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AI Consensus Fit Review

OtterlyAI AI Visibility Platforms Overall Fit Review

OtterlyAI is a good fit for companies that need prompt-based monitoring of brand mentions, citations, competitors, and share of voice across the core AI search engines, and it is a mixed fit for buyers who require confirmed coverage of Grok, DeepSeek, and Kimi.

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

Answer Capsule

OtterlyAI is a good fit for companies that need prompt-based monitoring of brand mentions, citations, competitors, and share of voice across the core AI search engines, and it is a mixed fit for buyers who require confirmed coverage of Grok, DeepSeek, and Kimi. Four of the seven included platforms named OtterlyAI during the ranking stage (openai, anthropic, grok, perplexity), a 57% share of included platform responses. Its strongest reason to consider it is a low entry price ($29/month Lite) combined with daily prompt monitoring and citation analytics. The main limitation is that current official materials do not confirm Grok, DeepSeek, or Kimi coverage, and Gemini, Claude, and Google AI Mode require paid add-ons.

Research Snapshot

FieldValue
Platform mentions in ranking stage4 of 7 included platforms (openai, anthropic, grok, perplexity)
Share of included platform responses57.1%
Average listed rank4.25
Best listed rank2 (grok, perplexity)
Relevant product/model/planOtterlyAI Content Intelligence Platform; Lite ($29/mo), Standard ($189/mo), Premium ($489/mo), Enterprise (custom)
Overall use-case fitGood for mainstream AI search visibility monitoring and GEO workflows; mixed for the broadest seven-engine requirement
Research date2026-09-19

Why OtterlyAI Qualified for This Study

Questions This Section Answers

  • Is OtterlyAI a good choice for AI Visibility Platforms overall?
  • How many AI platforms recommended OtterlyAI for AI visibility monitoring?

OtterlyAI qualified because four of the seven included platforms named it during ranking discovery, and six of the seven returned a usable fit assessment. The platforms that named it were openai, anthropic, grok, and perplexity; ranks ranged from 2 (grok, perplexity) to 8 (anthropic), producing an average listed rank of 4.25. OtterlyAI finished third in the final ranking.

The entity is a company, not a single product, and its official website is otterly.ai. OtterlyAI GmbH is based in Vienna, Austria, and was founded in 2024 by Thomas Peham (CEO), Josef Trauner (CPO), and Klaus-M. Schremser (CRO) [1]. One independent review describes the company as fully self-funded, with a team of 17 people and a user count that grew from 1,000 at launch to more than 40,000 by August 2026 [3]. Another independent review describes it as an early-stage product launched in 2024 [5].

Qualification was not unanimous. Kimi returned an uncertain assessment and stated that no independent sources in its search results mentioned OtterlyAI, and that official-site retrieval failed during its run [7]. DeepSeek also returned an uncertain assessment with no search enabled, so its findings are platform-reported rather than retrieved [8]. Those two responses are the main reason this review does not describe the fit findings as unanimous.

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

Questions This Section Answers

  • Which OtterlyAI plan should a buyer choose for tracking 100 prompts across ChatGPT, Perplexity, and Google AI Overviews?
  • Does OtterlyAI's Lite plan include enough prompts for ongoing AI visibility monitoring?

The most relevant offering is the OtterlyAI Content Intelligence Platform, sold on three self-serve tiers plus a custom Enterprise tier. The Lite plan lists at $29/month with 15 prompts; Standard lists at $189/month with 100 prompts; Premium lists at $489/month with 400 prompts; Enterprise starts from $1,000/month [9].

Platforms recommended different plans for different buyers. OpenAI pointed to Standard for small marketing teams and Premium for higher prompt volume, with Lite for limited testing. Grok named the Lite and Standard plans. Perplexity described Lite as the entry option, Standard for smaller marketing teams, and Premium for higher prompt volume. Anthropic described Lite as tracking-only with no integration possibilities, and noted that API and MCP access begin at Standard.

Base engine coverage on all paid plans is ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot [14]. Google AI Mode, Google Gemini, and Claude are paid add-ons [16]. One independent review states that OtterlyAI tracks brand mentions and citations across seven AI engines when add-ons are included [18], while another describes the base four-engine scope [15]. That difference reflects the base-versus-add-on distinction rather than a contradiction, but buyers should confirm exact availability by plan and country.

