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AI Consensus Fit Review

First Page Sage AI Citation Building Agency Fit Review for B2B Companies

First Page Sage is a qualified good fit for B2B companies that want AI citation building delivered as a managed, expert-led content and authority program rather than a software subscription.

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

Answer Capsule

First Page Sage is a qualified good fit for B2B companies that want AI citation building delivered as a managed, expert-led content and authority program rather than a software subscription. Two of seven platforms named it during ranking discovery — Grok (rank 3) and OpenAI (rank 2) — giving it an average listed rank of 2.5 and a 28.6% share of included platform responses. The strongest reason to consider it is its integrated B2B GEO, thought-leadership SEO, comparison-source, and authority-building model aimed at research-heavy buying journeys. The main limitation is evidence quality: public proof is predominantly company-published, pricing is indicative rather than quoted, and independent reviewers question whether its AI citation measurement is client-level or aggregate.

Research Snapshot

FieldFinding
Platform mentions in ranking stage2 of 7 platforms (Grok, OpenAI)
Share of included platform responses28.6%
Average listed rank2.5
Best listed rank2 (OpenAI)
Relevant product/model/planB2B GEO integrated with expert-led content, SEO, and authority building; Thought Leadership SEO + GEO
Overall use-case fitGood, with qualification (OpenAI, Perplexity, Google: good; Grok: strong; Anthropic, DeepSeek: mixed; Kimi: uncertain)
Research date2026-09-17

Why First Page Sage Qualified for This Study

Questions This Section Answers

  • Why did First Page Sage qualify for a B2B AI citation building agency review when only two platforms named it?
  • Is First Page Sage's third-party corroboration strong enough for a B2B buyer to shortlist it?

First Page Sage qualified because it cleared the study's minimum-mention threshold and because the platforms that did name it placed it near the top of their lists. Grok listed it third and OpenAI listed it second, producing an average listed rank of 2.5 and a best listed rank of 2 [1]. It appeared in 2 of 7 platform responses, a 28.6% share, which is a minority of the panel rather than a consensus.

The corroboration picture is mixed and worth separating carefully. Independent sources describe First Page Sage as a San Francisco-based SEO and GEO agency specializing in thought-leadership content for B2B enterprises [3], and independent roundups have ranked it as a leading B2B SEO agency in the United States [4]. Its founder, Evan Bailyn, is credited in independent coverage with pioneering generative engine optimization [5]. Independent review sites also note it has been referenced as a benchmark by Moz, SEMrush, HubSpot, and Search Engine Journal [6].

However, the largest share of substantive claims about its GEO methodology, case studies, and measurement comes from First Page Sage's own domain. Company-owned citations materially outnumber independent citations in this evidence set, so company claims should not be read as independently verified. Independent reviewers have also flagged an evidence gap: strong traditional SEO results but limited public proof of client-level recommendation movement or AI-attributed commercial outcomes [7].

The Product, Model, Plan, or Service Most Relevant to AI Citation Building Agencies for B2B Companies

Questions This Section Answers

  • Which First Page Sage service should a B2B buyer evaluate for AI citation building, and how is it scoped?
  • Does First Page Sage's Thought Leadership SEO + GEO plan include comparison-source and third-party authority work?

The relevant offer is First Page Sage's B2B GEO service integrated with expert-led content, SEO, and authority building, marketed as Thought Leadership SEO + GEO. Every platform that named the entity pointed to this same service model, though the naming was not perfectly standardized across platforms [8].

The model combines several components rather than selling citation placement alone. First Page Sage describes GEO as increasing the likelihood that generative AI systems recommend a company or product, and its B2B GEO material addresses vendor discovery and shortlisting across ChatGPT, Claude, Gemini, and Google AI Overviews [8]. Its published methodology emphasizes comparison and list articles, metrics content, authoritative lists, reviews, awards, and directories as third-party authority signals [12].

Content production is positioned as expert-led. First Page Sage describes an internal team of subject matter experts in technically complex B2B fields such as SaaS, medical devices, and fintech, producing content intended to satisfy both search algorithms and LLM citation standards [14]. Independent coverage describes the GEO approach as built on expert-authored, research-backed articles that AI systems tend to cite for high-trust commercial queries, with a framework covering authority content architecture, third-party list placements, traditional PR, and verifiability signals [15].

