One marketing need. Multiple leading AI platforms. One transparent consensus. How it works
AI MarketingConsensus Index

AI Consensus Fit Review

BeCited AI Search Audit Fit Review for B2B Companies

BeCited is a good fit for B2B marketing and revenue teams that want a fixed-price, analyst-led AI search audit built around buying-intent prompts.

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

Answer Capsule

BeCited is a good fit for B2B marketing and revenue teams that want a fixed-price, analyst-led AI search audit built around buying-intent prompts. Two of the seven platforms in this study named BeCited during the ranking stage — Grok (rank 3) and Kimi (rank 6) — giving it an average listed rank of 4.5 and a 28.6% share of included platform responses. The strongest reason to consider it is the Full Audit's direct alignment with the stated criteria: 100–300 buying-intent prompts across four AI engines, competitor benchmarking, source mapping, prompt-level gap analysis, and a prioritized 90-day plan. The main limitation is that nearly all evidence is company-published, with limited independent validation of methodology, outcomes, or B2B customer results.

Research Snapshot

FieldFinding
Platform mentions in ranking stage2 of 7 platforms (Grok, Kimi)
Share of included platform responses28.6%
Average listed rank4.5
Best listed rank3 (Grok)
Relevant product/model/planFull Audit
Overall use-case fitGood (five platforms rated good or strong; one uncertain)
Research date2026-09-18

Why BeCited Qualified for This Study

Questions This Section Answers

  • Is BeCited a good choice for AI Search Audits for B2B Companies?
  • How many AI platforms recommended BeCited for B2B AI search audits?

BeCited qualified because two independent platform rankings placed it among recommended audit providers for this exact use case, and because the Full Audit's published scope maps onto every criterion in the study prompt. Grok ranked BeCited third and described the Full Audit as an "exact match to evaluation criteria," citing recommendation analysis, competitor benchmarking, citation intelligence, gap analysis, and a 90-day strategy [1]. Kimi ranked it sixth and highlighted multi-engine coverage, persona-matched analysis, and citation platform mapping [2].

The remaining five platforms evaluated BeCited's fit without naming it in their ranking stage. OpenAI, Anthropic, Perplexity, and Google all rated the fit "good" or "strong" after reviewing the same public materials; DeepSeek rated it "uncertain" because its research pass could not retrieve the BeCited website and found no independent corroboration [3]. That split is itself a finding: the entity's fit case rests heavily on company-owned documentation, and one platform's inability to retrieve that documentation changed its verdict.

The Product, Model, Plan, or Service Most Relevant to AI Search Audits for B2B Companies

Questions This Section Answers

  • Which BeCited plan is most relevant for a B2B company that needs buying-journey prompt analysis?
  • Does the BeCited Full Audit cover competitor benchmarking and citation source mapping?

The Full Audit is the relevant offer. Every platform in this study identified it as the matching product, and it is the only BeCited tier that covers the full set of criteria in the study prompt.

According to company-published materials, the Full Audit tests 100–300 buying-intent prompts across ChatGPT, Gemini, Perplexity, and Claude, and reports a 0–100 visibility score with an engine-by-engine breakdown [4]. It is delivered in one week at a listed price of $2,000, and includes a 45-minute strategy session and a 90-day action plan [8]. A 30-day re-check is described in some platform summaries [6]; the public pricing page excerpt does not restate it, so treat that inclusion as platform-reported.

Two adjacent tiers exist. A Snapshot at $199 covers 10 buying-intent prompts on Perplexity with a 48-hour turnaround and credits toward a Full Audit within 30 days [11]. A Quarterly option at $1,500 per quarter re-runs the audit and adds delta reporting, trend tracking, and a 30-minute strategy call [4]. Relevance Engineering is a separate project-based service for implementation work such as schema, llms.txt, and content rewrites, with custom pricing [13].

What the AI Platforms Agreed About

Questions This Section Answers

  • What do AI platforms agree the BeCited Full Audit includes for B2B buying-journey visibility?
  • Is BeCited's audit methodology described consistently across AI platforms?

Agreement was strong on scope and positioning, and mixed on evidence quality.

