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Peec AI AI Citation Solution Fit Review for Digital PR and Earned Media Strategy

Peec AI is a good fit for the citation-intelligence and measurement half of AI Citation Solutions for Digital PR and Earned Media Strategy, but it is not a complete earned-media solution.

Research: 2026-09-177 usable platform responsesRead the methodology ↗

Answer Capsule

Peec AI is a good fit for the citation-intelligence and measurement half of AI Citation Solutions for Digital PR and Earned Media Strategy, but it is not a complete earned-media solution. Four of the seven platforms in this study named Peec AI during the ranking stage (openai, anthropic, deepseek, perplexity), a 57.1% share of included platform responses, at an average listed rank of 6.25 and a best rank of 4. The strongest reason to consider it is citation-versus-mention tracking with domain- and URL-level source analytics across major AI platforms [1]. The main limitation is that Peec AI diagnoses visibility rather than executing digital PR, outreach, or content, and it does not publicly establish causal attribution from one earned placement to one later AI citation [3].

Research Snapshot

FieldValue
Platform mentions in ranking stage4 of 7 platforms (openai, anthropic, deepseek, perplexity)
Share of included platform responses57.1%
Average listed rank6.25
Best listed rank4
Relevant product/model/planPeec AI brand AI-search visibility platform; Pro or Advanced brand plans; Enterprise for larger PR programs
Overall use-case fitGood for citation intelligence and measurement; incomplete as a standalone digital-PR system
Research date2026-09-17

Why Peec AI Qualified for This Study

Questions This Section Answers

  • Is Peec AI a good choice for AI Citation Solutions for Digital PR and Earned Media Strategy?
  • How many AI platforms named Peec AI in the ranking stage for this digital PR use case?

Peec AI qualified because it was named by four of the seven platforms during ranking discovery, and because its documented capabilities overlap directly with the citation-intelligence criteria this study set out to evaluate. The platform tracks citations separately from brand mentions, including cases where an AI platform cites a domain without naming the brand [5]. Its pricing materials describe prompt and model tracking, competitor analysis, visibility metrics, source analytics, and domain- and URL-level detail views [6].

Independent reviews add citation gap analysis, influential-source identification, competitor benchmarking, sentiment tracking, and API or Looker Studio capabilities on higher tiers [7]. Peec AI also describes visibility impact, lift analysis, visibility-lift prediction, and a recently introduced AI-referral capability [8].

The qualification is not unanimous. DeepSeek and Kimi both rated fit as uncertain, citing thin independently verifiable detail on citation architecture mapping, publisher influence, and earned-coverage-to-citation measurement [9]. Perplexity rated the fit mixed and flagged inconsistent public pricing [11]. Those disagreements are covered in later sections.

The Product, Model, Plan, or Service Most Relevant to AI Citation Solutions for Digital PR and Earned Media Strategy

Questions This Section Answers

  • Which Peec AI plan should a buyer choose for tracking whether earned coverage appears in AI citations?
  • Does Peec AI's Earned Media module manage outreach, or does it only identify citation opportunities?

The relevant offering is the Peec AI brand AI-search visibility platform, most often referenced as the Pro or Advanced brand plan, with Enterprise positioned for larger PR programs [13]. Platforms named the product in slightly different terms — "AI visibility platform," "Citation Tracking Platform," and "brand visibility in AI chat platforms" — and those product names are not independently confirmed [15].

For this use case, the most directly relevant capability is citation tracking at the domain and URL level, which lets a PR team see which publishers and pages AI answers draw from [13]. Peec AI classifies sources into types such as editorial, corporate, and user-generated content including Reddit [17]. It also operates an Earned Media module that tracks opportunities from external sources and shows which are shaping ChatGPT answers [18].

That module's scope is a documented uncertainty. Peec AI positions Earned Media as a tracking feature identifying sources already shaping AI answers; it is unclear whether the module actively manages outreach, tracks pitch-to-citation velocity, or integrates with PR platforms [18]. Buyers should treat it as a monitoring layer, not a media-relations system.

What the AI Platforms Agreed About

Questions This Section Answers

  • What do AI platforms agree Peec AI does well for digital PR and earned media measurement?
  • Does Peec AI track citations separately from brand mentions across major AI platforms?

