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AI Consensus Fit Review

Semrush AI Visibility Platforms Overall Fit Review

Semrush is a good — not best-in-class — fit for AI Visibility Platforms, and it is the strongest fit for companies already using Semrush for SEO.

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

Answer Capsule

Semrush is a good — not best-in-class — fit for AI Visibility Platforms, and it is the strongest fit for companies already using Semrush for SEO. Four of seven platforms named Semrush during the ranking stage (deepseek, grok, openai, perplexity), a 57% share of included platform responses, at an average listed rank of 4.0 and a best rank of 3. Its strongest reason to consider it is integrated AI visibility measurement — mentions, citations, sentiment, share of voice, competitor gaps, and daily prompt tracking — inside an existing SEO workflow. Its main limitation is documented engine coverage: Claude, Grok, DeepSeek, and Kimi are not verified in official sources, and coverage varies by report.

Research Snapshot

FieldValue
Platform mentions in ranking stage4 of 7 platforms (deepseek, grok, openai, perplexity)
Share of included platform responses57.1%
Average listed rank4.0
Best listed rank3 (perplexity)
Relevant product/model/planAI Visibility Toolkit Base ($99/month per domain, billed annually); also bundled in Semrush One plans
Overall use-case fitGood for SEO-led teams; mixed for buyers requiring all seven named AI systems
Research date2026-09-19

Why Semrush Qualified for This Study

Questions This Section Answers

  • Why did multiple AI platforms recommend Semrush for AI visibility tracking in 2026?
  • Is Semrush a good choice for AI Visibility Platforms if I already pay for Semrush SEO tools?

Semrush qualified because four of the seven included platforms named it during ranking discovery, and because it ships a documented product built for this use case rather than a generic SEO feature. The AI Visibility Toolkit is explicitly designed to monitor brand and competitor positioning across AI-generated answers [1]. Independent reviewers place it in the category alongside dedicated tools: CB Insights named Semrush a "Highflier" among 15 companies in generative engine optimization monitoring, including Scrunch, Profound, and Peec AI [3].

Its qualification rests on three supplied strengths. First, integration: the toolkit sits inside the same dashboard as 27.5 billion tracked keywords and 43 trillion backlinks, letting teams correlate traditional SEO performance with AI presence [4]. Second, data scale: Semrush documents a prompt database of more than 317 million prompts and responses [7], while independent reviews cite a 126-million-prompt 2026 index [9]. Third, refresh cadence: Visibility Overview, Competitor Research, and Prompt Research refresh daily, and tracked prompts run daily, where several rivals refresh weekly [11].

Qualification is not the same as endorsement. The same reviewers who credit the data scale also flag engine gaps and thin base-tier sampling, detailed below.

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

Questions This Section Answers

  • Which Semrush plan should a buyer choose for AI visibility tracking across ChatGPT, Gemini, and Perplexity?
  • Is the Semrush AI Visibility Toolkit a standalone product or an add-on to an existing Semrush subscription?

The relevant offering is the Semrush AI Visibility Toolkit, sold as a standalone add-on at $99 per month per domain billed annually, or bundled inside Semrush One plans [13]. Semrush One tiers scale prompt limits: Starter at $199/month with 50 prompts, Pro+ at $299/month with 100 prompts, and Advanced at $549/month with 200 prompts [16].

The toolkit contains six core reports: Visibility Overview, Competitor Research, Prompt Research, Brand Performance, Prompt Tracking, and an AI Search Site Audit [18]. Visibility Overview shows an AI Visibility Score from 0 to 100 reflecting how often the brand is mentioned across AI platforms [20]. Brand Performance covers platform perception, share of voice, sentiment, and narrative drivers [22]. Prompt Tracking reports cited domains and URLs, brand mentions, mention rate, competitor citations, citation position, lost mentions, and changes over time [25].

Product naming is genuinely inconsistent across the supplied evidence. Ranking-stage descriptions reference an "AI SEO Toolkit add-on," an "AI Visibility add-on," a "Brand Performance entry plan," "AI Visibility Toolkit Base," and "Semrush AI Toolkit" [26]. Current official materials primarily describe the AI Visibility Toolkit and Semrush One. Buyers should confirm the exact current product name and plan path rather than assume these labels describe distinct products.