Five platforms — OpenAI, Anthropic, Grok, Perplexity, and Google — converged on the same core description: a one-time, fixed-price, human-reviewed audit centered on buying-intent prompts rather than generic brand monitoring [15]. All five treated the $2,000 one-week Full Audit as the matching product, and all five credited the service with competitor benchmarking, source mapping, and a prioritized action plan.

Platforms also agreed that the manual analyst model is the differentiator. BeCited states that a named analyst reviews every answer by hand, and platforms repeated that claim as a stated advantage for brand disambiguation and misleading citations [20]. This is company-reported, not independently verified.

On methodology transparency, platforms noted that BeCited publishes a methodology page describing manual quote review, brand-variant matching, source tiering, a reported 95% confidence interval, and a reported blind-scoring agreement of approximately 72% with Cohen's kappa of 0.722 [20]. Platforms consistently labeled these as company-reported figures rather than audited results.

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Why did one AI platform rate BeCited's fit as uncertain for B2B AI search audits?
  • What do AI platforms disagree about regarding BeCited's site-readiness check count?

The clearest disagreement is the overall fit rating. Grok and Google rated the fit "strong" [23]. OpenAI, Anthropic, Perplexity, and Kimi rated it "good" [25]. DeepSeek rated it "uncertain," stating that the BeCited website was not retrievable during its research pass and that no independent review, pricing source, or B2B case study was located [29]. DeepSeek's research ran on 2026-02-06, months before the other platforms' 2026-09-18 passes, which may explain the retrieval failure.

A second conflict concerns the site-readiness check count. The BeCited homepage describes 19 checks, while the case-study page describes 15 [25]. Anthropic and Google both reported 19 [31]; Kimi described a "14-signal site-readiness grade" in the Snapshot tier [28]. The current Full Audit count is unresolved in the supplied evidence.

A third conflict concerns pricing presentation. Perplexity found third-party Capterra listings describing monthly plans and separate pricing tiers for "tobecited," which do not match the one-time $2,000 structure on the BeCited site [32]. Perplexity flagged this as package inconsistency in the broader market presentation rather than a confirmed BeCited price change.

Platforms also diverged on engine coverage as a limitation. Kimi and Anthropic both flagged the absence of Google AI Overviews and Microsoft Copilot as a gap versus competitors [28]. Google and Grok did not treat four-engine coverage as a disqualifying limitation.

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • Does the BeCited Full Audit map citation architecture at the page and URL level?
  • How does BeCited handle content-gap analysis for B2B buying-journey prompts?

BeCited's Full Audit covers all six criteria in the study prompt, but the depth of citation architecture mapping is the least clearly documented.

Recommendation analysis. Platforms agreed the audit tests 100–300 buying-intent prompts across four engines and reports a 0–100 visibility score with per-engine breakdown [34]. Google reported that BeCited explicitly distinguishes between a brand being "mentioned" and being actively "recommended," and analyzes that conversion gap [37].

Competitor benchmarking. The service is built around buyer-provided competitors and reports which competitors win or lose across tested prompts [34]. BeCited's methodology states competitor lists are narrowed to companies actually encountered in the audit [39]. Perplexity noted the full benchmark methodology is not fully disclosed [36].

Citation and source intelligence. The Full Audit includes a Source Influence Map of platforms AI cites for the category, with sources tiered by category-specific AI trust rather than general domain authority [34]. Google reported that the sample audit names directories such as G2 and Capterra as primary source tiers for SaaS [41].

Citation architecture mapping. This is the weakest-documented criterion. OpenAI rated it "neutral," noting that public materials do not clearly specify whether the audit maps a complete technical citation architecture across every page, URL, entity, and referring source [39]. Anthropic and Google both credited 19 site-readiness checks covering robots.txt, llms.txt, sitemap, structured data, meta tags, heading order, FAQ format, page speed, entity recognition, quotability, and agent-readiness [42]. BeCited's AI Search Guide lists robots.txt, llms.txt, JSON-LD schema, quotability, freshness, E-E-A-T, and entity readiness as graded factors [44].

Content-gap analysis. The Full Audit includes prompt-by-prompt gap analysis with root-cause explanations mapped to content, authority, or technical gaps [42]. Google reported that gaps are translated into revenue exposure through a Revenue at Risk Calculator with business-type models [45].