Agreement was strongest on three points: citation-versus-mention tracking, source-level analysis, and multi-platform coverage.

On citation intelligence, Peec AI states it tracks citations separately from mentions and can show citation performance for prompts across major AI channels [19]. Independent reviews describe citation-source reports showing that a brand's own site is only 2 to 6 percent of what AI engines cite, which is the kind of finding that redirects earned-media strategy toward third-party publishers [20].

On source analysis, platforms agreed that Peec AI surfaces which domains and URLs are cited for tracked prompts, ranked by citation count [21]. Grok's research describes tracking of "used" sources (content that informed an answer) and "cited" sources (URLs explicitly named) at domain and URL level with frequency, plus source classification [22].

On platform coverage, independent reviews report six engines included by default: ChatGPT, Gemini, Claude, Perplexity, Google AI Mode, and Microsoft Copilot [24]. One review notes Starter, Pro, and Advanced plans let buyers choose three engines from that set [26]. Google's research describes daily tracking across ChatGPT, Gemini, Perplexity, and Copilot with exact citation URLs [27].

Competitor benchmarking drew broad agreement as well. Peec AI lists competitor benchmarking, visibility, position, sentiment, share-of-voice, and source analytics [28]. Independent reviews describe an Add Brands feature for ranking against competitors on the same prompts [29].

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Is Peec AI's citation architecture mapping capability verified, or is it still unclear from public evidence?
  • How much do AI platforms disagree about Peec AI's pricing and earned-media attribution depth?

Fit ratings diverged sharply. Google and Grok rated Peec AI a strong fit [30]. OpenAI and Anthropic rated it good [32]. Perplexity rated it mixed [34]. DeepSeek and Kimi rated it uncertain [35].

The deepest disagreement concerns citation architecture mapping. OpenAI's research treats domain- and URL-level detail views as an advantage but notes the depth of network visualization, historical source lineage, and exportable citation-architecture graphs is unclear [37]. DeepSeek found no reviewed source documenting a citation-architecture-mapping capability at all [35]. Perplexity found no clearly verified public evidence of citation-architecture mapping or publisher influence scoring [34]. Kimi reported that no searched source describes Peec AI's citation intelligence features, while competitors document theirs explicitly [38].

Pricing is the second conflict zone. Reported figures include approximately $95/$245/$495 per month for Starter/Pro/Advanced [37], €85/€205/€425 monthly or €70/€180/€360 annually [42], and $80-$95, $205-$245, $420-$495 depending on billing mode [43]. Peec AI's March 2026 pricing update states that pricing and tracking capacity changed and that plans are subject to ongoing commercial updates [44].

Attribution depth is the third uncertainty. Peec AI describes AI-referral and lift-analysis features [45], and Google's research describes an AI Referrals integration with GA4 tracking sessions, conversions, and revenue [46]. But independent reviewers state Peec AI does not offer built-in end-to-end AI referral attribution and is a monitoring tool rather than a traffic or ROI attribution platform [48]. One review notes Peec AI does not estimate actual AI-referred traffic or provide conversion attribution [50]. Independent evidence validating causal earned-media attribution was not located [45].

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • Does Peec AI identify influential publishers and competitor citation sources for earned media planning?
  • Can Peec AI measure whether a specific earned-media placement later appears in AI citations?

Peec AI's capabilities map unevenly onto the five criteria in this use case.

Citation intelligence — advantage. Citation rate is tracked separately from mention rate, including cases where an AI platform cites a domain without naming the brand [51]. This is the capability most consistently supported across platforms.

Citation architecture mapping — advantage with caveats. Source analytics with domain- and URL-level detail views support source and citation mapping, but the depth of network visualization, historical source lineage, and exportable citation-architecture graphs is unclear [52]. DeepSeek and Perplexity found this capability unverified in public sources [53].

Competitor source analysis — advantage. Peec AI lists competitor benchmarking, visibility, position, sentiment, share-of-voice, competitor insights, and source analytics [52]. Grok's research describes gap analysis identifying sources that name competitors but not the buyer [56]. The precise competitor-source comparison workflow is not fully documented publicly [52].

