Answer Capsule
Conductor is a strong-to-good fit for large enterprise teams that want AI visibility measurement integrated with SEO, content, and technical monitoring, but the fit is conditional. Two of seven platforms named Conductor during the ranking stage — 28.6% of included platform responses — at an average listed rank of 6.0 and a best listed rank of 6. The strongest reason to consider it is the published Enterprise capacity: 2,500+ AI Search Credits per year, 125,000+ analyzed pages, 60,000 tracked keywords, 75+ tracked competitors, and 10+ tracked websites, plus multi-engine AI tracking and a Data API [1]. The main limitation is that Conductor publishes no dollar pricing, and its AI-credit economics, prompt limits, and historical retention are not fully disclosed [4].
Research Snapshot
| Field | Finding |
|---|---|
| Platform mentions in ranking stage | 2 of 7 included platforms (anthropic, perplexity) |
| Share of included platform responses | 28.6% |
| Average listed rank | 6.0 |
| Best listed rank | 6 |
| Relevant product/model/plan | Conductor Enterprise Plan / Conductor Intelligence within the enterprise AEO + SEO suite |
| Overall use-case fit | Strong (openai, grok); Good (anthropic, google, perplexity); Mixed (deepseek); Weak (kimi) |
| Research date | 2026-09-19 |
Why Conductor Qualified for This Study
Questions This Section Answers
- Why did Conductor qualify for this enterprise AI visibility platform study?
- How many AI platforms named Conductor in the ranking stage for enterprise AI visibility?
Conductor qualified because two of the seven included platforms named it during ranking discovery, and those two placed it at rank 6 — enough to clear the two-mention inclusion threshold for this study. The remaining five platforms evaluated Conductor's fit for the use case without naming it in their ranked lists, which is why the mention count (2) is lower than the number of platforms that produced fit research (7).
The qualification is narrow rather than emphatic. A rank of 6 on both naming platforms means Conductor entered the comparison set as a lower-ranked option, not as a top pick. Its inclusion rests on the fact that it was named at all, not on strong placement.
Conductor is an enterprise SEO and content platform that has extended into AI search visibility, sometimes described as answer engine optimization (AEO). It positions itself as an enterprise AEO platform with AI visibility tracking, unified search data, and more than 10 years of proprietary search data [6]. Independent coverage describes it as an enterprise SEO/content platform with publicly marketed AI-search visibility capabilities [7].
Because the ranking stage produced only two mentions, this review treats Conductor as a qualified but not consensus-leading option. Buyers comparing it against higher-ranked platforms should weigh the fit evidence below rather than the rank alone.
The Product, Model, Plan, or Service Most Relevant to AI Visibility Platforms for Enterprise Companies
Questions This Section Answers
- Which Conductor plan should a large enterprise choose for multi-brand AI visibility tracking?
- Is Conductor Intelligence or the full Conductor Enterprise suite the right product for enterprise AI visibility?
The relevant offering is the Conductor Enterprise Plan, which spans Conductor Intelligence (AI and traditional search insights), Conductor Creator (AI-driven content generation), and Conductor Monitoring (24/7 site auditing) [9]. Conductor Intelligence is the module that carries the AI visibility work: it reports AI visibility tracking, mentions, citations, sentiment, competitive intelligence, analytics integrations, multi-domain enterprise reporting, and millions-of-pages scale [11].
Conductor describes its platform as an enterprise AEO platform with AI visibility tracking, unified search data, and 10+ years of proprietary search data [12]. Its AI Search Performance product distinguishes brand mentions from website citations and adds sentiment and competitive visibility analysis [13]. The platform reports coverage across Google AI Overviews, Google AI Mode, ChatGPT, Copilot, Gemini, and other AI search platforms [14]. One independent comparison states Conductor tracks nine AI engines — ChatGPT Auto, ChatGPT Search, Claude Sonnet, Gemini, Google AI Mode, Google AI Overviews, Grok Auto, Microsoft Copilot, and Perplexity — but does not cover DeepSeek or Meta AI [15].
Conductor also markets a native LLM apps, developer infrastructure, and turnkey agents suite intended to help brands scale visibility across AI-driven search [16]. The Data API and MCP Server provide programmatic access for BI dashboards, automated reporting, agents, and AI workflows [17].