Prioritized buying-journey strategy. Deliverables include a prioritized 90-day action plan and a 45-minute strategy session, with actions ranked by impact and effort across listings, content, reviews, and community presence [34].

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does the BeCited Full Audit cost, and is there a cheaper entry option?
  • What are BeCited's refund, cancellation, and report-sharing terms for a B2B buyer?

Published pricing is unusually clear for this category, but contract mechanics are not.

TierPriceScopeTurnaround
Snapshot$199 one-time10 buying-intent prompts, Perplexity only; credits toward Full Audit within 30 days48 hours
Full Audit$2,000 one-time100–300 buying-intent prompts across four engines1 week
Quarterly$1,500 per quarterFull audit re-run, delta report, trend tracking, updated action plan, 30-minute strategy callOngoing

Sources: [47].

Contract terms are thinner. BeCited's terms state that pricing is as listed on the website or as agreed in writing, and that payment is due upon engagement unless otherwise agreed [51]. Dissatisfied customers are asked to contact BeCited within 14 days of delivery to discuss resolution; no specific refund policy is stated [52]. Reports are licensed for internal business use and may not be resold, redistributed, or publicly shared without written permission [52]. No minimum term or cancellation mechanics for the quarterly service are publicly specified [52].

Additional fees are not publicly specified. OpenAI noted that the site does not clearly state whether taxes, custom prompt expansion, implementation support, additional competitors, or extra audit runs incur fees [49]. Anthropic noted no disclosed fees for follow-up consulting or implementation support after report delivery [53]. Relevance Engineering is separately priced on a custom, project basis [54].

Best Suited For

Questions This Section Answers

  • Who gets the most value from a BeCited Full Audit for B2B vendor-discovery prompts?
  • Is BeCited a good fit for a B2B team that wants a one-time diagnostic instead of a monitoring subscription?

BeCited is best suited to mid-market B2B marketing and revenue teams that want a single, high-touch diagnostic before committing to ongoing monitoring. Platforms converged on three buyer profiles: teams evaluating visibility for vendor-discovery and comparison prompts [56]; teams that prefer analyst-reviewed recommendations over an automated dashboard [58]; and companies that need a one-time diagnostic plus a 90-day prioritization plan [56].

It also fits buyers who want a fixed, predictable price. The $2,000 one-time fee with no recurring subscription is simpler to budget than tiered SaaS pricing, and the $199 Snapshot credits toward the Full Audit within 30 days, which lowers the cost of evaluating the vendor first [58].

A fourth profile is B2B SaaS and professional-services companies targeting specific high-value buyer personas, where persona-matched analysis and source-tier mapping matter more than raw prompt volume [59].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose BeCited for AI Search Audits for B2B Companies?
  • Is BeCited suitable for an enterprise buyer that needs continuous monitoring and multi-user access?

BeCited is probably not the right choice for four buyer situations, and platforms were consistent on this.

First, teams needing continuous monitoring. The Full Audit is a point-in-time diagnostic; there is no weekly or daily tracking dashboard, and ongoing measurement requires the separate $1,500-per-quarter service [61]. Second, enterprises requiring procurement-ready security, integrations, role-based permissions, or service-level commitments. No multi-user platform, shared workspace, or marketing-automation integration is described in the public materials [64]. Third, buyers who need Google AI Overviews or Microsoft Copilot coverage. The Full Audit covers ChatGPT, Claude, Gemini, and Perplexity only [63]. Fourth, buyers requiring strong independent validation of methodology and customer outcomes. Published B2B SaaS case evidence appears limited, and the case-study page states additional SaaS audits were still in the pipeline [66].

Budget-constrained teams seeking sub-$500 comprehensive audits are also a poor match; competitors such as monitoraeo list a $79 full audit and SEOGrade lists a $349 blueprint [67].

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to BeCited for a B2B buyer who needs continuous AI visibility monitoring?
  • When should a B2B buyer choose a broader platform instead of the BeCited Full Audit?