What the AI Platforms Agreed About

Questions This Section Answers

  • What do AI platforms agree Semrush does well for AI visibility monitoring?
  • Does Semrush track brand mentions, citations, and sentiment across AI answers?

Agreement was strong on capability and integration, and unanimous on the core limitation. All four platforms that named Semrush described it as a capable AI visibility measurement layer, and none described it as a dedicated, AI-native monitoring platform.

On capabilities, the platforms converged. Semrush tracks mentions, citations, sentiment, share of voice, competitor gaps, and prompt research [28]. Prompt Tracking reports cited domains and URLs, mention rate, competitor citations, citation position, and lost mentions over time [30]. Brand Performance compares how different AI platforms perceive a brand versus competitors, focusing on share of positive sentiment [31]. Independent reviews confirm the toolkit tracks mentions, citations, sentiment, and share of voice across ChatGPT, Perplexity, Gemini, Google AI Mode, and Copilot, with Enterprise AIO extending to Claude, DeepSeek, and Grok [33].

On integration, the platforms agreed that Semrush's differentiator is workflow consolidation. Adding AI visibility into the Semrush ecosystem means connecting and correlating traditional SEO performance with AI presence in a single dashboard [34]. The Organic Rankings tool flags which keywords now trigger AI Overviews and whether the domain is cited [36].

On refresh cadence, the platforms agreed that daily tracking is a real advantage. Visibility Overview, Competitor Research, and Prompt Research refresh daily; Brand Performance refreshes weekly; tracked prompts run daily [38]. Independent reviewers call daily prompt tracking a differentiator where several rivals refresh weekly [39].

Agreement among AI platforms reflects shared source material, not verified product quality. Much of the underlying evidence is company-owned.

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Does Semrush track Claude, Grok, DeepSeek, and Kimi, or only ChatGPT, Gemini, and Perplexity?
  • How reliable is the Semrush AI Visibility Score given undisclosed sample sizes?

The platforms disagreed on engine coverage, and the disagreement is not resolvable from the supplied evidence. Semrush's own materials document different platform sets by report: the prompt database lists ChatGPT, Gemini, Google AI Overviews, and AI Mode; Brand Performance lists Google AI Mode, ChatGPT, Perplexity, and Gemini; Prompt Tracking lists Google AI Mode, AI Overviews, Gemini, and ChatGPT Search [40]. One official page states the toolkit tracks ChatGPT, Gemini, Perplexity, SearchGPT, Google AI Mode, and Google AI Overviews [41], while another states daily Prompt Tracking currently supports only ChatGPT, Google AI Mode, and Gemini, with other engines covered in general reports [42].

Independent reviews are more consistent about the gaps. Multiple reviewers state Claude, Microsoft Copilot, and DeepSeek are available only in a custom-priced Enterprise AIO product, and Grok is not covered on any self-serve tier [43]. One review states the toolkit does not cover Claude, Copilot, Grok, DeepSeek, Doubao, or Qwen [47]. Another states there is no Claude or Meta AI coverage [48]. Coverage of Kimi was not verified in any supplied source.

The platforms also disagreed on methodology transparency. Semrush does not disclose the sample size behind the AI Visibility Score or the number of prompt runs per report cycle; documentation states only that reports "gather a vast collection of common queries and run them through LLMs" [49]. Independent testing found the same prompt returns a different response about 70% of the time, and the brand named first changed in 28–44% of identical reruns [51]. One reviewer concludes the 25-prompt entry sample makes the headline AI Visibility Score a directional read rather than a defensible figure [52].

Prompt database figures conflict. Marketing materials cite a 126-million-prompt 2026 index [53], toolkit documentation cites 317 million or more prompts [40], and one official page cites over 26 million prompts and responses [55]. It is unclear whether these represent the same dataset at different times or different datasets.

One platform, kimi, reported that official-site retrieval failed and could not verify Semrush's AI visibility documentation at all, rating the fit uncertain [56]. That is a retrieval failure, not evidence of absence.

