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Veza Digital AI Search Audit Fit Review for Mid-Market Companies

Veza Digital is a good fit for mid-market companies that want a fixed-price, consultant-led AI search audit rather than an enterprise software subscription.

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

Answer Capsule

Veza Digital is a good fit for mid-market companies that want a fixed-price, consultant-led AI search audit rather than an enterprise software subscription. Two of the seven platforms in this study named Veza Digital during ranking discovery, at an average listed rank of 4.5 and a best rank of 4. The strongest reason to consider it is the publicly listed $4,500 AI Search Visibility Audit, which combines 30 days of tracking across six AI platforms, competitor benchmarking, content and technical review, and a 90-day action plan [1]. The main limitation is evidence quality: most public detail comes from Veza Digital's own pages, methodology specifics are thin, and independent validation of the audit product itself is limited [4].

Research Snapshot

FieldFinding
Platform mentions in ranking stage2 of 7 platforms (deepseek, kimi)
Share of included platform responses28.6%
Average listed rank4.5
Best listed rank4
Relevant product/model/planAI Search Visibility Audit ($4,500 fixed price)
Overall use-case fitGood, with verification caveats
Research date2026-09-18

Why Veza Digital Qualified for This Study

Questions This Section Answers

  • Why did only two of seven AI platforms name Veza Digital in the ranking stage for mid-market AI search audits?
  • Is Veza Digital a legitimate contender for AI Search Audits for Mid-Market Companies, or did it qualify on a technicality?

Veza Digital qualified because it cleared the study's minimum-mention threshold: at least two platforms had to name the entity during ranking discovery. DeepSeek listed it at rank 4 and Kimi at rank 5, giving an average listed rank of 4.5 and a best rank of 4. That placed Veza Digital seventh in the final ranking order.

The qualification is narrow. Five of the seven included platforms did not name Veza Digital in the ranking stage, so its 28.6% platform share reflects limited discovery rather than broad consensus. The platforms that did name it pointed to the same product: the AI Search Visibility Audit, publicly listed at a fixed $4,500 [6].

Qualification also reflects a real market gap. Mid-market teams often find that manual spot-checks do not scale while enterprise platforms carry price tags and timelines that do not match team size [12]. Veza Digital's productized audit sits inside the documented $2,500–$5,000 mid-market audit band [13], which is why platforms treated it as relevant even when they did not rank it.

The Product, Model, Plan, or Service Most Relevant to AI Search Audits for Mid-Market Companies

Questions This Section Answers

  • What exactly does Veza Digital's $4,500 AI Search Visibility Audit include for a mid-market company?
  • Which AI platforms does the Veza Digital audit test, and how long does tracking run?
  • Is the Veza Digital audit a one-time report or an ongoing monitoring service?

The relevant offer is the AI Search Visibility Audit, a one-time diagnostic listed at a fixed $4,500 [14]. Veza Digital describes it as a 30-page report covering 30 days of AI platform tracking across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, and Copilot [14].

Stated scope includes typically 50–100 custom prompts built from the buyer's keyword universe, competitors, sales input, and industry questions; competitor benchmarking against up to three competitors; a page-by-page review of roughly 20–30 top pages; entity analysis; technical readiness review covering schema, crawlers, and speed; and a 90-day prioritized action plan with impact and effort estimates [14].

Delivery is described as approximately six weeks, with the 30-day tracking window consuming most of the timeline. Veza Digital states the tracking period cannot be compressed without losing pattern data [23]. The buyer receives the report, raw tracking data, and a 60-minute strategy call, and Veza states the report and action plan are owned outright with no lock-in [26].

A separate free AEO audit is also offered: a manual baseline review delivered in about five business days with no commitment, testing the same six platforms for baseline citations and competitive gaps [29]. Veza Digital states its audits are hand-created and individually reviewed rather than automated scans [35].

What the AI Platforms Agreed About

Questions This Section Answers

  • What do multiple AI platforms agree the Veza Digital audit does well for mid-market buyers?
  • Is the Veza Digital audit's $4,500 price considered reasonable for mid-market AI search audits?