One important scoping caveat: the recommended service name and exact package structure are not clearly presented as a standardized public plan, so the assessment treats the supplied B2B GEO plus Thought Leadership SEO description as the relevant service model. Buyers should confirm the actual scope in writing.

What the AI Platforms Agreed About

Questions This Section Answers

  • What do AI platforms agree First Page Sage is actually good at for B2B AI citation building?
  • Is First Page Sage's B2B buying-journey and comparison-content focus confirmed across platforms?

Agreement was strong on positioning and mixed on proof. The clearest cross-platform agreement is that First Page Sage is a B2B-focused SEO and GEO agency whose core asset is expert-led thought-leadership content aimed at complex buying journeys.

Multiple platforms converged on buying-journey alignment. OpenAI found that First Page Sage describes GEO as increasing the likelihood that generative AI systems recommend a company or product, and that its B2B GEO material addresses vendor discovery and shortlisting [17]. Anthropic found the agency targets keywords across the full sales cycle and produces content designed to convert readers into qualified leads [19]. Grok found programs built around the full buyer evaluation, from problem searches to comparison keywords, with monthly deliverables including use-case pages, research pieces, and comparison articles [21]. Perplexity found the site says it uses thought-leadership content to establish expertise, build trust, and foster relationships [22].

Platforms also agreed on the authority-building mechanism. OpenAI described a methodology emphasizing comparison and list articles, metrics content, authoritative lists, reviews, awards, and directories [23]. Grok described GEO services combining SEO, PR, review management, superlative list articles, and authority placements [25]. Google described an approach targeting key LLM recommendation sources through expert thought-leadership content, structured database listings, schema implementation, and strategic third-party list placements [27].

Where agreement thinned was measurement. OpenAI reported that a published case study tracks citation share, first-mention rate, description accuracy, AI-sourced pipeline, and prompt clusters across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews [29]. Anthropic, by contrast, reported that the methodology does not include recurring prompt-level tracking across those engines or a pipeline attribution model connecting AI referral sessions to CRM conversions [31]. These are not necessarily contradictory — one describes a case study, the other describes the general methodology — but the distinction matters to buyers and is unresolved in the public evidence.

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Why do AI platforms disagree about whether First Page Sage offers native AI citation tracking?
  • How much should a B2B buyer trust First Page Sage's reported AI citation and pipeline results?

Fit ratings diverged sharply across the panel. Grok rated the fit strong; OpenAI, Perplexity, and Google rated it good; Anthropic and DeepSeek rated it mixed; Kimi rated it uncertain. That spread is itself the headline finding — this is not a consensus pick.

The most consequential disagreement concerns AI citation measurement. Anthropic reported that First Page Sage's methodology does not include recurring prompt-level tracking across ChatGPT, Perplexity, Gemini, and Google AI Overviews, nor pipeline attribution connecting AI referral sessions to CRM conversions [32]. Anthropic also reported that platforms did not find a consistently disclosed scoring protocol or sample client report for the AI measurement approach [33], and that public evidence did not demonstrate a mature, closed-loop system connecting the content/SEO layer to the AI measurement layer to business impact [34]. OpenAI, in contrast, reported measurement concepts including citation share, first mention, description accuracy, prompt clusters, and AI-sourced pipeline drawn from published case studies [35]. The unresolved question is whether that measurement is available to individual clients or only appears in aggregate research.

Pricing conflicts are material. First Page Sage publishes indicative GEO tiers of roughly $2,000–$3,000, $4,000–$7,000, and $8,000–$12,000 per month depending on scope [37]. Perplexity recorded the top tier as $10,000–$13,000 per month rather than $8,000–$12,000 [39]. Independent sources report a broader retainer range of $8,000–$20,000 per month with 6–12 month minimums [40]. Google reported annual contracts with a minimum commitment of 6 to 12 months as standard [41]. Perplexity found a company page stating engagements are month-to-month with no annual lock-in, while another company page says typical campaigns last 2–5 years [42]. These figures should be treated as company-published benchmarks or third-party estimates, not verified pricing for a specific engagement.

GEO capability maturity is also contested. First Page Sage positions itself as having pioneered GEO [44]. Independent assessments rate its GEO capability as moderate rather than best-in-class [46], and independent analysis notes a lack of clarity on whether the offering is a uniquely AI-native toolset or traditional high-quality SEO repackaged under the GEO label [47].