Choose a continuous-monitoring platform when tracking competitive dynamics or campaign impact week over week matters more than a one-time diagnostic. Platforms named Amadora AI, OptimizeGEO, Omnia, Semrush AI Visibility, and Veza Digital as alternatives for real-time or weekly tracking and multi-user workflows [69]. Third-party coverage of citation-tracking tools describes continuous monitoring versus point-in-time evaluation as the core distinction in this market [70].

Choose a broader engine-coverage provider when Google AI Overviews or Microsoft Copilot matter. Platforms named monitoraeo, SEOGrade, LoudScale, and Fratzke as alternatives with wider surface coverage [71].

Choose a technical SEO or content-intelligence engagement when the primary need is large-scale crawl analysis, content production, information architecture, or implementation rather than AI-answer visibility [76]. Veza Digital's $4,500, 30-day continuous-tracking audit and Paul Teitelman's five-area audit framework are documented alternatives at different price and scope points [77].

Choose a vendor with independently documented B2B SaaS case studies when procurement requires verified customer outcomes [76].

Questions to Verify Before Buying

Questions This Section Answers

  • What should a B2B buyer confirm with BeCited before signing for a Full Audit?
  • How should a buyer resolve the conflicting site-readiness check counts before purchase?

The supplied evidence leaves several items unresolved. Confirm each in writing before paying.

  • Exactly how many prompts, personas, competitors, pages, and source platforms are included for this B2B engagement [79]?
  • Does the report provide URL-level citation mapping and page-level content recommendations, or only category-level source mapping [80]?
  • What is the final number of site-readiness checks: 15 or 19 [79]?
  • How are prompt selection, sampling, geographic settings, personalization, and repeat-query variance controlled [79]?
  • Are taxes, custom research, additional engines, extra stakeholders, implementation support, or re-runs charged separately [79]?
  • What are the quarterly renewal, cancellation, refund, and prorating terms [82]?
  • Can the buyer share the report internally with agencies, board members, or external implementation partners [82]?
  • Can BeCited provide relevant B2B SaaS references and anonymized examples of competitor and citation-architecture findings [81]?
  • Does the 30-day re-check re-run all 100–300 prompts or a subset, and is it included in the $2,000 [83]?
  • Are Google AI Overviews and Microsoft Copilot on the roadmap, and if so, when [84]?

Final AI Consensus Verdict

BeCited is a good fit for AI Search Audits for B2B Companies, with a caveat about evidence quality. Five of seven platforms rated the fit good or strong; one rated it uncertain; one platform's rating was not captured as a distinct fit label in the supplied responses. Two platforms named BeCited in their ranking stage, at ranks 3 and 6.

The case for BeCited rests on scope alignment. The Full Audit covers buying-intent prompts, competitor benchmarking, source intelligence, gap analysis, and a prioritized 90-day plan at a published $2,000 one-time price — a direct match to the study criteria [86]. The case against rests on verification. Nearly all supporting citations are company-owned, the site-readiness check count conflicts across BeCited's own pages, quarterly cancellation terms are unspecified, and independent B2B customer evidence is limited [90].

Platform agreement on scope does not prove product quality. Buyers should treat the Full Audit as a focused, analyst-led diagnostic and verify scope, technical mapping depth, contract terms, and B2B references before purchase. Buyers who need continuous monitoring, enterprise workflow features, or broader engine coverage should evaluate the alternatives named above. For a fuller view of how other providers scored against the same criteria, see the AI Search Audits for B2B Companies consensus index.

How This Review Was Produced

This review was produced from a single research run dated 2026-09-18 covering seven AI platforms: OpenAI (gpt-5.6-luna), Anthropic (claude-haiku-4-5-20251001), Google (gemini-3.5-flash), Grok (x-ai/grok-4.3), Perplexity (perplexity/sonar), Kimi (moonshotai/kimi-k2.6), and DeepSeek (deepseek-v4-flash). Each platform received the same prompt asking which AI search audit providers it would recommend for B2B companies needing buying-journey prompt analysis, competitor benchmarking, citation and source intelligence, citation architecture mapping, content-gap analysis, and a prioritized visibility strategy.

Platform mentions in the ranking stage count only platforms that named BeCited during ranking discovery. All seven platforms evaluated fit, but only Grok and Kimi named the entity in their ranked recommendations. Fit ratings, strengths, limitations, pricing summaries, and verification questions were extracted from each platform's structured response.