Agreement was strong on scope and price, though not unanimous across all seven platforms.

On price, platforms that retrieved the audit page consistently reported the same figure: a fixed $4,500 with no tiered pricing disclosed [38]. Anthropic rated pricing confidence high and placed the figure inside the documented $2,500–$5,000 mid-market audit range [44]. Google described the flat-rate structure as removing procurement friction for mid-market budgets [43].

On scope, multiple platforms reported the same six-platform coverage, 30-day tracking window, competitor benchmarking against three competitors, and 90-day action plan [38].

On standalone usability, platforms agreed the deliverable does not require follow-on services. Veza states the action plan works standalone and the report is owned outright [51]. Google and Grok both characterized the audit as a one-time standalone engagement with no recurring contract commitment [43].

On fit rating, four of seven platforms rated Veza Digital a good or strong fit for this use case, while two rated it uncertain (deepseek, kimi). That split is itself a finding: agreement was strong on what the product claims to include, and weaker on whether those claims are independently verifiable.

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Why did some AI platforms rate Veza Digital's audit as uncertain rather than a good fit?
  • Does the Veza Digital audit include Claude, and is that platform coverage confirmed?

Disagreement centered on verifiability, not on product scope.

DeepSeek rated fit uncertain and stated that the service page could not be retrieved during its research, so deliverable details and pricing could not be confirmed against vendor text. It also noted the $4,500 figure appeared only in ranking-stage input, not in a retrievable Veza source [54]. Kimi reached a similar conclusion, reporting that the audit page content could not be verified in its accessible sources and that engine coverage, query volume, deliverable format, and methodology depth were unconfirmed [55].

Platforms also flagged a platform-coverage conflict. The paid audit page names ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, and Copilot, while another Veza service page references optimization work that includes Claude. It is unclear whether Claude is included in the paid audit itself [56]. Buyers should confirm this directly.

Methodology detail was repeatedly described as thin. OpenAI noted the page references both Ahrefs Brand Radar and custom prompt testing but does not disclose the division of labor, data access, sampling frequency, or export schema [56]. Perplexity found public detail on recommendation analysis, source-domain analysis, and scoring methodology limited or unclear [58]. Google noted it is publicly unclear whether the 30-day tracking uses automated monitoring scripts or manual prompt sampling protocols [61].

Independent evidence is scarce. Perplexity located a HarperFlow profile stating Veza Digital was mentioned in 14 of 150 AI answers in a Webflow buyer study and that two of three AI engines recommended it, but that evidence concerns the agency brand, not the audit product [62]. Independent review coverage exists on Clutch and Serchen, but those reviews describe general agency outcomes such as organic traffic, engagement, and conversion improvements rather than this specific audit [63].

One naming conflict is worth noting: search results return two separate entities, Veza.com (an identity security platform) and VezaDigital.com (the AEO and Webflow agency). This review addresses VezaDigital only, per the supplied URL (anthropic, factual conflict disclosure).

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • Does the Veza Digital audit measure brand mentions and citations across AI platforms, or only rankings?
  • How does Veza Digital handle competitor benchmarking and influential source-domain analysis in its audit?

Recommendation and citation analysis is a stated advantage. Veza Digital describes testing how the brand appears, is cited, or is omitted across six platforms using typically 50–100 custom prompts [65].

Tracking depth is a stated advantage. The service includes 30 days of continuous tracking with citation stability and volatility analysis rather than a one-time snapshot, using Ahrefs Brand Radar plus custom prompt testing [65].

Competitor benchmarking is a stated advantage. The scope benchmarks up to three competitors across all six platforms and produces a competitive gap map showing queries and topics where competitors appear and the buyer does not [65].

Influential source-domain analysis is unclear. Public scope describes citation analysis, competitor sources, entity analysis, and raw citation data, but does not clearly specify a separate ranked analysis of influential source domains, domain-level authority, or source causality. OpenAI explicitly advised verifying the exact source-domain deliverable [65]. Perplexity reached the same conclusion [71].