Kimi reported the weakest evidence base of any platform, stating that no retrieved source directly quoted First Page Sage's services or pricing and that official-site retrieval failed for at least one mention [48]. Kimi's uncertain rating reflects missing evidence, not a negative finding.

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • Does First Page Sage build comparison-source and third-party corroboration assets for B2B vendor comparison prompts?
  • What content capacity does First Page Sage deliver per month for a B2B AI citation program?

The capability set maps reasonably well to the six category criteria, with the weakest coverage on recommendation measurement.

B2B buying-journey understanding. Strong across platforms. The agency targets keywords across the full sales cycle and produces content designed to convert readers into qualified leads [49]. Grok reported monthly deliverables including use-case pages, research pieces, and comparison articles [51].

Third-party corroboration. Described but not fully specified. The framework covers authority content architecture, third-party list placements, traditional PR, and verifiability signals [52]. Grok reported facilitation of review management, directory listings, media coverage, and link-earning research content [53]. It remains unclear which placements are earned, paid, partner-based, or client-provided.

Citation architecture. Partially documented. The published methodology emphasizes comparison and list articles, metrics content, authoritative lists, reviews, awards, and directories [54]. Google reported schema implementation and site-retrievability optimization for conversational crawlers [56]. However, the public material does not establish that every engagement includes paid or editorial placements, and Anthropic found no documented evidence that the agency specifically engineers comparison content to rank in AI comparison-shopping prompts [57].

Comparison sources. Positioned but not proven. First Page Sage produces comparison articles and use-case content designed to appear in buyer research queries, but there is no documented evidence of specific optimization for competitive vendor evaluation chains within LLM responses [57].

Industry authority. Well supported. Independent coverage describes digital PR through thought-leadership content marketing helping SaaS companies establish industry authority [59]. The client list is reported to include Microsoft, Salesforce, US Bank, Logitech, and Cadence, plus 100+ mid-sized businesses [60]. B2B work is reported across SaaS, financial services, manufacturing, healthcare, and construction [61].

Recommendation measurement. The weakest area. Published case studies report tracking citation share, first-mention rate, description accuracy, AI-sourced pipeline, and prompt clusters [62], and one reports recommendation-share tracking with Profound [63]. Grok reported tracking share of recommendations via tools like Profound, with pipeline growth, ROI, and AI mention increases [51]. But Anthropic found no recurring prompt-level tracking or CRM pipeline attribution in the methodology [65], and independent review found limited public proof of client-level recommendation movement [66].

Content capacity is a practical constraint. Independent sources report deliverables typically include 4–8 content pieces per month depending on tier [67], while Anthropic reported 3–5 articles per month at the highest tier — significantly slower than velocity-focused competitors publishing 7–14 articles weekly [67]. Buyers prioritizing citation velocity over depth should weigh this.

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does First Page Sage cost per month for a B2B GEO and thought-leadership program?
  • Is First Page Sage month-to-month, or does it require a 6–12 month minimum contract?

Pricing is not published as a standard rate card, and the sources conflict. Treat every figure below as an indicative benchmark or third-party estimate, not a quote.

Cost elementReported figureSource type
GEO Tier 1~$2,000–$3,000/monthCompany-published
GEO Tier 2~$4,000–$7,000/monthCompany-published
GEO Tier 3~$8,000–$12,000/month (Perplexity recorded $10,000–$13,000)Company-published
Thought Leadership SEO~$10,000–$15,000/monthCompany-published
Typical B2B retainer$8,000–$20,000/monthIndependent estimate
Project floor$5,000+Independent estimate

Contract terms are genuinely unclear and should be treated as a verification item. One company page states month-to-month engagements with no annual lock-in [68], while another company page says typical campaigns last 2–5 years [69]. Independent sources report 6–12 month minimums [70], and Google reported annual contracts with a minimum commitment of 6 to 12 months as standard [71]. A plausible reading is an initial commitment period followed by monthly renewal, but the public language conflicts and should not be resolved by guessing.

Additional fees are not clearly itemized. Potential charges for third-party placements, PR, reviews, directories, original research, data acquisition, media, or specialist measurement tools are not separated from agency fees [72]. Whether tools such as Profound are included in the retainer or billed separately is also unclear [72]. The first month typically includes strategic planning before production begins [70].

Best Suited For

Questions This Section Answers

  • Which B2B companies get the most value from First Page Sage's Thought Leadership SEO + GEO program?
  • Is First Page Sage worth it for a B2B company with a complex, research-heavy buying journey?