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • What AI visibility features does the Semrush AI Visibility Toolkit include for prompt and competitor tracking?
  • Can Semrush show which pages and domains AI systems cite for my tracked prompts?

The toolkit covers the core tracking requirements of this use case, with documented limits on engine breadth. It provides Visibility Overview, Competitor Research, Prompt Research, Brand Performance, and Prompt Tracking [57].

Prompt and citation tracking. Prompt Tracking reports cited domains and URLs, brand mentions, mention rate, competitor citations, citation position, lost mentions, and changes over time for tracked prompts [58]. The base tier tracks 25 custom prompts daily [59].

Competitor and sentiment analysis. Brand Performance provides competitive perception by platform, comparing how different AI platforms perceive a brand versus competitors with a focus on share of positive sentiment [61]. For each brand, users can see the percentage of favorable sentiment across platforms including ChatGPT, Gemini, and Perplexity [62].

Recommendations and optimization workflow. Semrush provides source and topic opportunities, cited-page recommendations, AI-generated strategic recommendations, and AI Search Site Audit checks for technical blockers affecting AI crawlers [57]. One independent reviewer notes that some AI-generated strategic opportunities can feel unrealistic or difficult to implement [64]. Another states the toolkit identifies gaps and suggests on-page rewrites but does not provide an end-to-end execution loop — content generation, QA, publishing, and citation verification remain with the user [65].

Data methodology and freshness. Semrush states its main AI-analysis reports use a database of more than 317 million prompts and responses, updated daily on a rolling basis, while Brand Performance updates weekly and Prompt Tracking queries selected prompts daily [63]. Semrush characterizes the metrics as directional because AI responses are dynamic and personalized [63]. The AI Visibility Score is a proprietary benchmark based on topic coverage and mention consistency or competitor comparison, not an independently audited measure [63].

Geographic and language coverage. Visibility, competitor, and prompt research support multiple regional databases; Brand Performance is tied to a selected domain, location, and language [57]. One independent review states standard plans cover six markets — US, UK, Canada, Australia, India, and Spain — with data available in US English only, and LATAM coverage limited outside Spain [70]. Another states Enterprise AIO extends coverage to 38 countries and 28 languages [73]. These claims conflict and should be verified for the buyer's account.

Exports and reporting. The base tier includes 10 CSV exports per day [74]. Reports integrate with My Reports for PDF and shareable dashboards [75].

A gap noted by one independent reviewer: Semrush lacks CDN integration for accurate monitoring and cannot detect bot blocks or unintended firewall rules hampering AI visibility [76].

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does the Semrush AI Visibility Toolkit cost per month, and what do extra domains and prompts add?
  • Is there a free trial or refund policy for the Semrush AI Visibility Toolkit?

The published entry price is $99 per month per domain, billed annually, with no free trial documented for the standalone toolkit [78]. Pricing confidence is moderate: the official pricing page displays the annual-billing figure, while monthly checkout pricing and promotional pricing are unclear [78].

ItemPublished cost
AI Visibility Toolkit Base$99/month per domain, billed annually
Additional Brand Performance domain or location$99/month each
Additional 50 tracked prompts$60/month
Additional user license$99 per subuser (knowledge base) or from $45/month (pricing page)
Semrush One Starter$199/month (50 prompts, 1 domain)
Semrush One Pro+$299/month (100 prompts, 15 domains)
Semrush One Advanced$549/month (200 prompts, 40 domains)
Enterprise AIO (Claude, Copilot, DeepSeek coverage)Custom pricing, not disclosed

Sources: [78].

Base inclusions: 25 custom prompts for daily tracking, one Brand Performance domain, 300 daily AI-analysis reports, 1,000 daily Prompt Research queries, AI Search checks for up to 100 pages, and 10 CSV exports per day [78].

Two pricing conflicts are unresolved in the supplied evidence. First, additional users are listed at $99 per subuser in the knowledge base but starting at $45 per month on the pricing page [78]. Second, third-party reviews report extra-domain, extra-prompt, and reporting add-on fees that are not fully consistent across public sources [86]. Base Report and Pro Report add-ons are listed at $10 and $20 per month respectively, but their necessity for AI visibility use should be confirmed [78].