Content and authority gaps are a stated advantage. The audit includes page-by-page review of roughly 20–30 top pages, content freshness and citation-readiness checks, entity analysis, technical review, and buyer-question content-gap analysis. Authority-gap analysis is referenced in broader technical audit materials, but the paid audit page does not fully define an off-site authority methodology [65].

The prioritized roadmap is a stated advantage. The deliverable includes a 90-day action plan sequenced into quick wins (weeks 1–2), structural fixes (month 1), content work (months 2–3), and ongoing off-site activity, with expected-impact and effort estimates plus a 60-minute strategy call [65].

Operational fit is a stated advantage with one caveat. The report, raw data, and action plan are described as usable by the buyer's internal team or another agency, and the audit scope is the same regardless of CMS. However, Veza states implementation expertise is deepest for Webflow, and non-Webflow platforms receive specs for the client team to implement [65].

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does the Veza Digital AI Search Visibility Audit cost, and are there setup or cancellation fees?
  • What happens to the $4,500 audit fee if a mid-market buyer later signs a Veza Digital WAIO retainer?

The publicly listed price is $4,500 fixed for the AI Search Visibility Audit [81]. No tiered pricing or per-platform variable costs are disclosed (anthropic, pricing summary).

Ongoing costs are optional but material. Veza Digital lists a WAIO engagement at $8,000 per month, and states the $4,500 audit fee is credited in full toward the first month if the engagement begins within 60 days of receiving the audit [81]. Anthropic also noted WAIO setup and migrations from $28,000 if technical architecture changes are required, particularly for non-Webflow platforms [89]. These figures are company-reported and should be confirmed in a commercial proposal (openai, factual conflict disclosure).

Contract terms are partly documented. Veza states there is no lock-in and the buyer owns the report and raw data [81]. However, public materials do not specify payment schedule, refund policy, rescheduling terms, confidentiality language, data retention, or formal cancellation terms [81]. Veza's terms of service reserve the right to update or modify terms and services without prior notice, and disclose that AI-assisted tools may be used in service delivery (official:C3).

Pricing confidence varied by platform: high from Anthropic, Grok, and Google; moderate from OpenAI and Perplexity; low from DeepSeek and Kimi, which could not verify the figure against vendor materials [93].

For context, independent sources place mid-market B2B audits between $2,500 and $5,000 [94], and mid-market AEO agency retainers between $5,000 and $10,000 per month [95]. Semrush plans start at $139 per month for core SEO with bundled AI visibility options [96].

Best Suited For

Questions This Section Answers

  • Which mid-market companies get the most value from the Veza Digital AI Search Visibility Audit?
  • Is the Veza Digital audit a good choice for a mid-market team that plans to execute recommendations in-house?

Veza Digital is best suited to B2B companies that need a decision-ready AI search diagnostic rather than software access alone (openai, fit assessment). That includes B2B SaaS and software companies seeking a one-time AI visibility diagnostic before committing to ongoing optimization, and mid-market organizations evaluating whether AI citation gaps justify dedicated optimization budgets (anthropic, fit assessment).

It also suits marketing or SEO teams that can work within a six-week audit process and want data transferable to internal staff or another agency (openai, fit assessment). Buyers who prefer fixed pricing and defined scope over enterprise custom quotes are a stated fit (anthropic, fit assessment).

Companies with Webflow sites may get additional value, since Veza states implementation expertise is deepest for Webflow and it can implement schema and crawler configuration directly on Webflow [97].

Buyers willing to spend $4,500 for 30 days of tracking and interpretation are the intended audience (openai, fit assessment). The free five-day AEO audit also gives risk-averse buyers a low-commitment way to validate need before the paid engagement [100].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose Veza Digital for AI Search Audits for Mid-Market Companies?
  • Is Veza Digital a poor fit for a mid-market company that needs continuous AI citation monitoring?