First Page Sage is best suited to established B2B organizations with complex, research-heavy buying journeys and the budget and patience for a sustained content and authority program.

The strongest fit is B2B SaaS, technology, professional-services, and other complex categories where buyers use research-heavy prompts to discover, compare, and shortlist vendors [73]. Independent coverage describes the agency as ideal for B2B SaaS with long sales cycles and complex products requiring content-led education [75], and reports specialization across SaaS, financial services, manufacturing, healthcare, and construction [76].

It also fits teams that want one agency covering AI visibility, expert-led content, traditional SEO, comparison and list-article visibility, and third-party authority development rather than stitching together separate vendors [77]. Buyers should be prepared to fund a sustained, multi-month program rather than expecting immediate or guaranteed AI placement [80].

Organizations that can dedicate internal subject matter experts to co-create authoritative content are a better fit than those without that capacity [81]. Independent coverage also notes the agency's clearest strengths are expert long-form content, original research, technical SEO, online authority, conversion-focused organic growth, and operational capacity to execute [82].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose First Page Sage for B2B AI citation building?
  • Is First Page Sage a poor fit for a growth-stage SaaS company needing fast AI citation wins?

Several buyer profiles are poor matches. Teams requiring guaranteed AI citations, guaranteed recommendations, or immediate visibility should look elsewhere — no public guarantee of inclusion, citation, recommendation, ranking, or revenue outcome was verified [83].

Growth-stage or Series A/B SaaS companies under roughly $20M ARR needing fast AI citation results with documented prompt-level tracking and CRM pipeline attribution are a weak fit, because the model is built for established brands that can absorb a 12-month contract and a 6–12 month ramp to results [85]. Independent analysis states directly that if you are a $3M–$20M ARR SaaS company needing AI citation coverage measured, attributed, and tied to CRM pipeline, First Page Sage's model is not built for that [85].

Buyers seeking a transparent standardized package price or a narrowly scoped monitoring-software subscription are also mismatched [83]. Organizations requiring independently audited outcomes or extensive publicly verifiable third-party corroboration before purchase should note that reported case-study outcomes are not independently audited in the cited material [87].

Budget-constrained teams and those wanting instant results or short-term projects without ongoing retainers are excluded by the pricing floor and ramp timeline [89]. Buyers who only need narrow citation-listing or PR placement work without broader SEO and content execution are also a poor fit [91].

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to First Page Sage for a B2B buyer who needs self-service AI prompt tracking?
  • When should a B2B buyer choose a specialized GEO agency over First Page Sage?

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

If the primary need is self-service prompt tracking rather than managed content and authority building, a specialized monitoring or software provider is a better fit [93]. If the buyer needs recurring AI citation tracking with prompt libraries monitored daily or weekly across all major LLM platforms in client dashboards, or CRM-to-session attribution proving AI referral traffic converts to pipeline, purpose-built GEO platforms are the better comparison [94].

If the buyer needs visible AI citation wins within 30–90 days rather than a 6–12 month ramp, or prefers month-to-month flexibility with an exit if initial metrics miss expectations, a faster-ramp competitor is preferable [96]. If the buyer needs AI citation velocity of 10+ articles per week rather than authority-focused quality of 3–5 highly researched pieces per month, a velocity-focused provider fits better [97].

If the buyer needs transparent published pricing or a lower-cost option, alternatives with published tiers are preferable [98]. If the buyer needs independently verified GEO or citation performance benchmarks before purchase, a vendor with stronger third-party review coverage may be preferable [100]. If the buyer wants only tactical AI citation-listing or PR placements without a broader SEO and content program, a more specialized GEO or PR shop may fit better [102].

If the buyer already has strong subject-matter experts, content operations, and publisher relationships, an in-house or consulting-led model may be more efficient [93]. If the buyer operates in low-complexity product categories where expert ghostwriting adds limited incremental authority, technical optimization and citation architecture alone may suffice [103].

Questions to Verify Before Buying

Questions This Section Answers

  • What should a B2B buyer confirm with First Page Sage before signing a GEO contract?
  • How should a buyer verify First Page Sage's AI citation measurement and fee separation?

The verification list below consolidates the unresolved items across platforms. Every item reflects a documented gap or conflict in the supplied evidence.