What the AI Platforms Agreed About

Questions This Section Answers

  • What do multiple AI platforms agree OtterlyAI does well for AI visibility tracking?
  • Does OtterlyAI track brand mentions, citations, and competitors across AI search engines?

The platforms broadly agreed on the core monitoring workflow. OpenAI, Anthropic, Grok, and Perplexity all described prompt-based tracking of brand mentions, citations, competitors, and visibility changes over time. OpenAI stated that OtterlyAI reports brand mentions, coverage, share of voice, sentiment, competitor comparisons, cited domains and URLs, citation-position changes, and gap analysis, plus reports and CSV exports [19]. Anthropic described a Brand Visibility Index that aggregates mention frequency, citation positioning, and share of voice into a single KPI, with side-by-side competitor tracking and sentiment classification [21].

The platforms also agreed on the mechanics of prompt monitoring. Users build a prompt library of conversational questions, and OtterlyAI runs those prompts across engines on a schedule, logging which brands get cited and in what order [22]. Prompt-level views include brand coverage, sentiment, competitor ranking, responses, and citation URLs [24].

A third area of agreement was data-collection method. Two independent reviews state that OtterlyAI replicates actual AI interfaces that real users interact with, rather than pulling responses from LLM APIs [25]. That distinction matters for buyers who want to see user-visible outputs rather than raw model responses.

Grok rated the fit "strong," while OpenAI, Anthropic, and Perplexity each rated it "good." Agreement on the monitoring workflow was strong across those four platforms, but it does not by itself prove product quality or measurement accuracy.

Where the AI Platforms Disagreed or Were Uncertain

Questions This Section Answers

  • Does OtterlyAI monitor Grok, DeepSeek, and Kimi, or only ChatGPT, Gemini, Claude, and Perplexity?
  • How reliable is OtterlyAI's AI visibility data according to independent reviews?

Engine coverage was the clearest point of uncertainty. OpenAI stated that the official material it reviewed does not list Grok, DeepSeek, or Kimi as supported engines [27]. Perplexity reported that verified source evidence for Claude, Grok, DeepSeek, and Kimi was unclear in the materials it checked [29]. DeepSeek could not verify the specific list of supported systems and recommended confirming coverage directly with the vendor [32]. Kimi stated that no source in its results confirmed coverage of ChatGPT, Gemini, Claude, Perplexity, Grok, DeepSeek, or Kimi [33].

Data accuracy drew mixed signals. OtterlyAI's own site claims 92% citation accuracy on its AI visibility checker [34]. No independent third-party validation of that metric was identified in the sources reviewed, and the definition of citation accuracy is unclear. One independent review noted inconsistencies, such as the main dashboard showing a brand mention while the actual prompt analysis did not show the brand mentioned [35]. Another independent review stated that OtterlyAI is a monitor-only tool that cannot tell a buyer which ChatGPT mention drove visits or leads, and that no API access existed at the time of that review [36]. That API statement conflicts with Standard-tier descriptions that include API and MCP access, and with a Standard plan listing of 2,000 API requests per month; the "no API access" claim likely refers to an earlier product version or is a misstatement.

Company maturity and user counts also carry uncertainty. Independent reviews describe a 2024 founding and an October 2024 product launch [37], while the user-count trajectory from 1,000 to 40,000+ is reported but not independently audited [39]. G2 lists more than 30,000 marketing professionals using OtterlyAI as of 2026 [40], a different figure from the 40,000+ claim, and neither is independently verified.

Kimi's assessment diverges most sharply. It reported that OtterlyAI was absent from every competitive-landscape source it retrieved, that official-site retrieval failed, and that the ranking-stage recommendation appeared speculative [33]. That finding conflicts directly with the four platforms that retrieved OtterlyAI-owned pages and independent reviews. The most likely explanation is a retrieval failure in Kimi's run rather than evidence that the product does not exist, but buyers should treat the conflict as unresolved.

Use-Case-Specific Features and Capabilities

Questions This Section Answers

  • What AI visibility features does OtterlyAI include for tracking citations and share of voice?
  • Does OtterlyAI tell a buyer which AI mentions drove website traffic or leads?