Influential publisher identification — neutral. Domain and URL detail views, source visibility, and citation-rate reporting can help identify publishers appearing in AI answers, but public materials do not establish that Peec AI independently scores publisher authority, editorial influence, or earned-media quality beyond observed AI retrieval behavior [52]. Grok's research describes surfacing frequently cited domains and recommending digital PR actions for editorial sources [57].

Earned-coverage-to-citation measurement — neutral. Visibility-impact and lift-analysis capabilities plus AI-referral measurement can support before-and-after monitoring around earned coverage, but public evidence does not prove deterministic attribution that a specific placement caused a specific later citation [52]. Peec AI's own guidance frames success as new sources appearing in its source lists [59].

Two operational capabilities matter for PR workflows. Reporting runs through CSV exports, a Looker Studio connector, an API on higher tiers, and a Model Context Protocol integration [60]. Sentiment analysis classifies brand mentions as positive, neutral, or negative, and hallucination alerts address a concern that raw citation tracking misses [61].

The clearest limitation is the monitoring-to-execution gap. Multiple independent reviews state Peec AI surfaces citation data and competitive insights but has no built-in content creation tools, optimization workflows, or automated agents [63]. One review puts it plainly: Peec AI stops at diagnosis [65]. Another notes it tracks mentions but does not write content, build authority signals, or implement technical optimizations [66].

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does Peec AI cost per month, and are there setup or cancellation fees?
  • What do extra AI models add to a Peec AI plan, and does annual billing reduce the cost?

Public pricing is usage-based, tied primarily to tracked prompts and analyzed models [67]. The official pricing page displays Starter and Pro brand tiers and directs buyers to sales for additional details [67]. Reported figures conflict across sources and should be treated as current-price claims requiring confirmation.

PlanReported monthly priceReported promptsReported models
Starter~$95/month503
Pro~$245/month1503
Advanced~$495/month3503
EnterpriseCustomNot statedNot stated

Sources: [67]. European pricing is reported separately at €85/€205/€425 monthly, dropping to €70/€180/€360 on annual billing [71]. Perplexity's research reports $80-$95, $205-$245, and $420-$495 depending on billing mode [72].

Additional costs are documented. Extra models are add-ons reported at +$30/month on Starter, +$70/month on Pro, and +$140/month on Advanced per additional model [73]. Google's research reports different add-on figures: $35/month on Starter, $85/month on Pro, and $165/month on Advanced [74]. Annual billing is reported as offering a 15% discount [67]. All paid plans reportedly include unlimited seats [75].

Contract terms are the weakest-documented area. Public pages reviewed do not clearly state minimum contract duration, cancellation notice, refunds, data-retention terms, or overage treatment [67]. Monthly and annual billing are described, but precise cancellation mechanics should be verified [67]. A 7-day free trial is reported [76]. Peec AI's March 2026 pricing update confirms plans are subject to ongoing commercial updates [77].

Best Suited For

Questions This Section Answers

  • Who gets the most value from Peec AI for digital PR and earned media strategy?
  • Is Peec AI worth it for agencies managing AI visibility across multiple client brands?

Peec AI fits PR, SEO, and communications teams that need recurring AI-answer visibility and citation monitoring [78]. The strongest fit is a team mapping which publishers, domains, and URLs influence AI answers for tracked prompts [79].

Agencies and multi-brand teams are a documented fit. Peec AI's agency page describes citation-rate tracking for agency workflows [78], and agency plans are separately listed on the official site [80]. Focus areas agencies use Peec AI for include digital PR and outreach [81]. Unlimited seats on paid plans support multi-client reporting [82].

Organizations testing whether newly published coverage later appears in monitored AI answers are also a fit, because prompt-based daily tracking enables pre/post monitoring around PR campaigns [79]. B2B and SaaS companies benchmarking competitor source authority and citation patterns round out the core audience [84].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose Peec AI for AI Citation Solutions for Digital PR and Earned Media Strategy?
  • Is Peec AI a poor fit for buyers who need journalist outreach or media database tools?

Buyers seeking a full media-database, journalist-outreach, digital-PR distribution, or campaign-management platform should look elsewhere [85]. Peec AI is not demonstrated publicly as a media-relations, journalist-outreach, earned-media distribution, or newsroom-management platform [85].

Buyers requiring guaranteed causal attribution between one earned-media placement and a later AI citation will not find it here. Specific causal attribution from one earned article to one later AI citation is not publicly established [86]. Companies requiring pipeline attribution will find the lack of CRM integration and traffic tracking limiting [87].