Scope and deliverables. Confirm the exact monthly deliverables: expert articles, research assets, comparison pages, publisher outreach, digital PR, directories, reviews, and technical SEO [104]. Confirm how many content pieces per month apply at your tier and what the approval and revision cycle looks like [105]. Confirm whether the engagement includes technical implementation such as schema and structured data or only strategic guidance [106].

Measurement definitions. Ask how citation share, first mention, recommendation share, description accuracy, prompt coverage, and pipeline attribution are defined and reported [107]. Ask which target prompts, AI engines, countries, industries, competitors, and buying stages will be monitored [104]. Ask whether recurring prompt-level tracking is included, at what frequency, and on which platforms [109]. Request a redacted sample client report showing exact prompts tracked, raw citation data with dates and engines, normalized citation frequency, AI referral traffic, and pipeline attribution logic [110].

Fee separation. Ask what portion of placements is earned versus paid, and who pays external publisher, PR, directory, or media fees [104]. Ask whether Profound or another measurement platform is included, and who owns the account and historical data [104]. Ask whether third-party placement, PR, reviews, directories, original research, data acquisition, media, and specialist tool costs are itemized separately from agency fees [104].

Contract terms. Confirm the actual minimum contract term, cancellation notice, onboarding fee, renewal terms, and content-ownership provisions [111]. Ask what happens if progress lags agreed baselines by month six, and whether strategy adjustments or expanded prompt coverage require additional spend [114]. Ask whether price-protection clauses or capped annual increases apply on renewal [111].

References and outcomes. Ask for recent B2B references in your industry and whether reported outcomes can be substantiated with verifiable analytics [115]. Ask how inaccurate or unfavorable AI descriptions, competitor comparisons, and model changes are handled [104]. Ask explicitly what outcomes are not guaranteed, including rankings, citations, recommendations, leads, revenue, or publisher acceptance [104].

Final AI Consensus Verdict

First Page Sage is a good fit, with qualification, for B2B companies that want AI citation building delivered as a managed content and authority program. It was named by 2 of 7 platforms in the ranking stage, with an average listed rank of 2.5 and a best listed rank of 2. Fit ratings ranged from strong (Grok) to uncertain (Kimi), so this is a qualified rather than unanimous recommendation.

The case for it rests on integrated B2B GEO, thought-leadership SEO, comparison-source strategy, third-party authority development, and recommendation measurement aimed at research-heavy buying journeys [116]. The case against rests on evidence quality and transparency: public proof is predominantly company-published, pricing is indicative rather than quoted, contract terms conflict across sources, and independent reviewers question whether AI citation measurement is client-level or aggregate [119].

Buyers needing guaranteed AI visibility, standardized transparent pricing, self-service monitoring, or independently audited results should look at alternatives. For buyers who fit the profile, procurement should depend on a written scope, fee separation, measurement definitions, contract terms, and recent client references. The broader set of options is catalogued in the AI Citation Building Agencies for B2B Companies index, and related coverage sits in the ai citation authority building directory.

How This Review Was Produced

This review was produced from platform-reported research collected on 2026-09-17. Seven platforms evaluated First Page Sage for fit against the use case "AI Citation Building Agencies for B2B Companies": OpenAI, Anthropic, Google, Grok, Perplexity, DeepSeek, and Kimi. Each platform returned a fit rating, a direct answer, strengths, limitations, pricing and terms, use-case findings, and questions to verify before buying.

Ranking statistics were calculated only from platforms that named the entity during ranking discovery. Two platforms named First Page Sage — Grok and OpenAI — producing an average listed rank of 2.5, a best listed rank of 2, and a 28.6% share of included platform responses. The remaining platforms evaluated fit without naming the entity in the ranking stage.

All citations are platform-reported evidence, not independently verified facts. The supplied URLs were collected from platform responses and were not independently validated. Company-owned citations materially outnumber independent citations in this evidence set, so company claims should not be described as independently verified. No personal testing, customer experience, or independent verification was performed for this review.

Methodology Limitations

Several limitations materially affect how this review should be read.

Evidence ownership skew. Company-owned citations materially outnumber independent citations. Most substantive claims about First Page Sage's GEO methodology, case studies, and measurement come from its own domain. Do not treat company claims as independently verified.

Platform-reported research dates differ from the run date. The authoritative study date is 2026-09-17. DeepSeek's platform-reported research date was 2026-06-01, roughly three months earlier. Platform-reported dates are provenance metadata and do not independently prove freshness.