OtterlyAI covers the core AI visibility workflow: prompt research, daily monitoring, brand and competitor analytics, citation tracking, sentiment, share of voice, and GEO-oriented recommendations. OpenAI described daily prompt monitoring with multi-country support, where a prompt is counted separately for each country, so international coverage consumes prompt capacity faster [41]. Anthropic described tracking across 50+ countries with prompts in any language, with the dashboard interface presented in English only [43]. One official pricing rendering lists 50+ markets while help content lists 65+, so the exact country and language matrix is unclear.

Optimization features extend beyond measurement. OtterlyAI offers prompt research, crawlability checks, content audits, GEO audits, and recommendations intended to improve citation readiness [44]. One official page states that the platform audits 20+ on-page factors with specific remediation steps [46], and an independent review describes content audits that explain why AI engines skip a page and provide briefs to fix it [47]. Recommendations are generated from tracked brand-report data and require at least 15 prompts, three competitors, and at least three days of collected data before full refreshes [48]. On Lite, recommendation functionality is limited to a preview of three recommendations per seven-day cycle [48].

Operational features on Standard and Premium include API, MCP, Agent Analytics, Looker Studio integration, and unlimited workspaces [41]. One independent review states that report exports are CSV only, with no PDF export, which complicates board-ready reporting [49]. Another independent review notes a cluttered dashboard when many prompts and tracks are visible at once [50], while G2 reviews describe the dashboard as clean and intuitive [51].

The most consequential capability gap is attribution. OtterlyAI is a monitoring-only tool; it does not link AI mentions to visits, leads, or conversions, and buyers must correlate mention changes with GA4 or other analytics manually [49]. It also does not execute the optimization work it recommends.

Pricing, Fees, Contracts, and Ongoing Costs

Questions This Section Answers

  • How much does OtterlyAI cost per month, and what do the Gemini and Claude add-ons add to the bill?
  • What happens to OtterlyAI historical data and tracked engines after a subscription is canceled?

Published self-serve pricing is Lite at $29/month, Standard at $189/month, and Premium at $489/month, with annual billing shown as $25, $160, and $422 per month respectively when billed annually [52]. The pricing page states annual billing is 15% discounted [52]. Enterprise pricing is custom and starts from $1,000/month, with SSO, customizable prompt tracking, a quarterly GEO health check, and a dedicated CSM reported by one independent directory [56].

Add-ons materially change total cost. Google AI Mode and Gemini list at $9/$59/$149 per month for Lite/Standard/Premium, and Claude lists at $29/$109/$439 per month [52]. Additional prompt bundles on Standard and Premium cost $99 per 100 prompts monthly or $1,020 annually [52]. One independent review calculated that Premium with both Gemini and AI Mode add-ons can approach $787/month for full six-engine coverage [57]. Displayed add-on prices are in U.S. dollars excluding tax [52].

Contract terms are relatively flexible at the self-serve tiers. Monthly and annual billing are available, subscriptions can be canceled through account settings, and cancellation leaves access active through the current billing cycle [52]. One source reports a 14-day full-access trial with no credit card required [59], while the official pricing FAQ confirms a free trial for new users without stating the length [59]. The help documentation states that historical data and tracked engines are deleted after account cancellation [60], which is a material consideration for buyers who want to retain trend history. Enterprise plans can provide custom payment options and custom terms, and invoice payment is identified as available for Enterprise [52].

Pricing confidence varies by platform. Grok and Anthropic reported high confidence, OpenAI and Perplexity reported moderate confidence, and DeepSeek reported low confidence with no verified prices [61]. Some older OtterlyAI pages describe different plan names, prompt limits, tracking frequencies, or historical pricing, so current pricing and help pages should be treated as more relevant for a 2026 purchase.

Best Suited For

Questions This Section Answers

  • Who gets the most value from OtterlyAI for AI visibility monitoring?
  • Is OtterlyAI a good fit for a small marketing team tracking 15 to 100 prompts?

OtterlyAI is best suited to small and mid-sized marketing teams monitoring defined prompt sets across ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot [62]. It fits companies that need brand mentions, competitor rankings, citations, sentiment, share of voice, and changes over time in one workflow [64].

It also fits buyers who want a low-risk entry point. One independent review states that at $29/month, no other established AEO tracker gets a buyer started cheaper [66]. Anthropic described the platform as strongest for buyers validating whether AI visibility matters for their niche before investing in comprehensive GEO execution.

Agencies and multi-brand teams can use it where prompt volume stays within tier limits. The platform allows unlimited team members on all tiers and supports multiple workspaces for tracking multiple brands or clients under one subscription [67]. Standard and Premium add API, MCP, Looker Studio, and exports that support client reporting [62].