One conflict is worth flagging: a platform-reported comparison states Conductor Enterprise is priced at roughly $8,000–$14,000 per month [20], while other third-party procurement sources describe enterprise contracts at $150,000+ per year [21]. These figures are not reconciled in the supplied evidence, and no official Conductor page confirms either range.
What the AI Platforms Agreed About
Questions This Section Answers
- What do AI platforms agree Conductor does well for enterprise AI visibility?
- Does Conductor support multi-engine AI visibility tracking and citation analysis for large enterprises?
The clearest agreement is on scale and integration. Multiple platforms describe Conductor as an enterprise-grade platform that combines AI visibility with traditional SEO, content, and technical monitoring rather than offering a standalone mention tracker [22]. Independent coverage describes it as built for enterprise-scale organic search operations rather than lean teams [25].
Platforms also broadly agree on published Enterprise capacity. Conductor's pricing page lists 2,500+ AI Search Credits per year, 125,000+ analyzed pages, 60,000 tracked keywords, 75+ tracked competitors, and 10+ tracked websites [26]. Independent coverage repeats the 60,000+ tracked keyword figure for the Enterprise tier [30].
Agreement extends to AI visibility mechanics. Platforms describe mention and citation tracking, sentiment analysis, and competitive share-of-voice reporting [31]. One independent review describes a Competitor Intelligence module that tracks who appears alongside a brand on every prompt and surfaces suggested competitors based on co-mentions, plus Citation Analytics showing which domains AI engines pull from [34].
There is also agreement on enterprise deployment features: unlimited user licenses across plans [37], reported SOC 2 Type 2, ISO 27001, and ISO 42001 certifications [39], and a Data API positioned for BI and automated reporting [41].
Agreement among platforms does not establish product quality. Most of these findings trace back to Conductor's own materials, and no independent benchmark validating comparative accuracy was located in the supplied evidence.
Where the AI Platforms Disagreed or Were Uncertain
Questions This Section Answers
- Why do AI platforms disagree about whether Conductor is a strong fit for enterprise AI visibility?
- Is Conductor a purpose-built AI visibility platform or an SEO suite with AI features?
Fit ratings diverged sharply. OpenAI and Grok rated Conductor a strong fit; Anthropic, Google, and Perplexity rated it good; DeepSeek rated it mixed; and Kimi rated it weak (openai, grok, anthropic, google, perplexity, deepseek, kimi). That spread is the single most important signal in this review.
The disagreement centers on whether Conductor is a purpose-built AI visibility platform or an SEO suite with AI features bolted on. Kimi's assessment states Conductor lacks purpose-built LLM tracking, citation analysis, and AI visibility intelligence, and positions it as primarily an SEO platform (kimi). DeepSeek describes the AI-visibility feature depth, prompt-scale limits, and historical AI-answer data as not independently verifiable from public sources (deepseek). Google's assessment notes the AI module was added in 2024 and is integrated into the existing organic platform, making it a lower-friction add-on for existing customers [42].
Historical data is a second fault line. Conductor's own API documentation states the platform retains only 32 days of daily data, and no daily data is returned via API for requests more than 32 days from the current date [43]. One platform treats this as a significant limitation for multi-year trend analysis [45]. Other platforms describe historical tracking more favorably without citing a retention figure [46]. The scope of historical data available through the UI, as opposed to the API, is not explicitly documented in the supplied sources.
Automation depth is a third area of uncertainty. One independent review states Conductor cannot build a Monday-morning report combining AI visibility, GA4 sessions, GSC top movers, and HubSpot deal data inside the platform, nor webhooks that trigger a content brief when a competitor publishes [48]. Another notes Conductor shows citation rates but lacks an automated execution layer to fix or change content [50], and a third states it provides guidance and AI drafts but leaves optimization and publishing to external CMS tools [51].
Pricing is the fourth conflict. Conductor's own pricing page describes a usage-based model that aligns value to price [52], while third-party procurement sources consistently report fully custom-quoted annual subscriptions with no usage-based components [54]. Third-party estimates range from roughly $26,800 to $500,000+ annually, with a median near $48,950 for mid-market and $150,000+ typical for multi-domain enterprises [56].