Veza Digital is probably not the best fit for buyers needing continuous monitoring after the audit rather than a one-time diagnostic (openai, fit assessment; anthropic, fit assessment). The audit is time-bounded, and ongoing monitoring after delivery is not included in the stated $4,500 diagnostic (openai, limitations).

It is also a weaker fit for organizations requiring independently audited AI-search measurement or publicly documented methodology validation (openai, fit assessment; perplexity, fit assessment). Public materials do not fully specify source-domain influence scoring, sampling methodology, prompt reproducibility, statistical confidence, or how recommendation quality and citation correctness are adjudicated (openai, limitations).

Very small companies seeking a free or automated snapshot, and enterprises needing formal procurement, security, and governance documentation, are outside the intended fit (openai, fit assessment). Anthropic noted no mention of SOC 2 or regulatory compliance certifications, and no hallucination detection or advanced compliance features, which limits fit for regulated industries (anthropic, limitations).

Buyers with budgets below $2,500, or those needing results within two to three weeks, are also poorly matched given the six-week timeline [103].

Non-Webflow buyers should weigh the implementation gap. WordPress, HubSpot, and custom-build sites receive platform-appropriate specs for internal execution rather than the deeper Webflow-level support [105].

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to Veza Digital for a mid-market buyer who needs continuous AI citation monitoring?
  • When is a lower-cost self-service AI visibility tool a better choice than the Veza Digital audit?

Choose a lower-cost self-service or automated monitoring tool when the buyer only needs a baseline snapshot or recurring dashboard and can interpret results internally (openai, better alternative when). Kimi noted that TurboAudit, MonitorAEO, and TriRank publish explicit engine counts and query volumes, with entry prices well below $4,500 [109].

Choose an enterprise search-intelligence or analytics provider when the buyer needs formal governance, procurement documentation, larger-scale query coverage, API access, role-based controls, or continuous reporting (openai, better alternative when). Anthropic specifically named Semrush at $139+ per month, Conductor, and Scrunch AI for continuous programs, and noted Scrunch AI explicitly meets SOC 2 Type II with hallucination detection for regulated industries [112].

Choose a specialist research consultancy when independent validation of AI-search methodology, source-domain influence, or statistically defensible benchmarking matters more than a packaged agency roadmap (openai, better alternative when).

Choose a faster or platform-specialized provider when the buyer needs results in two to three weeks, needs implementation-ready code on a non-Webflow CMS, or needs multi-brand portfolio audits that scale better through self-serve tools (anthropic, better alternative when).

Choose a free or DIY route when budget is below $2,500. HubSpot's guidance notes that mid-market teams face a real tradeoff between manual spot-checks that do not scale and enterprise platforms that do not match team size [113].

Questions to Verify Before Buying

Questions This Section Answers

  • What should a mid-market buyer confirm with Veza Digital before signing for the $4,500 audit?
  • How can a buyer verify Veza Digital's prompt methodology, platform coverage, and raw-data deliverables before purchase?

Platforms converged on a similar verification list. Confirm the exact prompt count, page count, competitor count, markets, and business lines included for the price (openai, questions to verify; anthropic, questions to verify; deepseek, questions to verify).

Confirm whether Claude is included and whether all six named platforms are tested for every prompt across the full 30-day period (openai, questions to verify; kimi, questions to verify).

Confirm how prompts are selected, localized, refreshed, and reproducibly rerun, and how recommendation quality, citation correctness, source prominence, and hallucinated or outdated brand descriptions are scored (openai, questions to verify; perplexity, questions to verify).

Confirm the raw-data format and whether prompt text, timestamps, platform, response, cited URLs, and competitor results are included (openai, questions to verify; deepseek, questions to verify).

Confirm whether the final report includes a ranked list of influential source domains, domain-level citation share, and recommendations for acquiring or improving those sources (openai, questions to verify; deepseek, questions to verify).

Confirm payment, cancellation, refund, confidentiality, data-retention, and security terms, and whether third-party tool costs, data-access costs, revisions, extra competitors, or additional pages are billed separately (openai, questions to verify; perplexity, questions to verify; kimi, questions to verify).

