
    26. AI research evidence record anthropic:10-5
    27. AI research evidence record anthropic:10-6
    28. AI research evidence record anthropic:34-2
    29. AI research evidence record anthropic:34-8
    30. AI research evidence record anthropic:31-11
    31. AI research evidence record kimi:trirank_a
    32. AI research evidence record anthropic:8-3
    33. AI research evidence record anthropic:35-18
    34. AI research evidence record deepseek:c1
    35. AI research evidence record openai:c1
    36. AI research evidence record anthropic:29-1
    37. AI research evidence record anthropic:1-9
    38. AI research evidence record anthropic:31-1
    39. AI research evidence record anthropic:35-1
    40. AI research evidence record google:1.2.3
    41. AI research evidence record grok:5
    42. AI research evidence record anthropic:34-14
    43. AI research evidence record anthropic:2-6
    44. AI research evidence record anthropic:4-12
    45. AI research evidence record anthropic:4-13
    46. AI research evidence record openai:c3
    47. AI research evidence record anthropic:10-7
    48. AI research evidence record anthropic:26-20
    49. AI research evidence record anthropic:3-10
    50. AI research evidence record anthropic:3-11
    51. AI research evidence record anthropic:21-1
    52. AI research evidence record anthropic:14-14
    53. AI research evidence record anthropic:16-1
    54. AI research evidence record anthropic:16-2
    55. AI research evidence record anthropic:11-7
    56. AI research evidence record google:1.2.6
    57. AI research evidence record openai:c1
    58. AI research evidence record anthropic:29-1
    59. AI research evidence record anthropic:36-1
    60. AI research evidence record anthropic:1-9
    61. AI research evidence record anthropic:31-1
    62. AI research evidence record anthropic:35-1
    63. AI research evidence record anthropic:36-5
    64. AI research evidence record grok:9
    65. AI research evidence record anthropic:33-5
    66. AI research evidence record google:1.2.7
    67. AI research evidence record anthropic:1-1
    68. AI research evidence record openai:c1
    69. AI research evidence record anthropic:1-1
    70. AI research evidence record anthropic:29-8
    71. AI research evidence record anthropic:8-3
    72. AI research evidence record google:1.1.7
    73. AI research evidence record anthropic:33-5
    74. AI research evidence record openai:c1
    75. AI research evidence record anthropic:34-12
    76. AI research evidence record anthropic:1-7
    77. AI research evidence record openai:c5
    78. AI research evidence record anthropic:8-3
    79. AI research evidence record anthropic:35-18
    80. AI research evidence record anthropic:2-2
    81. AI research evidence record anthropic:34-14
    82. AI research evidence record openai:c1
    83. AI research evidence record anthropic:1-1
    84. AI research evidence record kimi:trirank_a
    85. AI research evidence record openai:c1
    86. AI research evidence record deepseek:c1
    87. AI research evidence record openai:c2
    88. AI research evidence record anthropic:19-4
    89. AI research evidence record anthropic:3-10
    90. AI research evidence record openai:c1
    91. AI research evidence record anthropic:35-1

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
46
Ranking mentions
2 of 7
Platform share
29%
Final consensus rank
#1

Research trail and source mix

Configured platforms

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

Source mix

28 independent · 18 company-owned

Evidence support

38 direct · 8 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 ac2ab787dbc932dceffa556819b541bb4d90753effdf808bbff6357cd0afac67