Use-Case-Specific Features and Capabilities
Questions This Section Answers
- Does Conductor support large prompt sets, role-based reporting, and executive dashboards for enterprise AI visibility?
- How does Conductor handle multi-brand, multi-market AI visibility measurement?
Conductor's fit for this use case rests on seven capabilities the study criteria named: large prompt sets, historical data, role-based reporting, competitive intelligence, citation analysis, executive reporting, and scalable measurement.
Large prompt sets. Conductor reports configurable tracking by audience persona, search intent, market, local competitors, and region, including separate configurations for markets such as the United States, United Kingdom, and Germany [60]. The public materials do not specify the maximum number of prompts, prompt refresh cadence, or per-prompt credit consumption (openai). The Enterprise tier lists 60,000 tracked keywords [61], but the relationship between tracked keywords and AI prompts is not defined publicly.
Historical data. This is the weakest area. Conductor's API documentation states 32 days of daily data retention [63]. Conductor separately states its unified data engine contains more than 10 years of proprietary search data [65], but the public materials do not clearly state the retention period or historical depth specifically for AI visibility observations (openai).
Role-based reporting. Conductor emphasizes unlimited user licenses on all plans, enabling insights to be shared across marketing, product, and web development teams [66]. The Enterprise plan is described as adding automated user provisioning, an SLA for dedicated support, and fine-grained security controls [68]. Independent coverage notes that 10+ websites monitored and role-based access control matter once managing access across multiple accounts or internal teams [69]. Public materials do not specify role-permission granularity, dashboard limits, or executive-report distribution options (openai).
Competitive intelligence. Conductor reports competitor market-share analysis, competitor content-strategy analysis, competitive gaps, and comparison across AI and traditional search [70]. The public materials do not independently validate the accuracy or methodology of the reported share-of-voice metrics (openai).
Citation analysis. Conductor reports analysis of mentions, website citations, sentiment, AI referral traffic, engagement, conversions, and revenue, including integrations such as Google Analytics and Adobe [72]. The depth of citation-level attribution should be confirmed in a demonstration (openai).
Executive reporting. Conductor says users can build custom reports to share insights and demonstrate ROI [73], and positions Enterprise for advanced reporting and governance [62]. One independent user review notes that Conductor's reporting and dashboard features are lacking compared to other AI citation tools [74] — a direct conflict with the vendor positioning.
Scalable measurement. Conductor states it can aggregate reporting across millions of pages and multiple domains [70]. The Data API provides AI visibility, competitive share-of-voice, content signals, and website health data for BI dashboards and automated reporting [75]. The default API call rate limit is 2 calls per second or 5,000 calls per day [76], and full Data API access is an Enterprise-only feature [77].
Pricing, Fees, Contracts, and Ongoing Costs
Questions This Section Answers
- How much does Conductor Enterprise cost per year for enterprise AI visibility, and is pricing public?
- What contract terms, overage fees, and implementation costs should a buyer expect from Conductor?
Conductor publishes no dollar pricing. The pricing page shows three tiers with feature limits but no dollar figures, and every tier routes to "Request a Demo" or "Contact Sales" [78]. Conductor describes its model as value-focused and usage-based, with pricing built around value rather than seats [80].
Third-party procurement data fills part of the gap, with wide disagreement. Reported ranges include approximately $30,000 to $150,000+ per year with a median near $49,000 [82]; $26,800 to $500,000+ annually with a median of $48,950 for mid-market [84]; and $150,000+ for enterprises managing multiple domains with dedicated customer success [85]. One source reports entry-level tiers at $26,800–$45,000, mid-market at $48,000–$85,000, and enterprise at $150,000–$500,000+ [86]. A platform-reported competitor comparison states $8,000–$14,000 per month [87], which conflicts with the annual figures.
Implementation and professional services can add 1.5x to 2x the first-year subscription cost [88]. Pricing is customized based on the number of domains, keyword tracking volume, user seats, and specific modules required [89]. AI Search Credits are included only in Growth and Enterprise tiers, not Essentials; the Growth tier includes 2,500 credits per year [90].