Programs centered on sources inaccessible to AI crawlers are a poor fit. Public product documentation states that AI models may not see pages behind paywalls or dependent on JavaScript, which can undercount premium publisher coverage or interactive media pages [88].

Enterprise buyers with specific governance requirements should verify carefully. One independent review states Peec AI lacks SOC 2 certification and has no dedicated implementation or AI strategist support [89]. That claim comes from a competing vendor's comparison page and should be confirmed directly with Peec AI.

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to Peec AI for a buyer who needs end-to-end earned media execution?
  • When should a buyer choose a PR agency or execution platform instead of Peec AI?

Choose a dedicated digital-PR or media-intelligence platform when the primary need is journalist discovery, outreach, monitoring of conventional media, campaign execution, or earned-media distribution [90]. Teams needing end-to-end earned media execution plus citation visibility in one platform may consider Profound, Muck Rack, or a combined agency-plus-Peec AI stack [91].

Choose an execution-focused platform when the buyer needs content creation, optimization, and briefing to close citation gaps. Independent reviews name Scalenut, Profound, Writesonic, and AirOps as carrying more of that work into content, outreach, technical changes, or managed workflows [92]. One review notes Writesonic, Profound, and AirOps carry more of that work than Peec AI does [92].

Choose a more enterprise-oriented AI-visibility platform when the buyer requires contractual SLAs, broader governance, mature attribution, or deeply customized publisher and citation taxonomies [90]. Organizations wanting a unified SEO plus AI visibility platform may prefer SE Ranking or Semrush to reduce tool sprawl [92].

Kimi's research names additional alternatives with documented earned-media measurement: Cite Solutions, GetCited, Citingly, and Connective3 [94]. Those are vendor-owned claims from competing providers and were not independently verified in this study.

Questions to Verify Before Buying

Questions This Section Answers

  • What should a buyer confirm with Peec AI before signing a contract?
  • Which capabilities should a buyer test in a Peec AI pilot before committing budget?

The following questions come from the platform research and should be resolved before purchase.

Coverage and scope. Which exact AI platforms, models, countries, languages, and prompt volumes are included in the selected Pro, Advanced, or Enterprise plan as of the purchase date [98]? How are paywalled, JavaScript-rendered, robots-blocked, syndicated, updated, or removed publisher pages handled [99]? Are private or enterprise LLM deployments visible to Peec AI, and what is the scope of that blind spot [100]?

Data and exports. Can the platform export every cited domain, URL, citation position, timestamp, prompt, model, and competitor relationship for historical analysis [98]? Does source analytics identify publisher names, canonical URLs, duplicate syndication, and publication dates reliably [98]? Can Peec AI ingest a list of earned-media URLs and report whether each later appears as an AI citation or recommendation source [98]?

Attribution methodology. What lift-analysis methodology is used, and what evidence supports causal attribution versus correlation [101]? Does the Earned Media module actively manage outreach or only identify opportunities [102]? What is the turnaround time from earned coverage to detection in citation trends [103]?

Commercial terms. What are the monthly and annual prices, model add-on fees, prompt overage rules, minimum term, cancellation notice, refund policy, and data-retention period [98]? Are API access, SSO, Looker Studio or other integrations, automated reporting, and multi-country tracking included in the selected plan or charged separately [98]?

Vendor and compliance. What service-level commitments, support response times, security documentation, and data-processing terms apply to a US enterprise buyer [98]? Does Peec AI hold SOC 2 certification, and what implementation or strategy support is included [105]? Can the vendor provide a current sample report showing citation architecture, influential-source analysis, and an earned-coverage pre/post case using comparable AI platforms [98]?

Identity confirmation. The supplied normalization context says official-site retrieval failed for one or more mentions and that exact-name identity matching remains unverified; confirm that the contracted entity is the intended Peec AI service [106].

Final AI Consensus Verdict

Peec AI is a good fit for the citation-intelligence and measurement portion of AI Citation Solutions for Digital PR and Earned Media Strategy, and an incomplete fit for the full use case. Four of seven platforms named it during ranking discovery, and the strongest buying case is a PR or communications team pairing Peec AI with media intelligence, campaign records, and web analytics [107].