Confirm ongoing monitoring or reporting options after the six-week audit and their price, and ask for a redacted sample report and references from comparable mid-market clients (openai, questions to verify; deepseek, questions to verify; perplexity, questions to verify).

Final AI Consensus Verdict

Veza Digital is a good fit for mid-market companies seeking a contained, human-led AI search diagnostic with multi-platform citation tracking, competitor benchmarking, technical and content analysis, and a prioritized roadmap (openai, final verdict; anthropic, final verdict; perplexity, final verdict). Google and Grok rated the fit strong; OpenAI, Anthropic, and Perplexity rated it good; DeepSeek and Kimi rated it uncertain because they could not verify the audit page content or the $4,500 price against retrievable vendor materials [114].

The buying risks are consistent across platforms: limited independent validation, incomplete public detail on influential source-domain analysis and methodology, capped competitor and page scope, and unclear ongoing-monitoring and contract terms (openai, final verdict; perplexity, final verdict; anthropic, limitations). Buyers should obtain a detailed statement of work before purchase.

How This Review Was Produced

This review synthesizes fit-research responses from seven AI platforms: OpenAI, Anthropic, Google, Grok, Perplexity, DeepSeek, and Kimi. Each platform independently evaluated Veza Digital against the same use case and criteria. The study date is 2026-09-18.

Two of the seven platforms named Veza Digital during ranking discovery, which is the basis for its inclusion. All seven platforms then produced fit assessments, which are the primary evidence for this review. Platform-reported research dates differ from the study date: DeepSeek reported 2026-02-14, while the other six reported 2026-09-18. Platform-reported dates are provenance metadata and do not independently prove freshness.

Methodology Limitations

Company-owned citations materially outnumber independent citations in this evidence set. Most product detail comes from Veza Digital's own pages, and those claims are not independently verified. Citations are platform-reported evidence, not verified facts.

DeepSeek ran without search enabled, so its findings rest on ranking-stage input rather than retrieved vendor pages. DeepSeek and Kimi both reported that the audit page could not be retrieved during their research, which is why they rated fit uncertain rather than good or poor.

The supplied URLs were collected from platform responses and were not independently validated by the writer stage. Platform-reported research dates differ from the authoritative run date, and one platform's date is roughly seven months older than the rest.

Several material conflicts remain unresolved: whether Claude is included in the paid audit, how Ahrefs Brand Radar and custom prompt testing divide labor, and whether the $8,000-per-month WAIO figure and 60-day credit condition hold in a commercial proposal. Missing research was not treated as disagreement.

See the broader AI Search Audits for Mid-Market Companies consensus index for comparisons across qualified options.