Contract terms are sales-led. Most contracts are structured as annual or multi-year subscriptions with pricing negotiated case-by-case [92]. One source states Conductor offers a 3-week full-featured trial with no credit card required but no ongoing free plan [94]; another states there is no free plan, no free trial, and no money-back guarantee [95]. These two claims conflict directly and should be resolved with Conductor before purchase.
Public materials do not state contract length, billing frequency, renewal mechanics, cancellation rights, notice periods, service-level commitments, or treatment of unused credits (openai). Overage rates for AI Search Credits, additional domains, users, or integrations are not publicly quantified (openai).
Best Suited For
Questions This Section Answers
- Who is Conductor best suited for among enterprise AI visibility buyers?
- Is Conductor worth it for a large enterprise managing multiple brands and markets?
Conductor is best suited to large enterprises managing multiple brands, domains, markets, and business units that want AI visibility measurement connected to SEO, content, and technical monitoring in one platform. Independent coverage describes it as built for enterprise-scale organic search operations [96] and best for medium to large organizations with significant organic search revenue, multi-page sites, and dedicated SEO/content teams [97].
It fits organizations that need unlimited user seats to distribute visibility data across departments [98], that require API and BI integration for centralized reporting [100], and that have security review requirements — Conductor reports SOC 2 Type 2, ISO 27001, and ISO 42001 certifications [102].
It also fits buyers tracking high keyword volumes. Independent analysis states unlimited keyword tracking delivers 30–50% cost advantages for organizations tracking 50,000+ keywords compared to competitors' enterprise tiers [103].
Named customers include SAP, FedEx, Mastercard, Citi, Airbnb, and 1-800-Contacts, and Conductor was named a Leader in the 2025 Forrester Wave for SEO platforms [105]. These are vendor-adjacent and third-party-reported claims, not independently verified in this study.
Probably Not Best Suited For
Questions This Section Answers
- Who should not choose Conductor for enterprise AI visibility?
- Is Conductor a poor fit for buyers who need transparent pricing or long historical AI data?
Conductor is probably not the best fit for buyers whose primary requirement is deep, standalone AI-answer analytics with transparent pricing. One platform rates it a weak fit specifically because it lacks purpose-built LLM tracking, citation analysis, and AI visibility intelligence (kimi). Another rates it mixed, citing thin independently verifiable evidence on prompt-set limits, historical AI-answer data, and citation analysis depth (deepseek).
It is also a poor fit for teams needing persistent historical AI visibility data. Conductor's API documentation states 32 days of daily data retention [106], which one platform calls a significant limitation for multi-year trend analysis and quarterly benchmarking [108].
Buyers who need transparent, self-serve pricing should look elsewhere. Conductor publishes no public price, and every tier routes to sales [109]. Independent coverage states no price transparency plus no AEO tracking at the base tier makes Conductor a harder sell outside a dedicated enterprise budget [112].
Teams needing closed-loop content execution — automatically rewriting and republishing content to fix AI citation gaps — are also a poor fit. Independent reviews state Conductor stops at reporting and guidance, leaving optimization and publishing to external CMS tools [113].
Smaller organizations are explicitly out of scope: independent coverage states Conductor is not best for very small businesses, freelancers, or organizations with simple, low-traffic sites or limited SEO budgets [115].
When Another Option May Be Better
Questions This Section Answers
- What is a better alternative to Conductor for a buyer who needs standalone AI visibility tracking?
- When should an enterprise choose a specialist AI visibility tool instead of Conductor?
A standalone AI visibility specialist may be preferable when the primary requirement is deep AI answer monitoring rather than an integrated SEO, content, analytics, and technical platform (openai). One platform states a standalone specialist such as Profound may be preferable in that scenario, with comparative fit and pricing validated directly (openai).
A lower-cost or self-serve platform may be preferable for a single brand, limited prompt set, or proof-of-concept where executive reporting, APIs, and multi-market governance are not required (openai). One platform cites Capital's Prompt Volumes feature, which reveals how many users ask specific queries across AI platforms, with pricing starting at $99/month for ChatGPT-only monitoring and $399/month for three-platform tracking, requiring a custom Enterprise plan for full 10+ platform coverage [116].