Contract terms. The pricing page states subscriptions can be canceled, upgraded, or downgraded at any time unless custom terms or a signed agreement apply [78]. For annual subscriptions, adding the toolkit aligns it to the existing annual billing cycle and may create a prorated charge for the remaining term [78]. The cited sources do not establish refund terms [78]. Third-party sources report 7-day and 14-day trials for Semrush One with discrepancies by partner, while the standalone toolkit has no documented trial [79].

Scaling cost is the most consistent independent criticism. Per-domain and per-seat pricing stacks rapidly for agencies and multi-brand teams [81]. One reviewer notes that for a team tracking 10 domains at 100 prompts, per-domain stacking becomes prohibitive relative to per-seat or unlimited-domain models [81].

Best Suited For

Questions This Section Answers

  • Who gets the most value from Semrush for AI visibility tracking in 2026?
  • Is Semrush worth it for an in-house SEO team monitoring ChatGPT and Gemini?

Semrush is best suited to companies already inside the Semrush ecosystem. The strongest fit is an existing Semrush subscriber adding AI visibility monitoring without switching platforms, because the marginal complexity is low and the data sits beside existing SEO reporting [91].

The supplied evidence supports four buyer profiles:

  • Existing Semrush customers adding AI visibility monitoring without switching platforms [91].
  • Content and SEO teams with established workflows wanting a unified AI-plus-SEO dashboard [92].
  • Brands in search-driven verticals — SaaS, publishers, e-commerce — protecting organic keywords from AI Overview displacement [95].
  • Teams needing daily prompt tracking and competitor benchmarking within an existing Semrush login, with 25–200 prompt tracking needs [97].

One reviewer frames the boundary clearly: if you simply need to monitor where you stand, Semrush is sufficient [99].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose Semrush for AI Visibility Platforms?
  • Is Semrush a poor fit for agencies managing many client domains?

Semrush is probably not the best fit for buyers whose defining requirement is comprehensive multi-engine coverage or low-cost standalone tracking. The supplied evidence identifies four exclusion profiles.

Buyers requiring Claude, Microsoft Copilot, DeepSeek, or Grok on a standard plan. These are documented only in a custom-priced Enterprise AIO product, and Grok is not covered on any self-serve tier [100]. One reviewer calls the Claude absence a blind spot for brands competing in B2B corporate environments — consulting, legal, financial services — where Claude is a reference model [104]. Another notes Copilot has the highest penetration in Microsoft 365 environments, where it is frequently the first point of query in enterprise settings [106].

Agencies managing many domains. Per-domain and per-seat pricing stacks rapidly; the base tier tracks only 25 prompts [100].

Startups without existing Semrush investment. Entry-level alternatives are cited at $29/month (Otterly), roughly $25/month (Trackerly), and free (CheckThat.ai) — 66–75% cheaper than the $99 Semrush base tier [100].

Organizations needing execution support. The toolkit reports findings and directions but does not generate, gate, publish, or verify content; dedicated platforms like Meev run that loop end to end [110].

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to Semrush for a buyer who needs Claude, Copilot, DeepSeek, or Grok coverage?
  • When should a buyer choose a dedicated AI visibility tool instead of the Semrush AI Visibility Toolkit?

Another option may be better in five documented situations.

When engine breadth is the priority. Reviewers cite GEO Metrics (9 engines from entry plan), MaxAEO (9 engines), and Rankscale (17+ engines from roughly €20/month) as offering broader coverage without custom pricing [112]. Rankscale documents tracking of 17+ engines including ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews, AI Mode, Copilot, DeepSeek, Mistral, and Grok [113].

When per-domain stacking is prohibitive. Dedicated tools with per-seat or unlimited-domain models — Sightivo, Profound, Peec AI — scale better for agencies managing 10 or more domains [112].

When verbatim answer evidence is required. Purpose-built platforms such as Viali, SE Visible, Discoverable, BeVisible, and Ceyo document per-query answer text, share of voice, sentiment, and citation classification [114]. BeVisible explicitly preserves the prompt and generated answer for reviewability [119].