Buyers who value transparent published pricing also fit well. One independent review notes that OtterlyAI publishes pricing without a "contact sales" wall until Enterprise [69]. The company is GDPR-compliant and based in Austria [70].

Probably Not Best Suited For

Questions This Section Answers

  • Who should not choose OtterlyAI for AI visibility monitoring?
  • Is OtterlyAI suitable for an agency tracking many client brands with high prompt volume?

OtterlyAI is probably not the best choice for buyers who require one verified platform covering ChatGPT, Gemini, Claude, Perplexity, Grok, DeepSeek, and Kimi without paid engine add-ons or unsupported-engine gaps [71]. Current official materials do not confirm Grok, DeepSeek, or Kimi coverage.

It is also a weak fit for teams that need real user query-volume data comparable to Google Search Console. OtterlyAI states that AI engines do not provide public query data and that its prompt research produces estimates [71]. Buyers who need traffic attribution or conversion data should look elsewhere, because the platform cannot link AI mentions to visits or leads [73].

Agencies tracking many clients simultaneously may find the economics unfavorable. One independent review states that prompt limits and per-engine add-on costs stack up, making purpose-built agency platforms more economical [74]. Another notes that at Premium with add-ons, cost approaches $787/month, competing directly with broader-feature platforms [74].

Organizations requiring enterprise procurement, invoice payment, SSO, custom terms, and dedicated support are also a poor fit unless they purchase a custom Enterprise plan [71]. Buyers who need real-time monitoring should note that data updates are weekly or daily, not real-time [73]. Buyers who need PDF exports or direct GA4 integration will also find gaps [73].

When Another Option May Be Better

Questions This Section Answers

  • What is a better alternative to OtterlyAI for a buyer who needs confirmed Grok, DeepSeek, and Kimi coverage?
  • When should a buyer choose a different AI visibility platform instead of OtterlyAI?

Another option may be better when verified coverage of specific engines is mandatory. OpenAI recommended choosing another platform when verified coverage of Grok, DeepSeek, Kimi, or other specific engines is mandatory and OtterlyAI cannot confirm availability. Perplexity gave the same guidance for buyers who need contractually explicit coverage of Claude, Grok, DeepSeek, and Kimi.

A different platform may also be better for high prompt volumes. OpenAI noted that buyers needing more than 400 prompts per month may find competing platforms with higher baseline prompts more cost-effective. Perplexity recommended another tool when monitoring volume will exceed 100 to 400 prompts and more generous default limits are needed.

Buyers who need attribution should consider alternatives. Anthropic stated that Trakkr and some full-stack platforms include crawler analytics and conversion tracking that OtterlyAI lacks. Buyers who need immediate execution on optimization recommendations may prefer tools that bundle content production, publishing, and distribution, such as Writesonic or Semrush integrated GEO modules [75].

Enterprise procurement requirements are another trigger. OpenAI recommended a higher-end enterprise vendor when procurement requires SSO, custom security review, contractual commitments, invoice terms, dedicated success support, or custom data retention. Buyers who need independently documented methodology or third-party validation should also look at platforms with published measurement governance [76].

Kimi's response named several independently confirmed alternatives with transparent capabilities and pricing, including SE Visible, Discoverable, Rankscale, Viali, BeVisible, and Meev [77]. Those recommendations come from a platform that could not retrieve OtterlyAI's own site, so they should be treated as platform-reported rather than as a verified comparison.

Questions to Verify Before Buying

Questions This Section Answers

  • What should a buyer confirm with OtterlyAI about engine coverage before signing a contract?
  • How are prompts, countries, and engine runs counted against an OtterlyAI plan allowance?

Buyers should confirm engine coverage in writing before purchase. The specific question is whether the exact subscription includes monitoring for every required engine, particularly Grok, DeepSeek, and Kimi, or only the engines listed on the pricing page [83].

Buyers should also confirm add-on availability and pricing for their target tier. Gemini, Claude, and Google AI Mode are paid add-ons, and buyers should verify United States availability, current add-on prices, and limits for the selected plan [85].

Prompt accounting deserves scrutiny. Buyers should ask how prompts, countries, languages, retries, and engine runs are counted against the plan allowance, since a prompt monitored across multiple countries consumes multiple prompt slots [87].