Teams needing persistent historical data beyond 32 days for multi-year trend analysis and quarterly benchmarking should evaluate alternatives (anthropic). One platform recommends Analyze AI when budget sits beyond Conductor's investment level and notes it provides a programmable layer Conductor does not have [119].
Organizations requiring deep custom reporting automation with webhooks, API extensions, and programmatic data pipelines without enterprise-only limitations should compare options (anthropic). One independent review states that for enterprise teams running mature SEO automation stacks, this is where Conductor stops scaling [121].
An existing enterprise SEO suite may be preferable when the buyer already has validated SEO, analytics, and reporting infrastructure and wants only an incremental AI visibility module (openai). Platform-reported alternatives named in the supplied research include Georion Enterprise at $4,999/month with 6-engine tracking, Ayzeo Enterprise at $6,000/month with 300+ projects and three-layer reporting, and UltraScout AI Enterprise from roughly £5,000/month with 8+ platform tracking [122]. These are vendor-published claims from competing platforms and were not independently verified.
Questions to Verify Before Buying
Questions This Section Answers
- What should a buyer confirm with Conductor before signing an enterprise AI visibility contract?
- Which Conductor Enterprise terms, limits, and capabilities need written confirmation?
The supplied research surfaces a consistent set of verification items. Buyers should get written answers before committing.
Credit economics. What is the exact definition and consumption rate of an AI Search Credit, and how many prompts, engines, markets, refreshes, and historical snapshots are included (openai)? How are AI Response Credits metered, and what happens when credits are exhausted (perplexity)? What are the exact custom limits and overage costs for keyword, page, and AI credit volumes (grok)?
Capacity limits. What are the maximum configurable prompts, competitors, domains, brands, markets, users, dashboards, and API calls under the quoted Enterprise package (openai)? What is the multi-brand project limit and user role hierarchy (kimi)?
Engine coverage. What AI engines, model versions, geographic locations, languages, personalization states, and answer formats are actually covered, and how often is coverage changed (openai)? Are there plans to support newly prominent AI models like DeepSeek or Meta AI (google)?
Historical data. How far back does AI visibility history go, and can raw prompt responses, citations, URLs, timestamps, and methodology metadata be exported through the UI or API (openai)? What is Conductor's policy on historical data retention beyond 32 days, and can historical data be archived or accessed through non-API channels (anthropic)?
Governance. What role-based permissions, SSO/SCIM, approval workflows, business-unit isolation, audit logs, scheduled executive reports, and white-label options are included (openai)? Does Enterprise include RBAC, SSO/SAML, SCIM, audit logs, and data/API access in the base package (perplexity)?
Measurement methodology. How are mentions, citations, sentiment, share of voice, and competitive market share calculated, deduplicated, sampled, and validated (openai)?
Commercial terms. What is the exact annual cost for the organization's specific configuration, and can a formal quote be obtained in writing (anthropic)? What are the contract length, cancellation terms, renewal mechanics, price-escalation terms, and onboarding timeline (grok, perplexity)? What are the implementation, onboarding, and professional services costs, and how are the 1.5–2x first-year costs allocated (anthropic)?
Trial and guarantee. Does Conductor offer a 3-week full-featured trial with no credit card required [125], or is there no free trial and no money-back guarantee [126]? These supplied claims conflict and should be resolved directly.
References. Can Conductor provide independent validation, customer references in comparable industries, or a proof-of-concept using the buyer's brands, markets, competitors, and executive reporting requirements (openai)?
Final AI Consensus Verdict
Conductor is a qualified but not consensus-leading fit for AI Visibility Platforms for Enterprise Companies. Two of seven included platforms named it in the ranking stage at rank 6, and fit ratings ranged from strong (openai, grok) to weak (kimi), with good (anthropic, google, perplexity) and mixed (deepseek) in between.
The case for Conductor rests on published Enterprise capacity, multi-engine AI tracking, citation and sentiment analysis, competitive intelligence, unlimited user seats, reported security certifications, and a Data API for BI and automated reporting [127]. Most of this evidence is vendor-reported.