When execution, not measurement, is the gap. Meev, MaxAEO, and specialized GEO platforms bundle execution workflows; Semrush reports findings only [120].

When multi-country or non-English coverage is required. Standard plans are described as limited to six markets with US English data, while GEO Metrics and Rankscale are cited at 38+ countries and multiple languages from the entry tier [123].

Questions to Verify Before Buying

Questions This Section Answers

  • What should a buyer confirm with Semrush before signing a contract for AI visibility tracking?
  • How can a buyer validate Semrush AI visibility accuracy against their own prompts before purchase?

The supplied research surfaces ten verification items. Buyers should treat each as unresolved until Semrush confirms it in writing.

  1. Which exact AI systems are available in the buyer's United States account today, including Claude, Grok, DeepSeek, and Kimi [126]?
  2. Are results collected from live queries, a sampled prompt database, or both, for each required report and platform [126]?
  3. How many times per month does Semrush run each tracked prompt, and what is the confidence interval for the AI Visibility Score given answer volatility [129]?
  4. Can the buyer upload and track its own prompt set, and what are the exact daily, monthly, domain, location, and user limits [131]?
  5. Are citation URLs, answer snapshots, historical responses, lost mentions, and competitor comparisons exportable through CSV, API, or integrations [133]?
  6. How often is each platform's data refreshed, and what historical retention period is included [135]?
  7. What is the exact monthly price, annual commitment, renewal behavior, refund policy, and prorated-cancellation treatment for the selected plan [131]?
  8. Does the buyer need an existing SEO Toolkit subscription, Semrush One subscription, or any additional module to obtain all required capabilities [137]?
  9. How are brand aliases, product names, subsidiaries, misspellings, and multilingual mentions detected and corrected [139]?
  10. Can Semrush demonstrate coverage and accuracy for the buyer's priority prompts and competitors before purchase [140]?

One reviewer's guidance applies directly: findings conflict across sources, so verify current coverage directly with each vendor [140].

Final AI Consensus Verdict

Semrush is a good fit for AI Visibility Platforms, with a clear condition attached. Four of seven platforms named it in the ranking stage at an average listed rank of 4.0, and the fit ratings across platforms were good for openai, anthropic, deepseek, google, and perplexity, mixed for grok, and uncertain for kimi. No platform rated it a strong or best-in-class fit.

The consensus case for Semrush is integration plus data scale: AI visibility measurement — mentions, citations, sentiment, share of voice, competitor gaps, prompt research, and daily prompt tracking — inside an existing SEO workflow with 27.5 billion keywords and 43 trillion backlinks behind it [141].

The consensus case against is threefold. Engine coverage excludes Claude, Copilot, DeepSeek, and Grok from standard plans, with Grok absent from all self-serve tiers [146]. Base-tier sampling of 25 prompts plus undisclosed run counts makes the AI Visibility Score directional rather than defensible [150]. Per-domain pricing at $99/month stacks rapidly for agencies and multi-brand teams [146].

Purchase should be contingent on verifying current model coverage, limits, pricing, and data methodology directly with Semrush. For buyers already paying for Semrush, the trade-off is defensible. For buyers whose defining requirement is verified coverage across all seven named AI systems, a dedicated platform is the better starting point. The broader AI Visibility Platforms consensus index compares Semrush against the other finalists.

Buyers evaluating this category alongside traditional search tooling can also review the ai visibility llm monitoring directory for related platform research.

How This Review Was Produced

This review synthesizes fit-research responses from seven AI platforms — openai, anthropic, deepseek, grok, kimi, perplexity, and google — each asked whether Semrush fits the AI Visibility Platforms use case. Four platforms named Semrush during ranking discovery; all seven evaluated fit. Platform mentions count only platforms that named the entity during ranking discovery, not all platforms that evaluated it.

The study date is 2026-09-19. Platform-reported research dates are provenance metadata and do not independently prove freshness; one platform (deepseek) reported a research date of 2026-06-15, which differs from the authoritative run date. All included platforms evaluated fit, but platform_mentions counts only platforms that named the entity during ranking discovery.