Data retention and deletion terms matter. Buyers should confirm whether historical answers are retained indefinitely and what data is deleted after cancellation or downgrade, because help documentation states that historical data and tracked engines are deleted after cancellation [88].

Measurement methodology should be documented. Buyers should ask what methodology is used for brand coverage, share of voice, sentiment, competitor ranking, citation detection, and change alerts, and whether the 92% citation accuracy claim has been independently audited [89].

Integration limits should be confirmed. Buyers should verify whether API, MCP, Looker Studio, exports, and agent-analytics limits are sufficient for their reporting volume, and whether API access includes webhook support or only REST polling [83].

Enterprise requirements should be negotiated in advance. Buyers should ask whether Enterprise can provide SSO, data-processing terms, security documentation, invoice payment, custom retention, and a service-level commitment [83].

Finally, buyers should request a current written engine-coverage matrix and a sample report using their own prompts before purchase [83].

Final AI Consensus Verdict

OtterlyAI is a good fit for mainstream AI search visibility monitoring and GEO workflows, especially on Standard for small marketing teams or Premium for larger prompt portfolios. It is only a mixed fit for the broadest seven-engine requirement, because current official materials do not confirm Grok, DeepSeek, or Kimi coverage and because Gemini, Claude, and Google AI Mode require paid add-ons.

Four of seven included platforms named OtterlyAI during ranking discovery, and six returned a usable fit assessment. Fit ratings were strong from Grok and good from OpenAI, Anthropic, and Perplexity, with uncertain ratings from DeepSeek and Kimi. That split reflects a real evidence gap rather than a settled consensus, and buyers should treat the uncertain assessments as a signal to verify coverage directly.

The strongest reason to consider OtterlyAI is the combination of a $29/month entry price, daily prompt monitoring, citation and competitor analytics, and GEO recommendations in one platform. The main limitation is that it monitors rather than improves visibility, cannot attribute AI mentions to traffic or leads, and does not confirm coverage of every engine named in the broadest buyer requirement.

How This Review Was Produced

This review evaluates OtterlyAI only for the AI Visibility Platforms use case. It is not a broad company review. The study used the supplied platform fit-research responses from seven included platforms: openai, anthropic, grok, perplexity, deepseek, kimi, and google. Six of the seven returned a usable fit assessment; google did not return a usable fit assessment in the supplied inputs.

Ranking statistics come from the supplied entity ranking data: four platform mentions, a 57.1% share of included platform responses, an average listed rank of 4.25, a best listed rank of 2, and a final rank of 3. Fit ratings come from the supplied per-platform assessments. Pricing and feature claims come from the supplied citation catalog, which mixes company-owned pages and independent reviews.

Company-owned citations materially outnumber independent citations in the supplied catalog. Company claims such as the 92% citation accuracy figure and the 34% citation-increase claim are labeled as company-reported and were not independently verified. Platform-reported research dates differ from the authoritative run date of 2026-09-19; DeepSeek's assessment is dated 2026-01-15 and was produced without search enabled.

Methodology Limitations

Six of seven included platforms returned a usable fit assessment, so the fit findings are not unanimous. Platform mentions count only platforms that named the entity during ranking discovery, which is a different measure from fit assessment.

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. Company-owned sources materially outnumber independent sources, so company claims should not be read as independently verified.

Platform-reported research dates differ from the authoritative run date. DeepSeek's assessment is dated 2026-01-15 and was produced with search disabled, so its findings are platform-reported rather than retrieved. Kimi reported an official-site retrieval failure and found no independent sources mentioning OtterlyAI, which conflicts with the four platforms that retrieved OtterlyAI-owned pages and independent reviews.

Conflicting product names, pricing, and capabilities were not resolved by guessing. Where sources disagreed, this review describes the conflict and identifies what buyers should verify. Independent evidence on product accuracy, data completeness, and customer outcomes was limited in the sources reviewed.

Explore more ai visibility llm monitoring guidance in the category directory.