The research date is the authoritative run date. Platform-reported research dates are provenance metadata and do not independently prove freshness. DeepSeek's response carries a research date of 2026-02-06, which differs from the run date.

Methodology Limitations

Several limitations apply. Company-owned citations materially outnumber independent citations in the supplied evidence; company claims are not independently verified and should not be read as such. 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 pass ran without search enabled and could not retrieve the BeCited website, so its "uncertain" rating reflects absence of evidence rather than a contradiction of other platforms' findings [93]. Its research date also differs from the run date.

Factual conflicts remain unresolved and were not guessed at: the 15-versus-19 site-readiness check count, third-party Capterra listings describing monthly plans that do not match the site's one-time pricing, and the unspecified scope of the 30-day re-check [94]. BeCited's terms disclaim guarantees of future visibility or business outcomes, and AI answers are inherently volatile [99].

No personal testing, customer experience, or independent verification was performed for this review. Platform agreement on scope does not establish product quality.

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

Sources

Company-Owned Sources

  • BeCited — AI Search Visibility Audit: https://becited.io/
  • About BeCited — One analyst, calibrated method, real audits: https://becited.io/about
  • AI Search Guide — How AI engines pick which brands to cite: https://becited.io/ai-search-guide
  • Query Fan-Out, Dense Retrieval, Pairwise Ranking - BeCited: https://becited.io/ai-search-guide/how-ai-mode-works
  • Case Studies — BeCited: https://becited.io/case-studies
  • Contact — Scope your AI search engagement - BeCited: https://becited.io/contact/
  • Methodology — How BeCited keeps the audit honest: https://becited.io/methodology
  • Revenue at Risk Calculator — How much could AI search gaps cost you?: https://becited.io/revenue-calculator/
  • Sample BeCited GEO Audit — what every audit looks like: https://becited.io/sample-report
  • Services — Audits, tracking, and relevance engineering | BeCited: https://becited.io/services
  • Relevance Engineering — Move the needle, not the dashboard: https://becited.io/services/relevance-engineering
  • Ridgeview Window Cleaning - Sample Snapshot: https://becited.io/snapshot-sample/snapshot
  • Terms of Service — BeCited: https://becited.io/terms
  • AI Search Audit | LoudScale: https://loudscale.com/ai-search-audit/
  • SaaS SEO Audit — Built for PLG, AI Search, and pSEO: https://seograde.ai/for/saas
  • Audit — AI visibility diagnostic | monitoraeo: https://www.monitoraeo.com/product/audit
  • AI Visibility Audit for B2B Companies | Profitec AI: https://www.profitec-ai.com/ai-visibility-audit
  • Official pricing and terms source: https://becited.io#pricing
  • Additional AI research evidence99 records
    1. AI research evidence record grok:web:0
    2. AI research evidence record kimi:c1
    3. AI research evidence record deepseek:c1
    4. AI research evidence record openai:becited-home
    5. AI research evidence record anthropic:2
    6. AI research evidence record anthropic:10
    7. AI research evidence record anthropic:31
    8. AI research evidence record perplexity:c1
    9. AI research evidence record perplexity:c2
    10. AI research evidence record google:2.1.5
    11. AI research evidence record kimi:c1
    12. AI research evidence record grok:web:0
    13. AI research evidence record perplexity:c12
    14. AI research evidence record google:2.1.3
    15. AI research evidence record openai:becited-home
    16. AI research evidence record anthropic:2
    17. AI research evidence record grok:web:0
    18. AI research evidence record perplexity:c3
    19. AI research evidence record google:2.1.2
    20. AI research evidence record openai:becited-methodology