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

Sources

Company-Owned Sources

  • AEO Audit - 42-Point AI Search Visibility Analysis — Agenxus: https://agenxus.com/tools/aeo-audit
  • SaaS SEO Audit — SEOGrade: https://seograde.ai/for/saas
  • AEO / AI Visibility Audit — TriRank: https://trirankai.com/audit
  • TurboAudit — AI Search Audit & Visibility Platform: https://turboaudit.ai/
  • Frase Auditor — AI Readiness Scoring: https://www.frase.io/features/auditor
  • Audit — AI visibility diagnostic — MonitorAEO: https://www.monitoraeo.com/product/audit
  • AI search visibility - Veza Digital: https://www.vezadigital.com/ai-search-visibility
  • Free AEO Audit: AI Search Visibility Check: https://www.vezadigital.com/services/aeo-audit
  • Answer Engine Optimization (AEO) & GEO Agency: https://www.vezadigital.com/services/answer-engine-optimization
  • Technical SEO Audit Service Optimized for Crawlers, Users, and LLMs: https://www.vezadigital.com/services/technical-seo-audit
  • Official pricing and terms source: https://www.vezadigital.com/work-with-veza
  • Official pricing and terms source: https://www.vezadigital.com/legal/terms-of-service
  • Additional AI research evidence115 records
    1. AI research evidence record openai:c1
    2. AI research evidence record anthropic:1-2
    3. AI research evidence record anthropic:1-40
    4. AI research evidence record perplexity:c6
    5. AI research evidence record kimi:vezadigital-unverified
    6. AI research evidence record openai:c1
    7. AI research evidence record anthropic:1-6
    8. AI research evidence record anthropic:11-3
    9. AI research evidence record grok:0
    10. AI research evidence record perplexity:c1
    11. AI research evidence record google:veza_audit_page
    12. AI research evidence record anthropic:38-1
    13. AI research evidence record anthropic:32-3
    14. AI research evidence record openai:c1
    15. AI research evidence record anthropic:1-6
    16. AI research evidence record perplexity:c1
    17. AI research evidence record google:veza_audit_page
    18. AI research evidence record anthropic:1-2
    19. AI research evidence record anthropic:1-19
    20. AI research evidence record anthropic:1-39
    21. AI research evidence record anthropic:1-40
    22. AI research evidence record grok:0
    23. AI research evidence record anthropic:1-12
    24. AI research evidence record anthropic:1-16
    25. AI research evidence record anthropic:1-17
    26. AI research evidence record anthropic:1-8
    27. AI research evidence record anthropic:1-10
    28. AI research evidence record anthropic:39-26
    29. AI research evidence record anthropic:2-1
    30. AI research evidence record anthropic:2-2
    31. AI research evidence record anthropic:2-3
    32. AI research evidence record anthropic:14-11
    33. AI research evidence record anthropic:14-12
    34. AI research evidence record perplexity:c2
    35. AI research evidence record anthropic:14-25
    36. AI research evidence record anthropic:14-26
    37. AI research evidence record anthropic:14-27
    38. AI research evidence record openai:c1
    39. AI research evidence record anthropic:1-6
    40. AI research evidence record anthropic:11-3
    41. AI research evidence record grok:0
    42. AI research evidence record perplexity:c1
    43. AI research evidence record google:veza_audit_page
    44. AI research evidence record anthropic:32-3
    45. AI research evidence record anthropic:39-1
    46. AI research evidence record anthropic:39-2