Sources

Company-Owned Sources

  • AI Visibility Tracker for ChatGPT & AI Overviews | Rankscale: https://ai-visibility.keyword.com/
  • AI Visibility Software for Brand Monitoring | BeVisible: https://bevisible.app/ai-visibility-software
  • How do Recommendations work in OtterlyAI?: https://help.otterly.ai/ai-recommendations
  • How many search prompts / keywords can I track?: https://help.otterly.ai/amount-searchprompts
  • I want to cancel a subscription - how does that work?: https://help.otterly.ai/cancel-subscription
  • How can I purchase Google AI Mode/Gemini/Claude?: https://help.otterly.ai/how-can-i-purchase-extra-engines
  • What are the plans and the pricing of OtterlyAI?: https://help.otterly.ai/pricing-of-otterlyai
  • What insights can I get from a prompt detail analysis?: https://help.otterly.ai/prompt-detail-analysis
  • How does Prompt Monitoring with OtterlyAI work?: https://help.otterly.ai/search-prompt-monitoring
  • AI Visibility Tracker: Continuous Share-of-Answer Tracking | Meev: https://meev.ai/ai-visibility-tracker
  • AI Search Monitoring Tool: Track ChatGPT, Perplexity & Google AIO: https://otterly.ai/
  • AI Visibility Checker – Track Citations in ChatGPT & More: https://otterly.ai/ai-visibility-checker
  • Meet the OtterlyAI Team – People Behind AI Search Monitoring: https://otterly.ai/blog/meet-the-otterlyai-team-v1/
  • Enterprise AI Search Visibility Tool | OtterlyAI Platform: https://otterly.ai/enterprise-ai-search-visibility-tool
  • Generative Engine Optimization Features: https://otterly.ai/features/
  • AI Search Analytics: Track Mentions & Citations: https://otterly.ai/features/ai-search-analytics
  • OtterlyAI Pricing - Transparent & Simple: https://otterly.ai/pricing/
  • Platform: Discover, Improve, Measure AI Visibility | Viali: https://viali.ai/product/
  • Visibility Tracker — See Every AI Answer | Viali: https://viali.ai/product/visibility-tracking/
  • SE Visible — An AI Visibility Tool Made to Empower Brands: https://visible.seranking.com/
  • AI Search Visibility Tool for ChatGPT & Gemini | Visibly: https://visibly.so/
  • Official pricing and terms source: https://otterly.ai/terms
  • Additional AI research evidence90 records
    1. AI research evidence record anthropic:28-1
    2. AI research evidence record anthropic:28-6
    3. AI research evidence record anthropic:30-4
    4. AI research evidence record anthropic:30-5
    5. AI research evidence record anthropic:6-5
    6. AI research evidence record anthropic:6-6
    7. AI research evidence record kimi:execution_context
    8. AI research evidence record deepseek:c1
    9. AI research evidence record openai:c1
    10. AI research evidence record anthropic:3-1
    11. AI research evidence record anthropic:3-2
    12. AI research evidence record perplexity:c1
    13. AI research evidence record anthropic:9-2
    14. AI research evidence record anthropic:25-1
    15. AI research evidence record anthropic:26-3
    16. AI research evidence record anthropic:26-4
    17. AI research evidence record openai:c12
    18. AI research evidence record anthropic:2-14
    19. AI research evidence record openai:c6
    20. AI research evidence record openai:c7
    21. AI research evidence record anthropic:1-3
    22. AI research evidence record anthropic:11-2
    23. AI research evidence record openai:c3
    24. AI research evidence record openai:c4
    25. AI research evidence record anthropic:22-2
    26. AI research evidence record anthropic:39-11
    27. AI research evidence record openai:c1
    28. AI research evidence record openai:c2
    29. AI research evidence record perplexity:c4
    30. AI research evidence record perplexity:c5
    31. AI research evidence record perplexity:c6
    32. AI research evidence record deepseek:c1
    33. AI research evidence record kimi:execution_context
    34. AI research evidence record anthropic:10-2
    35. AI research evidence record anthropic:22-9
    36. AI research evidence record anthropic:39-3
    37. AI research evidence record anthropic:6-5
    38. AI research evidence record anthropic:6-6
    39. AI research evidence record anthropic:30-5
    40. AI research evidence record anthropic:15-5
    41. AI research evidence record openai:c1
    42. AI research evidence record openai:c8
    43. AI research evidence record anthropic:8-8
    44. AI research evidence record openai:c9
    45. AI research evidence record openai:c10
    46. AI research evidence record anthropic:12-3
    47. AI research evidence record anthropic:17-13
    48. AI research evidence record openai:c5
    49. AI research evidence record anthropic:39-3
    50. AI research evidence record anthropic:38-1
    51. AI research evidence record anthropic:37-1
    52. AI research evidence record openai:c1
    53. AI research evidence record anthropic:3-1
    54. AI research evidence record anthropic:3-2
    55. AI research evidence record perplexity:c1
    56. AI research evidence record anthropic:9-2
    57. AI research evidence record anthropic:7-2
    58. AI research evidence record anthropic:3-16
    59. AI research evidence record anthropic:3-13
    60. AI research evidence record openai:c11
    61. AI research evidence record deepseek:c1
    62. AI research evidence record openai:c1
    63. AI research evidence record anthropic:25-1
    64. AI research evidence record openai:c6
    65. AI research evidence record anthropic:1-3
    66. AI research evidence record anthropic:7-18
    67. AI research evidence record anthropic:8-8
    68. AI research evidence record anthropic:2-4
    69. AI research evidence record anthropic:7-2
    70. AI research evidence record anthropic:41-5
    71. AI research evidence record openai:c1
    72. AI research evidence record openai:c2
    73. AI research evidence record anthropic:39-3
    74. AI research evidence record anthropic:7-2
    75. AI research evidence record anthropic:7-2
    76. AI research evidence record openai:c1
    77. AI research evidence record kimi:visible_seranking
    78. AI research evidence record kimi:bediscoverable_ai_visibility
    79. AI research evidence record kimi:rankscale_tracker
    80. AI research evidence record kimi:viali_product
    81. AI research evidence record kimi:bevisible_software
    82. AI research evidence record kimi:meev_visibility_tracker
    83. AI research evidence record openai:c1
    84. AI research evidence record openai:c2
    85. AI research evidence record openai:c12
    86. AI research evidence record anthropic:26-4
    87. AI research evidence record openai:c8
    88. AI research evidence record openai:c11
    89. AI research evidence record anthropic:10-2
    90. AI research evidence record anthropic:39-3