The consensus is not uniform. Google and Grok rated the fit strong [109]; OpenAI and Anthropic rated it good [107]; Perplexity rated it mixed [112]; DeepSeek and Kimi rated it uncertain [113]. Platform agreement here reflects overlapping public evidence, not proof of product quality.

The recurring limitation across every platform is the same: Peec AI diagnoses visibility but does not execute digital PR, create content, manage outreach, or provide defensible causal attribution [115]. Buyers with in-house execution capacity will extract more value than buyers expecting an end-to-end earned-media system. Verify current plan coverage, source exports, attribution methodology, and commercial terms before purchase [108].

How This Review Was Produced

This review synthesizes fit-research responses from seven AI platforms, each evaluating Peec AI against the same use case: AI Citation Solutions for Digital PR and Earned Media Strategy. The study date is 2026-09-17. Platform mentions in the ranking stage count only platforms that named Peec AI during ranking discovery; all included platforms evaluated fit regardless of whether they named the entity.

Each platform supplied citations to company-owned pages, independent reviews, directories, and journalism. Company-owned evidence is labeled as such; independent evidence is labeled separately. No personal testing, customer interviews, or hands-on product evaluation was performed. No affiliate relationship is disclosed in the supplied inputs.

Methodology Limitations

Platform-reported research dates differ from the authoritative run date. DeepSeek's research is dated 2026-06-01, while the remaining platforms are dated 2026-09-17. Platform-reported dates are provenance metadata and do not independently prove freshness [118].

Official-site retrieval failed for one or more mentions. The Peec AI homepage returned an unavailable status with the failure reason "HTML exceeded 1000000 bytes," and no failed fetch was used as a verified domain key [119]. Identity used exact-name fallback, and the matching reported domain remains unverified.

The supplied URLs were collected from platform responses and were not independently validated by the writer stage. Citations are platform-reported evidence, not independently verified facts. DeepSeek's research ran with search disabled, so its claims rest on model knowledge rather than retrieved sources [118].

Pricing conflicts were not resolved. Reported figures vary by currency, billing mode, and source, and Peec AI's own March 2026 update confirms plans are subject to ongoing commercial updates [120]. Product names also vary across platforms and are not independently confirmed [119].

Several claims in this review come from competing vendors' comparison pages, including the SOC 2 and implementation-support claims [121] and the alternative-vendor capability claims [122]. Those should be treated as vendor-reported rather than independently established.

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

Sources

Company-Owned Sources

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    30. AI research evidence record google:1.1.3
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    34. AI research evidence record perplexity:c1
    35. AI research evidence record deepseek:c1
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    46. AI research evidence record google:2.2.1
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    51. AI research evidence record openai:c1
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    53. AI research evidence record deepseek:c1
    54. AI research evidence record perplexity:c1
    55. AI research evidence record openai:c3
    56. AI research evidence record grok:web:7
    57. AI research evidence record grok:web:0
    58. AI research evidence record openai:c4
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    60. AI research evidence record anthropic:11-7
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    69. AI research evidence record google:2.1.9
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    71. AI research evidence record anthropic:11-2
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    73. AI research evidence record anthropic:14-2
    74. AI research evidence record google:2.1.8
    75. AI research evidence record anthropic:16-1
    76. AI research evidence record anthropic:14-1
    77. AI research evidence record openai:c6
    78. AI research evidence record openai:c1
    79. AI research evidence record openai:c2
    80. AI research evidence record perplexity:c2
    81. AI research evidence record anthropic:28-4
    82. AI research evidence record anthropic:16-1
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    84. AI research evidence record anthropic:33-6
    85. AI research evidence record openai:c1
    86. AI research evidence record openai:c4
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    88. AI research evidence record openai:c5
    89. AI research evidence record anthropic:41-9
    90. AI research evidence record openai:c1
    91. AI research evidence record anthropic:41-2
    92. AI research evidence record anthropic:29-3
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    97. AI research evidence record kimi:connective3_bcs
    98. AI research evidence record openai:c2
    99. AI research evidence record openai:c5
    100. AI research evidence record anthropic:27-3
    101. AI research evidence record openai:c4
    102. AI research evidence record anthropic:20-4
    103. AI research evidence record anthropic:31-1
    104. AI research evidence record anthropic:11-7
    105. AI research evidence record anthropic:41-9
    106. AI research evidence record kimi:ranking_stage_normalization
    107. AI research evidence record openai:c1
    108. AI research evidence record openai:c2
    109. AI research evidence record google:1.1.3
    110. AI research evidence record grok:web:0
    111. AI research evidence record anthropic:1-10
    112. AI research evidence record perplexity:c1
    113. AI research evidence record deepseek:c1
    114. AI research evidence record kimi:ranking_stage_normalization
    115. AI research evidence record anthropic:39-6
    116. AI research evidence record anthropic:41-2
    117. AI research evidence record openai:c4
    118. AI research evidence record deepseek:c1
    119. AI research evidence record kimi:ranking_stage_normalization
    120. AI research evidence record openai:c6
    121. AI research evidence record anthropic:41-9
    122. AI research evidence record kimi:cite_solutions_pr
    123. AI research evidence record kimi:getcited_pricing
    124. AI research evidence record kimi:citingly_features
    125. AI research evidence record kimi:connective3_bcs