No-search model claims. DeepSeek reported search_enabled as false, so its findings are model-reported rather than retrieval-backed and require explicit verification before being described as current facts.

Official-site retrieval failure. Official-site retrieval failed for one or more mentions, and no failed fetch was used as a verified domain key. Kimi reported that no retrieved source directly quoted First Page Sage's services or pricing, and that official-site retrieval failed for at least one mention [123]. Missing research is not evidence of absence.

Unresolved conflicts. Pricing, contract length, product naming, and GEO capability maturity all conflict across sources. This review describes the conflicts rather than resolving them by guessing. Buyers should verify each directly.

Company-reported outcomes. Published case studies and performance figures are company-reported, with no independent audit confirmed in the cited sources. Reported results are directional company claims.

Minimum-mention threshold. Only 2 of 7 platforms named First Page Sage in the ranking stage. Platform agreement does not prove product quality, and a minority mention share means this is not a consensus recommendation.

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

Sources

Company-Owned Sources

Independent Sources

  • AEO Engine vs First Page Sage: AEO Execution Platform vs…: https://aeoengine.ai/vs/first-page-sage
  • B2B AI Visibility Services | Cite Solutions: https://cite.solutions/b2b-ai-visibility-services
  • First Page Sage Review: Pricing, Services & Expert Analysis (2026: https://deathtoseo.com/agencies/first-page-sage/
  • The 7 Best First Page Sage Alternatives for B2B SaaS in 2026; Ranked by GEO Model, Not Just Price: https://derivatex.agency/blog/first-page-sage-alternatives/
  • First Page Sage Pricing: $8K to $20K/Month, Lock-In | Fervor Studio: https://fervorstudio.ca/first-page-sage-pricing/
  • The 7 Best SaaS SEO Agencies In 2026 | Garit Boothe Digital: https://garitboothe.com/best-saas-seo-agencies
  • First Page Sage Review 2026: AI Search Verdict | LLM Authority Index: https://llmauthorityindex.com/ai-search-agencies/first-page-sage-review
  • 15 Best B2B SEO Agencies for Pipeline Growth in 2026: https://nathanojaokomo.com/blog/best-b2b-seo-agencies
  • The 10 best SaaS and enterprise SEO agencies for 2026: https://superframeworks.com/articles/best-saas-enterprise-seo-agencies
  • First Page Sage: SEO & GEO agency that turns content into: https://surferstack.com/first-page-sage
  • The 7 Best GEO Agencies for B2B Tech in 2026: https://www.breakingb2b.com/blog/best-geo-agencies-b2b-tech
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    2. AI research evidence record openai:c2
    3. AI research evidence record anthropic:46-5
    4. AI research evidence record anthropic:9-1
    5. AI research evidence record anthropic:5-4
    6. AI research evidence record anthropic:46-7
    7. AI research evidence record anthropic:14-5
    8. AI research evidence record openai:c1
    9. AI research evidence record grok:web:1
    10. AI research evidence record perplexity:1
    11. AI research evidence record openai:c2
    12. AI research evidence record openai:c3
    13. AI research evidence record openai:c4
    14. AI research evidence record anthropic:5-6
    15. AI research evidence record anthropic:11-1
    16. AI research evidence record anthropic:11-3
    17. AI research evidence record openai:c1
    18. AI research evidence record openai:c2
    19. AI research evidence record anthropic:6-3
    20. AI research evidence record anthropic:9-3
    21. AI research evidence record grok:web:1
    22. AI research evidence record perplexity:7
    23. AI research evidence record openai:c3
    24. AI research evidence record openai:c4
    25. AI research evidence record grok:web:0
    26. AI research evidence record grok:web:12
    27. AI research evidence record google:first_page_sage_geo_guide
    28. AI research evidence record google:saffron_edge_geo
    29. AI research evidence record openai:c6
    30. AI research evidence record openai:c7
    31. AI research evidence record anthropic:11-5
    32. AI research evidence record anthropic:11-5
    33. AI research evidence record anthropic:44-6
    34. AI research evidence record anthropic:44-8
    35. AI research evidence record openai:c6
    36. AI research evidence record openai:c7
    37. AI research evidence record openai:c8
    38. AI research evidence record grok:web:0
    39. AI research evidence record perplexity:5
    40. AI research evidence record anthropic:30-1
    41. AI research evidence record google:gtm_8020_alternatives
    42. AI research evidence record perplexity:1
    43. AI research evidence record perplexity:12