    21. AI research evidence record anthropic:31
    22. AI research evidence record perplexity:c7
    23. AI research evidence record grok:web:0
    24. AI research evidence record google:2.1.2
    25. AI research evidence record openai:becited-home
    26. AI research evidence record anthropic:2
    27. AI research evidence record perplexity:c3
    28. AI research evidence record kimi:c1
    29. AI research evidence record deepseek:c1
    30. AI research evidence record openai:becited-case-studies
    31. AI research evidence record anthropic:38
    32. AI research evidence record perplexity:c13
    33. AI research evidence record perplexity:c14
    34. AI research evidence record openai:becited-home
    35. AI research evidence record grok:web:0
    36. AI research evidence record perplexity:c3
    37. AI research evidence record google:2.1.6
    38. AI research evidence record anthropic:10
    39. AI research evidence record openai:becited-methodology
    40. AI research evidence record perplexity:c4
    41. AI research evidence record google:2.2.5
    42. AI research evidence record anthropic:38
    43. AI research evidence record google:2.1.2
    44. AI research evidence record perplexity:c5
    45. AI research evidence record google:2.2.6
    46. AI research evidence record anthropic:31
    47. AI research evidence record kimi:c1
    48. AI research evidence record grok:web:0
    49. AI research evidence record openai:becited-home
    50. AI research evidence record google:2.1.5
    51. AI research evidence record perplexity:c11
    52. AI research evidence record openai:becited-terms
    53. AI research evidence record anthropic:2
    54. AI research evidence record perplexity:c12
    55. AI research evidence record google:2.1.3
    56. AI research evidence record openai:becited-home
    57. AI research evidence record perplexity:c3
    58. AI research evidence record anthropic:2
    59. AI research evidence record google:2.1.2
    60. AI research evidence record kimi:c1
    61. AI research evidence record anthropic:10
    62. AI research evidence record anthropic:38
    63. AI research evidence record kimi:c1
    64. AI research evidence record openai:becited-home
    65. AI research evidence record anthropic:2
    66. AI research evidence record openai:becited-case-studies
    67. AI research evidence record kimi:c4
    68. AI research evidence record kimi:c5
    69. AI research evidence record anthropic:2
    70. AI research evidence record anthropic:27
    71. AI research evidence record kimi:c1
    72. AI research evidence record kimi:c4
    73. AI research evidence record kimi:c5
    74. AI research evidence record kimi:c6
    75. AI research evidence record anthropic:6
    76. AI research evidence record openai:becited-home
    77. AI research evidence record anthropic:1
    78. AI research evidence record anthropic:4
    79. AI research evidence record openai:becited-home
    80. AI research evidence record openai:becited-methodology
    81. AI research evidence record openai:becited-case-studies
    82. AI research evidence record openai:becited-terms
    83. AI research evidence record anthropic:10
    84. AI research evidence record anthropic:2
    85. AI research evidence record kimi:c1
    86. AI research evidence record openai:becited-home
    87. AI research evidence record grok:web:0
    88. AI research evidence record perplexity:c3
    89. AI research evidence record google:2.1.5
    90. AI research evidence record openai:becited-case-studies
    91. AI research evidence record anthropic:2
    92. AI research evidence record deepseek:c1
    93. AI research evidence record deepseek:c1
    94. AI research evidence record openai:becited-home
    95. AI research evidence record openai:becited-case-studies
    96. AI research evidence record perplexity:c13
    97. AI research evidence record perplexity:c14
    98. AI research evidence record anthropic:10
    99. AI research evidence record openai:becited-terms