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  • Peec AI Reviews 2026: Details, Pricing, & Features | G2: https://www.g2.com/products/peec-ai/reviews
  • Peec AI Review & Pricing 2026: Clean Reporting, Nothing: https://www.get-ryze.ai/blog/peec-ai-review-pricing-2026
  • Peec AI Review 2026: Is It The Right GEO Tool For Your Brand?: https://www.scalenut.com/blogs/peec-ai-review
  • AI visibility tools coverage (third-party: https://www.searchenginejournal.com/
  • Profound vs. Peec AI: Which AEO platform is right for your brand?: https://www.tryprofound.com/articles/profound-vs-peec-ai
  • Peec AI Review: Is the Features & Price Worth It in 2026?: https://www.workduo.ai/blog/peec-ai-review
  • AI visibility Tools Review : Peec AI v/s Developer Marketing Hub: https://www.youtube.com/watch?v=1EIZC_UQfrE
  • Peec.ai Review & Tutorial 2026 — Full Beginner's Guide: https://www.youtube.com/watch?v=1O0U0oemB84
  • New in Peec AI: Brand Perception: https://www.youtube.com/watch?v=AKzS5yeQolQ
  • Additional AI research evidence125 records
    1. AI research evidence record openai:c1
    2. AI research evidence record openai:c2
    3. AI research evidence record anthropic:39-6
    4. AI research evidence record anthropic:41-2
    5. AI research evidence record openai:c1
    6. AI research evidence record openai:c2
    7. AI research evidence record openai:c3
    8. AI research evidence record openai:c4
    9. AI research evidence record deepseek:c1
    10. AI research evidence record kimi:ranking_stage_normalization
    11. AI research evidence record perplexity:c1
    12. AI research evidence record perplexity:c9
    13. AI research evidence record openai:c2
    14. AI research evidence record anthropic:16-1
    15. AI research evidence record kimi:ranking_stage_normalization
    16. AI research evidence record anthropic:1-10
    17. AI research evidence record anthropic:11-4
    18. AI research evidence record anthropic:20-4
    19. AI research evidence record openai:c1
    20. AI research evidence record anthropic:16-10
    21. AI research evidence record anthropic:1-10
    22. AI research evidence record grok:web:0
    23. AI research evidence record grok:web:7
    24. AI research evidence record anthropic:16-3
    25. AI research evidence record anthropic:16-8
    26. AI research evidence record anthropic:27-14
    27. AI research evidence record google:1.1.3
    28. AI research evidence record openai:c2
    29. AI research evidence record anthropic:33-6
    30. AI research evidence record google:1.1.3
    31. AI research evidence record grok:web:0
    32. AI research evidence record openai:c1
    33. AI research evidence record anthropic:1-10
    34. AI research evidence record perplexity:c1
    35. AI research evidence record deepseek:c1
    36. AI research evidence record kimi:ranking_stage_normalization
    37. AI research evidence record openai:c2
    38. AI research evidence record kimi:cite_solutions_aiseo
    39. AI research evidence record kimi:citingly_features
    40. AI research evidence record anthropic:10-8
    41. AI research evidence record google:2.1.9
    42. AI research evidence record anthropic:11-2
    43. AI research evidence record perplexity:c9
    44. AI research evidence record openai:c6
    45. AI research evidence record openai:c4
    46. AI research evidence record google:2.2.1
    47. AI research evidence record google:2.2.4
    48. AI research evidence record anthropic:27-3
    49. AI research evidence record anthropic:27-4
    50. AI research evidence record anthropic:43-20
    51. AI research evidence record openai:c1
    52. AI research evidence record openai:c2
    53. AI research evidence record deepseek:c1
    54. AI research evidence record perplexity:c1
    55. AI research evidence record openai:c3
    56. AI research evidence record grok:web:7
    57. AI research evidence record grok:web:0
    58. AI research evidence record openai:c4