Citations are platform-reported evidence, not independently verified facts. Company-owned citations materially outnumber independent citations in the supplied catalog (29 owned versus 20 independent), so company claims should not be described as independently verified. The supplied URLs were collected from platform responses and were not independently validated by the writer stage. No-search model claims require explicit verification before being described as current facts.

Methodology Limitations

Several limitations constrain this review.

Conflicting product names, pricing, and capabilities were not resolved by guessing. The evidence describes the AI Visibility Toolkit, Semrush One, an AI SEO Toolkit add-on, an AI Visibility add-on, a Brand Performance entry plan, and Enterprise AIO. Whether these are distinct products, tiers, or naming variations is unconfirmed [153].

Engine coverage is inconsistent across Semrush's own documentation and across independent reviews. Coverage of Claude, Grok, DeepSeek, and Kimi was not verified in the official sources checked [155]. One platform's official-site retrieval failed entirely, producing an uncertain fit rating based on absence of retrieved evidence rather than evidence of absence [154].

Pricing conflicts remain open: additional users are listed at $99 per subuser in one source and from $45 per month in another [157]. Prompt database figures range from 26 million to 317 million across sources [159]. Sample size and run-count methodology behind the AI Visibility Score are not disclosed [161].

No independent validation of metric accuracy or model-by-model completeness was found in the cited sources. Semrush states its AI visibility metrics are directional because AI answers are dynamic and personalized [155]. Independent testing found the same prompt returns a different response about 70% of the time [163].

The Adobe acquisition of Semrush completed April 28, 2026, at approximately $1.9 billion, with Semrush operating as a wholly owned Adobe subsidiary within the Customer Experience Orchestration business and Bill Wagner remaining CEO [164]. No public announcements indicate whether this will alter the AI visibility product roadmap, pricing, or bundling [166].