Independent Sources

  • AI Search Visibility Audit for B2B SaaS: https://getaisearchaudit.com/
  • AI Search Audit Services | Benchmark AI Visibility | Fratzke: https://www.fratzkemedia.com/solutions/ai-search-audit
  • AI Citation Tracking Tools: Monitor Your Brand (2026: https://www.stackmatix.com/blog/ai-citation-tracking-tools
  • Best Citation Analysis Options for Optimizing AI Search in 2026: https://www.useomnia.com/blog/best-citation-analysis-options-optimizing-ai-search
  • Additional AI research evidence99 records
    1. AI research evidence record grok:web:0
    2. AI research evidence record kimi:c1
    3. AI research evidence record deepseek:c1
    4. AI research evidence record openai:becited-home
    5. AI research evidence record anthropic:2
    6. AI research evidence record anthropic:10
    7. AI research evidence record anthropic:31
    8. AI research evidence record perplexity:c1
    9. AI research evidence record perplexity:c2
    10. AI research evidence record google:2.1.5
    11. AI research evidence record kimi:c1
    12. AI research evidence record grok:web:0
    13. AI research evidence record perplexity:c12
    14. AI research evidence record google:2.1.3
    15. AI research evidence record openai:becited-home
    16. AI research evidence record anthropic:2
    17. AI research evidence record grok:web:0
    18. AI research evidence record perplexity:c3
    19. AI research evidence record google:2.1.2
    20. AI research evidence record openai:becited-methodology
    21. AI research evidence record anthropic:31
    22. AI research evidence record perplexity:c7
    23. AI research evidence record grok:web:0
    24. AI research evidence record google:2.1.2
    25. AI research evidence record openai:becited-home
    26. AI research evidence record anthropic:2
    27. AI research evidence record perplexity:c3
    28. AI research evidence record kimi:c1
    29. AI research evidence record deepseek:c1
    30. AI research evidence record openai:becited-case-studies
    31. AI research evidence record anthropic:38
    32. AI research evidence record perplexity:c13
    33. AI research evidence record perplexity:c14
    34. AI research evidence record openai:becited-home
    35. AI research evidence record grok:web:0
    36. AI research evidence record perplexity:c3
    37. AI research evidence record google:2.1.6
    38. AI research evidence record anthropic:10
    39. AI research evidence record openai:becited-methodology
    40. AI research evidence record perplexity:c4
    41. AI research evidence record google:2.2.5
    42. AI research evidence record anthropic:38
    43. AI research evidence record google:2.1.2
    44. AI research evidence record perplexity:c5
    45. AI research evidence record google:2.2.6
    46. AI research evidence record anthropic:31
    47. AI research evidence record kimi:c1
    48. AI research evidence record grok:web:0
    49. AI research evidence record openai:becited-home
    50. AI research evidence record google:2.1.5
    51. AI research evidence record perplexity:c11
    52. AI research evidence record openai:becited-terms
    53. AI research evidence record anthropic:2
    54. AI research evidence record perplexity:c12
    55. AI research evidence record google:2.1.3
    56. AI research evidence record openai:becited-home
    57. AI research evidence record perplexity:c3
    58. AI research evidence record anthropic:2
    59. AI research evidence record google:2.1.2
    60. AI research evidence record kimi:c1
    61. AI research evidence record anthropic:10
    62. AI research evidence record anthropic:38
    63. AI research evidence record kimi:c1
    64. AI research evidence record openai:becited-home
    65. AI research evidence record anthropic:2
    66. AI research evidence record openai:becited-case-studies
    67. AI research evidence record kimi:c4
    68. AI research evidence record kimi:c5
    69. AI research evidence record anthropic:2
    70. AI research evidence record anthropic:27
    71. AI research evidence record kimi:c1
    72. AI research evidence record kimi:c4
    73. AI research evidence record kimi:c5
    74. AI research evidence record kimi:c6
    75. AI research evidence record anthropic:6
    76. AI research evidence record openai:becited-home
    77. AI research evidence record anthropic:1
    78. AI research evidence record anthropic:4
    79. AI research evidence record openai:becited-home
    80. AI research evidence record openai:becited-methodology
    81. AI research evidence record openai:becited-case-studies
    82. AI research evidence record openai:becited-terms
    83. AI research evidence record anthropic:10
    84. AI research evidence record anthropic:2
    85. AI research evidence record kimi:c1
    86. AI research evidence record openai:becited-home
    87. AI research evidence record grok:web:0
    88. AI research evidence record perplexity:c3
    89. AI research evidence record google:2.1.5
    90. AI research evidence record openai:becited-case-studies
    91. AI research evidence record anthropic:2
    92. AI research evidence record deepseek:c1
    93. AI research evidence record deepseek:c1
    94. AI research evidence record openai:becited-home
    95. AI research evidence record openai:becited-case-studies
    96. AI research evidence record perplexity:c13
    97. AI research evidence record perplexity:c14
    98. AI research evidence record anthropic:10
    99. AI research evidence record openai:becited-terms

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
28
Ranking mentions
2 of 7
Platform share
29%
Final consensus rank
#6

Research trail and source mix

Configured platforms

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

Source mix

8 independent · 20 company-owned

Evidence support

13 direct · 13 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 bd41c1b6d63d176679c0e9caf25cf48998b87952f29e269cb5a28dcb0b6ab155