    59. AI research evidence record anthropic:31-1
    60. AI research evidence record anthropic:11-7
    61. AI research evidence record anthropic:3-11
    62. AI research evidence record anthropic:43-11
    63. AI research evidence record anthropic:41-2
    64. AI research evidence record anthropic:41-5
    65. AI research evidence record anthropic:39-6
    66. AI research evidence record anthropic:39-7
    67. AI research evidence record openai:c2
    68. AI research evidence record anthropic:10-8
    69. AI research evidence record google:2.1.9
    70. AI research evidence record grok:web:6
    71. AI research evidence record anthropic:11-2
    72. AI research evidence record perplexity:c9
    73. AI research evidence record anthropic:14-2
    74. AI research evidence record google:2.1.8
    75. AI research evidence record anthropic:16-1
    76. AI research evidence record anthropic:14-1
    77. AI research evidence record openai:c6
    78. AI research evidence record openai:c1
    79. AI research evidence record openai:c2
    80. AI research evidence record perplexity:c2
    81. AI research evidence record anthropic:28-4
    82. AI research evidence record anthropic:16-1
    83. AI research evidence record anthropic:31-1
    84. AI research evidence record anthropic:33-6
    85. AI research evidence record openai:c1
    86. AI research evidence record openai:c4
    87. AI research evidence record anthropic:43-10
    88. AI research evidence record openai:c5
    89. AI research evidence record anthropic:41-9
    90. AI research evidence record openai:c1
    91. AI research evidence record anthropic:41-2
    92. AI research evidence record anthropic:29-3
    93. AI research evidence record anthropic:38-2
    94. AI research evidence record kimi:cite_solutions_pr
    95. AI research evidence record kimi:getcited_pricing
    96. AI research evidence record kimi:citingly_features
    97. AI research evidence record kimi:connective3_bcs
    98. AI research evidence record openai:c2
    99. AI research evidence record openai:c5
    100. AI research evidence record anthropic:27-3
    101. AI research evidence record openai:c4
    102. AI research evidence record anthropic:20-4
    103. AI research evidence record anthropic:31-1
    104. AI research evidence record anthropic:11-7
    105. AI research evidence record anthropic:41-9
    106. AI research evidence record kimi:ranking_stage_normalization
    107. AI research evidence record openai:c1
    108. AI research evidence record openai:c2
    109. AI research evidence record google:1.1.3
    110. AI research evidence record grok:web:0
    111. AI research evidence record anthropic:1-10
    112. AI research evidence record perplexity:c1
    113. AI research evidence record deepseek:c1
    114. AI research evidence record kimi:ranking_stage_normalization
    115. AI research evidence record anthropic:39-6
    116. AI research evidence record anthropic:41-2
    117. AI research evidence record openai:c4
    118. AI research evidence record deepseek:c1
    119. AI research evidence record kimi:ranking_stage_normalization
    120. AI research evidence record openai:c6
    121. AI research evidence record anthropic:41-9
    122. AI research evidence record kimi:cite_solutions_pr
    123. AI research evidence record kimi:getcited_pricing
    124. AI research evidence record kimi:citingly_features
    125. AI research evidence record kimi:connective3_bcs

Verify this research

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

Study date
September 17, 2026
Platforms analyzed
7
Source records
41
Ranking mentions
4 of 7
Platform share
57%
Final consensus rank
#3

Research trail and source mix

Configured platforms

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

Source mix

23 independent · 18 company-owned

Evidence support

34 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 0741dd36344031b6010ca89c34db82651922554de7d74a2785a20b713ded6d0e