Sources

Company-Owned Sources

Independent Sources

  • Semrush vs Ahrefs: Which Platform Is Actually Right for AI Visibility in 2026: https://athenahq.ai/blog/semrush-vs-ahrefs-which-platform-is-actually-right-for-ai-visibility-in-2026
  • Best AI Visibility Tools for 2026: Top 5 Platforms: https://checkthat.ai/answers/what-are-the-best-ai-visibility-tool-options
  • Semrush AI Visibility Toolkit Review 2026: Price and Fit: https://echowi.ai/blog/semrush-ai-visibility-toolkit-review/
  • Semrush AI Visibility Toolkit Pricing (2026): Real Cost: https://geotally.ai/blog/semrush-ai-visibility-toolkit-pricing
  • Semrush Review: Is the AI Visibility Toolkit Enough? (2026: https://getmint.ai/resources/semrush-review
  • Semrush AI Visibility Toolkit Review (2026): Pricing: https://meev.ai/reviews/semrush-ai-visibility-toolkit
  • Top 10 AI Visibility Tools for Optimization in 2026: https://nogood.io/blog/top-ai-visibility-tools-for-optimization
  • Semrush AI Visibility Toolkit Review (2026): Pricing and Limits | Sightivo: https://sightivo.com/blog/semrush-ai-visibility-toolkit-review
  • Semrush Review (2026) - AI Visibility Toolkit, Pricing, and: https://trakkr.ai/reviews/semrush-review
  • Semrush AI Visibility Toolkit Review: Should You Use It? - 01net: https://www.01net.com/en/seo/tools/semrush/ai-visibility-toolkit/
  • Semrush Pricing 2026: New Plans & Cost Breakdown: https://www.demandsage.com/semrush-pricing/
  • Semrush AI Visibility Toolkit Review (2026) — Honeyb Blog: https://www.honeyb.ai/blog/semrush-ai-visibility-toolkit-review
  • The Best AI Visibility Tracking Tools (My Honest Reviews: https://www.position.digital/blog/best-ai-visibility-tracking-tools/
  • Semrush One vs GEO Metrics: Which Is Better for AI Visibility in 2026?: https://www.trygeometrics.com/blog/semrush-one-vs-geo-metrics
  • Semrush AI Visibility Toolkit review: what it gets right (and wrong: https://www.tryprofound.com/blog/semrush-ai-visibility-toolkit-review
  • Additional AI research evidence166 records
    1. AI research evidence record openai:c1
    2. AI research evidence record openai:c2
    3. AI research evidence record anthropic:26-4
    4. AI research evidence record anthropic:9-4
    5. AI research evidence record anthropic:9-5
    6. AI research evidence record anthropic:9-6
    7. AI research evidence record openai:c4
    8. AI research evidence record anthropic:32-15
    9. AI research evidence record anthropic:5-3
    10. AI research evidence record anthropic:39-4
    11. AI research evidence record anthropic:5-12
    12. AI research evidence record anthropic:39-5
    13. AI research evidence record openai:c1
    14. AI research evidence record grok:7
    15. AI research evidence record perplexity:c1
    16. AI research evidence record anthropic:5-4
    17. AI research evidence record google:1.3.1
    18. AI research evidence record openai:c2
    19. AI research evidence record google:1.1.1
    20. AI research evidence record anthropic:25-13
    21. AI research evidence record anthropic:25-14
    22. AI research evidence record openai:c5
    23. AI research evidence record anthropic:19-5
    24. AI research evidence record anthropic:19-6
    25. AI research evidence record openai:c3
    26. AI research evidence record deepseek:c1
    27. AI research evidence record kimi:search_failure_semrush
    28. AI research evidence record perplexity:c4
    29. AI research evidence record perplexity:c5
    30. AI research evidence record openai:c3
    31. AI research evidence record anthropic:19-5
    32. AI research evidence record anthropic:19-6
    33. AI research evidence record anthropic:37-1
    34. AI research evidence record anthropic:9-6
    35. AI research evidence record anthropic:23-1
    36. AI research evidence record anthropic:30-6
    37. AI research evidence record anthropic:30-7
    38. AI research evidence record anthropic:5-12
    39. AI research evidence record anthropic:39-5
    40. AI research evidence record openai:c4
    41. AI research evidence record google:1.4.2
    42. AI research evidence record google:1.4.3
    43. AI research evidence record anthropic:5-4
    44. AI research evidence record anthropic:39-7
    45. AI research evidence record anthropic:44-2
    46. AI research evidence record anthropic:44-15
    47. AI research evidence record anthropic:40-2
    48. AI research evidence record anthropic:41-1
    49. AI research evidence record anthropic:40-29
    50. AI research evidence record anthropic:40-30
    51. AI research evidence record anthropic:4-7
    52. AI research evidence record anthropic:4-9
    53. AI research evidence record anthropic:5-3
    54. AI research evidence record anthropic:32-15
    55. AI research evidence record google:1.1.3
    56. AI research evidence record kimi:search_failure_semrush
    57. AI research evidence record openai:c2
    58. AI research evidence record openai:c3
    59. AI research evidence record openai:c1
    60. AI research evidence record anthropic:5-4
    61. AI research evidence record anthropic:19-5
    62. AI research evidence record anthropic:19-6
    63. AI research evidence record openai:c4
    64. AI research evidence record google:1.3.5
    65. AI research evidence record anthropic:33-13
    66. AI research evidence record anthropic:33-15
    67. AI research evidence record anthropic:39-3
    68. AI research evidence record perplexity:c5
    69. AI research evidence record openai:c5