Independent Sources

  • Otterly.AI Pricing 2026: Plans, Costs & Free Options | AISO Tools: https://aisotools.com/pricing/otterly-ai
  • Otterly AI Pros & Cons 2026 (otterly ai pros cons) | aitoolsatlas.ai: https://aitoolsatlas.ai/tools/otterly-ai/pros-cons
  • OtterlyAI review: Quick start guide and data validation framework | Discovered Labs: https://discoveredlabs.com/blog/otterlyai-review-quick-start-guide-and-data-validation-framework
  • Otterly.AI Pricing 2026: $29 Lite to Custom Enterprise | TMB: https://thatmarketingbuddy.com/pricing/otterly-ai
  • Otterly AI review 2026: features, pricing, and who it's for: https://visible.seranking.com/blog/otterly-ai-review/
  • Otterly.AI Review (2026): Pricing, Features, and Limits | AEO Labs: https://www.aeolabs.ai/blog/otterly-ai-review
  • Otterly.ai Review 2026: Features, Pricing, and Who It's Really Built For | Am I Cited: https://www.amicited.com/reviews/otterly-ai-review/
  • Otterly AI Review: Pricing, Features, and Honest Verdict (2026) | Fokal Guides: https://www.fokal.com/tools/otterly-ai-review/
  • OtterlyAI Pros and Cons | User Likes & Dislikes: https://www.g2.com/products/otterly-ai/reviews?qs=pros-and-cons
  • OtterlyAI Reviews 2026: Details, Pricing, & Features | G2: https://www.g2.com/products/otterlyai/reviews
  • Otterly.AI Review & Pricing 2026: The $29 Entry Point: https://www.get-ryze.ai/blog/otterly-ai-review-pricing-2026
  • The Best AI Visibility Tracking Tools (My Honest Reviews: https://www.position.digital/blog/best-ai-visibility-tracking-tools/
  • Otterly.ai Review: AI Search Visibility Monitoring (2026: https://www.stackmatix.com/blog/otterly-ai-review
  • Best AI Visibility Tools for Brand Mention Tracking (2026: https://www.therankmasters.com/insights/ai-visibility/ai-brand-mention-tracking-tools
  • Additional AI research evidence90 records
    1. AI research evidence record anthropic:28-1
    2. AI research evidence record anthropic:28-6
    3. AI research evidence record anthropic:30-4
    4. AI research evidence record anthropic:30-5
    5. AI research evidence record anthropic:6-5
    6. AI research evidence record anthropic:6-6
    7. AI research evidence record kimi:execution_context
    8. AI research evidence record deepseek:c1
    9. AI research evidence record openai:c1
    10. AI research evidence record anthropic:3-1
    11. AI research evidence record anthropic:3-2
    12. AI research evidence record perplexity:c1
    13. AI research evidence record anthropic:9-2
    14. AI research evidence record anthropic:25-1
    15. AI research evidence record anthropic:26-3
    16. AI research evidence record anthropic:26-4
    17. AI research evidence record openai:c12
    18. AI research evidence record anthropic:2-14
    19. AI research evidence record openai:c6
    20. AI research evidence record openai:c7
    21. AI research evidence record anthropic:1-3
    22. AI research evidence record anthropic:11-2
    23. AI research evidence record openai:c3
    24. AI research evidence record openai:c4
    25. AI research evidence record anthropic:22-2
    26. AI research evidence record anthropic:39-11
    27. AI research evidence record openai:c1
    28. AI research evidence record openai:c2
    29. AI research evidence record perplexity:c4
    30. AI research evidence record perplexity:c5
    31. AI research evidence record perplexity:c6
    32. AI research evidence record deepseek:c1