    47. AI research evidence record anthropic:1-2
    48. AI research evidence record anthropic:1-3
    49. AI research evidence record anthropic:1-4
    50. AI research evidence record anthropic:1-19
    51. AI research evidence record anthropic:1-8
    52. AI research evidence record anthropic:1-10
    53. AI research evidence record anthropic:39-26
    54. AI research evidence record deepseek:c1
    55. AI research evidence record kimi:vezadigital-unverified
    56. AI research evidence record openai:c1
    57. AI research evidence record openai:c2
    58. AI research evidence record perplexity:c1
    59. AI research evidence record perplexity:c2
    60. AI research evidence record perplexity:c3
    61. AI research evidence record google:veza_audit_page
    62. AI research evidence record perplexity:c6
    63. AI research evidence record anthropic:20-1
    64. AI research evidence record anthropic:27-1
    65. AI research evidence record openai:c1
    66. AI research evidence record anthropic:1-2
    67. AI research evidence record grok:0
    68. AI research evidence record google:veza_audit_page
    69. AI research evidence record anthropic:1-3
    70. AI research evidence record anthropic:1-19
    71. AI research evidence record perplexity:c1
    72. AI research evidence record openai:c2
    73. AI research evidence record anthropic:1-39
    74. AI research evidence record anthropic:1-40
    75. AI research evidence record anthropic:39-11
    76. AI research evidence record openai:c3
    77. AI research evidence record anthropic:1-25
    78. AI research evidence record anthropic:1-26
    79. AI research evidence record anthropic:1-27
    80. AI research evidence record anthropic:1-28
    81. AI research evidence record openai:c1
    82. AI research evidence record anthropic:1-6
    83. AI research evidence record anthropic:11-3
    84. AI research evidence record grok:0
    85. AI research evidence record perplexity:c1
    86. AI research evidence record google:veza_audit_page
    87. AI research evidence record anthropic:12-2
    88. AI research evidence record anthropic:39-21
    89. AI research evidence record anthropic:12-3
    90. AI research evidence record anthropic:1-8
    91. AI research evidence record anthropic:39-26
    92. AI research evidence record kimi:vezadigital-unverified
    93. AI research evidence record deepseek:c1
    94. AI research evidence record anthropic:32-3
    95. AI research evidence record anthropic:44-2
    96. AI research evidence record anthropic:31-4
    97. AI research evidence record openai:c3
    98. AI research evidence record anthropic:1-26
    99. AI research evidence record anthropic:1-27
    100. AI research evidence record anthropic:2-3
    101. AI research evidence record anthropic:14-11
    102. AI research evidence record anthropic:14-12
    103. AI research evidence record anthropic:1-12
    104. AI research evidence record anthropic:1-17
    105. AI research evidence record anthropic:1-25
    106. AI research evidence record anthropic:1-26
    107. AI research evidence record anthropic:1-27
    108. AI research evidence record anthropic:1-28
    109. AI research evidence record kimi:turboaudit-2026
    110. AI research evidence record kimi:monitoraeo-2026
    111. AI research evidence record kimi:trirank-2026
    112. AI research evidence record anthropic:31-4
    113. AI research evidence record anthropic:38-1
    114. AI research evidence record deepseek:c1
    115. AI research evidence record kimi:vezadigital-unverified