    70. AI research evidence record anthropic:44-18
    71. AI research evidence record anthropic:44-19
    72. AI research evidence record anthropic:44-20
    73. AI research evidence record anthropic:37-5
    74. AI research evidence record anthropic:7-12
    75. AI research evidence record anthropic:5-12
    76. AI research evidence record anthropic:23-9
    77. AI research evidence record anthropic:23-10
    78. AI research evidence record openai:c1
    79. AI research evidence record anthropic:16-10
    80. AI research evidence record perplexity:c2
    81. AI research evidence record anthropic:5-4
    82. AI research evidence record anthropic:16-9
    83. AI research evidence record anthropic:15-2
    84. AI research evidence record grok:7
    85. AI research evidence record perplexity:c1
    86. AI research evidence record perplexity:c3
    87. AI research evidence record perplexity:c10
    88. AI research evidence record perplexity:c11
    89. AI research evidence record anthropic:39-2
    90. AI research evidence record google:1.3.3
    91. AI research evidence record anthropic:39-2
    92. AI research evidence record anthropic:9-6
    93. AI research evidence record deepseek:c2
    94. AI research evidence record anthropic:23-1
    95. AI research evidence record anthropic:30-6
    96. AI research evidence record anthropic:30-7
    97. AI research evidence record anthropic:5-12
    98. AI research evidence record anthropic:39-5
    99. AI research evidence record anthropic:33-14
    100. AI research evidence record anthropic:5-4
    101. AI research evidence record anthropic:39-7
    102. AI research evidence record anthropic:44-2
    103. AI research evidence record anthropic:44-15
    104. AI research evidence record anthropic:44-5
    105. AI research evidence record anthropic:44-6
    106. AI research evidence record anthropic:44-7
    107. AI research evidence record anthropic:44-8
    108. AI research evidence record anthropic:44-9
    109. AI research evidence record anthropic:39-2
    110. AI research evidence record anthropic:33-15
    111. AI research evidence record anthropic:39-3
    112. AI research evidence record anthropic:5-4
    113. AI research evidence record kimi:rankscale_engines
    114. AI research evidence record kimi:viali_method
    115. AI research evidence record kimi:viali_verbatim
    116. AI research evidence record kimi:sevisible_method
    117. AI research evidence record kimi:bevisible_evidence
    118. AI research evidence record kimi:ceyo_engines
    119. AI research evidence record kimi:bevisible_method
    120. AI research evidence record anthropic:33-13
    121. AI research evidence record anthropic:33-15
    122. AI research evidence record anthropic:39-3
    123. AI research evidence record anthropic:44-18
    124. AI research evidence record anthropic:44-19
    125. AI research evidence record anthropic:44-20
    126. AI research evidence record openai:c4
    127. AI research evidence record perplexity:c7
    128. AI research evidence record anthropic:40-29
    129. AI research evidence record anthropic:4-7
    130. AI research evidence record anthropic:40-30
    131. AI research evidence record openai:c1
    132. AI research evidence record openai:c2
    133. AI research evidence record openai:c3
    134. AI research evidence record anthropic:7-12
    135. AI research evidence record anthropic:5-12
    136. AI research evidence record perplexity:c2
    137. AI research evidence record deepseek:c1
    138. AI research evidence record deepseek:c2
    139. AI research evidence record google:1.3.5
    140. AI research evidence record anthropic:42-4
    141. AI research evidence record anthropic:9-4
    142. AI research evidence record anthropic:9-5
    143. AI research evidence record anthropic:9-6
    144. AI research evidence record openai:c3
    145. AI research evidence record openai:c4
    146. AI research evidence record anthropic:5-4
    147. AI research evidence record anthropic:39-7
    148. AI research evidence record anthropic:44-2
    149. AI research evidence record anthropic:44-15
    150. AI research evidence record anthropic:4-9
    151. AI research evidence record anthropic:40-30
    152. AI research evidence record anthropic:39-2
    153. AI research evidence record deepseek:c1
    154. AI research evidence record kimi:search_failure_semrush
    155. AI research evidence record openai:c4
    156. AI research evidence record perplexity:c7
    157. AI research evidence record openai:c1
    158. AI research evidence record perplexity:c2
    159. AI research evidence record google:1.1.3
    160. AI research evidence record anthropic:5-3
    161. AI research evidence record anthropic:40-29
    162. AI research evidence record anthropic:40-30
    163. AI research evidence record anthropic:4-7
    164. AI research evidence record anthropic:5-5
    165. AI research evidence record anthropic:39-14
    166. AI research evidence record anthropic:39-15

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Study date
September 19, 2026
Platforms analyzed
7
Source records
49
Ranking mentions
4 of 7
Platform share
57%
Final consensus rank
#2

Research trail and source mix

Configured platforms

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

Source mix

20 independent · 29 company-owned

Evidence support

42 direct · 6 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 d1368970707caef906650fa28658a6f2367c97f699c1eeed5fd2cd5c02f1b3be