    44. AI research evidence record anthropic:5-4
    45. AI research evidence record google:saffron_edge_geo
    46. AI research evidence record anthropic:32-10
    47. AI research evidence record google:spicy_margarita_comparison
    48. AI research evidence record kimi:ranking_stage_input
    49. AI research evidence record anthropic:6-3
    50. AI research evidence record anthropic:9-3
    51. AI research evidence record grok:web:1
    52. AI research evidence record anthropic:11-3
    53. AI research evidence record grok:web:0
    54. AI research evidence record openai:c3
    55. AI research evidence record openai:c4
    56. AI research evidence record google:first_page_sage_geo_guide
    57. AI research evidence record anthropic:1-1
    58. AI research evidence record anthropic:1-2
    59. AI research evidence record anthropic:3-1
    60. AI research evidence record anthropic:10-5
    61. AI research evidence record anthropic:1-9
    62. AI research evidence record openai:c6
    63. AI research evidence record openai:c7
    64. AI research evidence record grok:web:12
    65. AI research evidence record anthropic:11-5
    66. AI research evidence record anthropic:14-5
    67. AI research evidence record anthropic:30-7
    68. AI research evidence record perplexity:1
    69. AI research evidence record perplexity:12
    70. AI research evidence record anthropic:30-1
    71. AI research evidence record google:gtm_8020_alternatives
    72. AI research evidence record openai:c8
    73. AI research evidence record openai:c1
    74. AI research evidence record openai:c2
    75. AI research evidence record anthropic:6-3
    76. AI research evidence record anthropic:1-9
    77. AI research evidence record openai:c3
    78. AI research evidence record openai:c4
    79. AI research evidence record anthropic:11-3
    80. AI research evidence record anthropic:41-15
    81. AI research evidence record google:spicy_margarita_comparison
    82. AI research evidence record anthropic:14-3
    83. AI research evidence record openai:c8
    84. AI research evidence record anthropic:41-15
    85. AI research evidence record anthropic:41-4
    86. AI research evidence record perplexity:11
    87. AI research evidence record anthropic:14-5
    88. AI research evidence record openai:c7
    89. AI research evidence record grok:web:0
    90. AI research evidence record anthropic:30-1
    91. AI research evidence record perplexity:5
    92. AI research evidence record perplexity:7
    93. AI research evidence record openai:c8
    94. AI research evidence record anthropic:11-5
    95. AI research evidence record anthropic:41-4
    96. AI research evidence record anthropic:41-15
    97. AI research evidence record anthropic:30-7
    98. AI research evidence record perplexity:11
    99. AI research evidence record kimi:badenbower_agency
    100. AI research evidence record anthropic:14-5
    101. AI research evidence record perplexity:15
    102. AI research evidence record perplexity:5
    103. AI research evidence record anthropic:11-1
    104. AI research evidence record openai:c8
    105. AI research evidence record anthropic:30-7
    106. AI research evidence record google:first_page_sage_geo_guide
    107. AI research evidence record openai:c6
    108. AI research evidence record openai:c7
    109. AI research evidence record anthropic:11-5
    110. AI research evidence record anthropic:44-6
    111. AI research evidence record anthropic:30-1
    112. AI research evidence record perplexity:1
    113. AI research evidence record perplexity:12
    114. AI research evidence record anthropic:41-15
    115. AI research evidence record anthropic:14-5
    116. AI research evidence record openai:c1
    117. AI research evidence record openai:c2
    118. AI research evidence record anthropic:11-3
    119. AI research evidence record anthropic:14-5
    120. AI research evidence record anthropic:44-6
    121. AI research evidence record perplexity:1
    122. AI research evidence record perplexity:12
    123. AI research evidence record kimi:ranking_stage_input

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Study date
September 17, 2026
Platforms analyzed
7
Source records
45
Ranking mentions
2 of 7
Platform share
29%
Final consensus rank
#5

Research trail and source mix

Configured platforms

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

Source mix

17 independent · 28 company-owned

Evidence support

36 direct · 9 partial

Important limitation

Use the run research_date as the study date. Platform-reported dates are provenance metadata and do not independently prove freshness.

Source snapshot SHA-256 c99c21dba9320b434eae75b554510d0b25967a083fe23e3c3738b5dc14a24576