    33. AI research evidence record kimi:execution_context
    34. AI research evidence record anthropic:10-2
    35. AI research evidence record anthropic:22-9
    36. AI research evidence record anthropic:39-3
    37. AI research evidence record anthropic:6-5
    38. AI research evidence record anthropic:6-6
    39. AI research evidence record anthropic:30-5
    40. AI research evidence record anthropic:15-5
    41. AI research evidence record openai:c1
    42. AI research evidence record openai:c8
    43. AI research evidence record anthropic:8-8
    44. AI research evidence record openai:c9
    45. AI research evidence record openai:c10
    46. AI research evidence record anthropic:12-3
    47. AI research evidence record anthropic:17-13
    48. AI research evidence record openai:c5
    49. AI research evidence record anthropic:39-3
    50. AI research evidence record anthropic:38-1
    51. AI research evidence record anthropic:37-1
    52. AI research evidence record openai:c1
    53. AI research evidence record anthropic:3-1
    54. AI research evidence record anthropic:3-2
    55. AI research evidence record perplexity:c1
    56. AI research evidence record anthropic:9-2
    57. AI research evidence record anthropic:7-2
    58. AI research evidence record anthropic:3-16
    59. AI research evidence record anthropic:3-13
    60. AI research evidence record openai:c11
    61. AI research evidence record deepseek:c1
    62. AI research evidence record openai:c1
    63. AI research evidence record anthropic:25-1
    64. AI research evidence record openai:c6
    65. AI research evidence record anthropic:1-3
    66. AI research evidence record anthropic:7-18
    67. AI research evidence record anthropic:8-8
    68. AI research evidence record anthropic:2-4
    69. AI research evidence record anthropic:7-2
    70. AI research evidence record anthropic:41-5
    71. AI research evidence record openai:c1
    72. AI research evidence record openai:c2
    73. AI research evidence record anthropic:39-3
    74. AI research evidence record anthropic:7-2
    75. AI research evidence record anthropic:7-2
    76. AI research evidence record openai:c1
    77. AI research evidence record kimi:visible_seranking
    78. AI research evidence record kimi:bediscoverable_ai_visibility
    79. AI research evidence record kimi:rankscale_tracker
    80. AI research evidence record kimi:viali_product
    81. AI research evidence record kimi:bevisible_software
    82. AI research evidence record kimi:meev_visibility_tracker
    83. AI research evidence record openai:c1
    84. AI research evidence record openai:c2
    85. AI research evidence record openai:c12
    86. AI research evidence record anthropic:26-4
    87. AI research evidence record openai:c8
    88. AI research evidence record openai:c11
    89. AI research evidence record anthropic:10-2
    90. AI research evidence record anthropic:39-3

Verify this research

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

Study date
September 19, 2026
Platforms analyzed
7
Source records
41
Ranking mentions
4 of 7
Platform share
57%
Final consensus rank
#3

Research trail and source mix

Configured platforms

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

Source mix

15 independent · 26 company-owned

Evidence support

36 direct · 5 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 c77e36be63ce5a6c82362a365b6953f0c00ccb7c16bbcc1569523a375daf9075