Independent Sources

  • AEO Agency Pricing: Month-to-Month Retainers (2026: https://aiadvantageagency.com/aeo-agency-pricing/
  • AI engine optimization audit: How to audit your content for AI search engines: https://blog.hubspot.com/marketing/aeo-audit
  • Veza Digital Reviews (45), Pricing, Services & Verified Ratings: https://clutch.co/profile/veza-digital
  • Veza Digital — AI Visibility Profile (85/100) | HarperFlow: https://www.harperflow.io/webflow-agencies/veza-digital
  • Veza Digital Product Details | Reviews, Pricing and Alternatives: https://www.serchen.com/company/veza-digital/reviews/
  • Additional AI research evidence115 records
    1. AI research evidence record openai:c1
    2. AI research evidence record anthropic:1-2
    3. AI research evidence record anthropic:1-40
    4. AI research evidence record perplexity:c6
    5. AI research evidence record kimi:vezadigital-unverified
    6. AI research evidence record openai:c1
    7. AI research evidence record anthropic:1-6
    8. AI research evidence record anthropic:11-3
    9. AI research evidence record grok:0
    10. AI research evidence record perplexity:c1
    11. AI research evidence record google:veza_audit_page
    12. AI research evidence record anthropic:38-1
    13. AI research evidence record anthropic:32-3
    14. AI research evidence record openai:c1
    15. AI research evidence record anthropic:1-6
    16. AI research evidence record perplexity:c1
    17. AI research evidence record google:veza_audit_page
    18. AI research evidence record anthropic:1-2
    19. AI research evidence record anthropic:1-19
    20. AI research evidence record anthropic:1-39
    21. AI research evidence record anthropic:1-40
    22. AI research evidence record grok:0
    23. AI research evidence record anthropic:1-12
    24. AI research evidence record anthropic:1-16
    25. AI research evidence record anthropic:1-17
    26. AI research evidence record anthropic:1-8
    27. AI research evidence record anthropic:1-10
    28. AI research evidence record anthropic:39-26
    29. AI research evidence record anthropic:2-1
    30. AI research evidence record anthropic:2-2
    31. AI research evidence record anthropic:2-3
    32. AI research evidence record anthropic:14-11
    33. AI research evidence record anthropic:14-12
    34. AI research evidence record perplexity:c2
    35. AI research evidence record anthropic:14-25
    36. AI research evidence record anthropic:14-26
    37. AI research evidence record anthropic:14-27
    38. AI research evidence record openai:c1
    39. AI research evidence record anthropic:1-6
    40. AI research evidence record anthropic:11-3
    41. AI research evidence record grok:0
    42. AI research evidence record perplexity:c1
    43. AI research evidence record google:veza_audit_page
    44. AI research evidence record anthropic:32-3
    45. AI research evidence record anthropic:39-1
    46. AI research evidence record anthropic:39-2
    47. AI research evidence record anthropic:1-2
    48. AI research evidence record anthropic:1-3
    49. AI research evidence record anthropic:1-4
    50. AI research evidence record anthropic:1-19
    51. AI research evidence record anthropic:1-8
    52. AI research evidence record anthropic:1-10
    53. AI research evidence record anthropic:39-26
    54. AI research evidence record deepseek:c1
    55. AI research evidence record kimi:vezadigital-unverified
    56. AI research evidence record openai:c1
    57. AI research evidence record openai:c2
    58. AI research evidence record perplexity:c1
    59. AI research evidence record perplexity:c2
    60. AI research evidence record perplexity:c3
    61. AI research evidence record google:veza_audit_page
    62. AI research evidence record perplexity:c6
    63. AI research evidence record anthropic:20-1
    64. AI research evidence record anthropic:27-1
    65. AI research evidence record openai:c1
    66. AI research evidence record anthropic:1-2
    67. AI research evidence record grok:0
    68. AI research evidence record google:veza_audit_page
    69. AI research evidence record anthropic:1-3
    70. AI research evidence record anthropic:1-19
    71. AI research evidence record perplexity:c1
    72. AI research evidence record openai:c2
    73. AI research evidence record anthropic:1-39
    74. AI research evidence record anthropic:1-40
    75. AI research evidence record anthropic:39-11
    76. AI research evidence record openai:c3
    77. AI research evidence record anthropic:1-25
    78. AI research evidence record anthropic:1-26
    79. AI research evidence record anthropic:1-27
    80. AI research evidence record anthropic:1-28
    81. AI research evidence record openai:c1
    82. AI research evidence record anthropic:1-6
    83. AI research evidence record anthropic:11-3
    84. AI research evidence record grok:0
    85. AI research evidence record perplexity:c1
    86. AI research evidence record google:veza_audit_page
    87. AI research evidence record anthropic:12-2
    88. AI research evidence record anthropic:39-21
    89. AI research evidence record anthropic:12-3
    90. AI research evidence record anthropic:1-8
    91. AI research evidence record anthropic:39-26
    92. AI research evidence record kimi:vezadigital-unverified
    93. AI research evidence record deepseek:c1
    94. AI research evidence record anthropic:32-3
    95. AI research evidence record anthropic:44-2
    96. AI research evidence record anthropic:31-4
    97. AI research evidence record openai:c3
    98. AI research evidence record anthropic:1-26
    99. AI research evidence record anthropic:1-27
    100. AI research evidence record anthropic:2-3
    101. AI research evidence record anthropic:14-11
    102. AI research evidence record anthropic:14-12
    103. AI research evidence record anthropic:1-12
    104. AI research evidence record anthropic:1-17
    105. AI research evidence record anthropic:1-25
    106. AI research evidence record anthropic:1-26
    107. AI research evidence record anthropic:1-27
    108. AI research evidence record anthropic:1-28
    109. AI research evidence record kimi:turboaudit-2026
    110. AI research evidence record kimi:monitoraeo-2026
    111. AI research evidence record kimi:trirank-2026
    112. AI research evidence record anthropic:31-4
    113. AI research evidence record anthropic:38-1
    114. AI research evidence record deepseek:c1
    115. AI research evidence record kimi:vezadigital-unverified

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Study date
September 18, 2026
Platforms analyzed
7
Source records
22
Ranking mentions
2 of 7
Platform share
29%
Final consensus rank
#7

Research trail and source mix

Configured platforms

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

Source mix

9 independent · 13 company-owned

Evidence support

16 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 bae93f44c59ee202ccd23b71596f810e457d75e4b984d68069721d2e0d03fc7a