The case against rests on four unresolved issues: no public dollar pricing and conflicting third-party estimates [133]; 32-day daily data retention via API [136]; limited closed-loop automation and custom reporting hooks [137]; and no independent benchmark validating comparative accuracy (openai). One independent user review also reports that reporting and dashboards lag other AI citation tools [140], which conflicts with vendor positioning.
For a large enterprise that already runs an SEO and content operation and wants AI visibility folded into that stack, Conductor is a reasonable shortlist candidate — conditional on validating credit economics, prompt capacity, historical retention, permissions, and total cost in a scoped proposal. For a buyer whose primary need is deep standalone AI-answer analytics with transparent pricing, the supplied evidence points toward specialist alternatives.
How This Review Was Produced
This review evaluates Conductor only for the AI Visibility Platforms for Enterprise Companies use case. It draws on fit-research responses from seven AI platforms — OpenAI, Anthropic, Google, Grok, Perplexity, DeepSeek, and Kimi — collected for a study dated 2026-09-19. Two of those platforms named Conductor during ranking discovery; all seven produced fit assessments.
The review aggregates platform-reported findings, preserves conflicts rather than resolving them, and labels vendor-owned evidence as such. No product testing, customer interviews, or independent benchmark validation was performed. Where a claim traces only to Conductor's own materials, it is described as company-reported.
For the full comparison set, see the AI Visibility Platforms for Enterprise Companies consensus index. Broader coverage of this software category is available in the ai visibility llm monitoring directory.
Methodology Limitations
Several limitations constrain this review.
Ranking mentions are narrow. Only two of seven platforms named Conductor during ranking discovery, so the rank statistics rest on a small sample. A rank of 6 on both naming platforms should not be read as a broad consensus position.
Most evidence is vendor-reported. Conductor's product pages, pricing page, API documentation, and partner pages supply the majority of capability claims. Independent sources exist but frequently repeat vendor figures rather than verify them.
Pricing is unresolved. Conductor publishes no dollar pricing. Third-party estimates conflict materially — from roughly $26,800 to $500,000+ annually, plus a platform-reported $8,000–$14,000 per month figure that does not reconcile with the annual ranges. No estimate in this review should be treated as authoritative.
Historical retention is documented only for the API. The 32-day daily data limit comes from Conductor's Reporting API documentation. The scope of historical data available through the UI-based Conductor Intelligence module is not explicitly documented in the supplied sources.
Research dates differ. The authoritative study date is 2026-09-19. One platform's research is dated 2026-02-14, and platform-reported dates are provenance metadata that do not independently prove freshness.
No independent accuracy validation. No benchmark was located that establishes comparative accuracy across engines, prompts, citations, or markets. Conductor's claims about accuracy and enterprise leadership are company claims.
URLs were not independently validated. The supplied source URLs were collected from platform responses and were not independently verified at the writer stage.
Competing-platform pricing is vendor-published. Alternative pricing cited in this review (Georion, Ayzeo, UltraScout AI, Capital) comes from those vendors' own materials or from reviews citing them, and was not independently verified.
Sources
Company-Owned Sources
- Enterprise AI Visibility Platform - Multi-Brand Top-Down Reporting | Ayzeo: https://ayzeo.com/use-cases/enterprise
- Enterprise AI Visibility Platform: SSO, SLA, Scale | Georion: https://georion.app/solutions/enterprise
- Conductor Intelligence's Reporting API: https://support.conductor.com/en_US/conductor-intelligence-apis/conductor-intelligence-s-reporting-api
- Enterprise AI Visibility & Strategic Intelligence | UltraScout AI: https://ultrascout.ai/platform/enterprise
- Enterprise AI Visibility & Strategic Intelligence Platform | UltraScout AI: https://ultrascout.ai/platform/intelligence
- Plans for enterprises at every stage of growth - Conductor: https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEtQdQ4q9cKxY0y6HCIV7eiT-WJNlrzzqDem_NZN9i5TO-t3UGlQ8AjHycBsbdvEa5YeKoAhwY8iDdtxgpllKF6HW_diC63MMgYKXMntDVuvdC65yDwhWM=
- What is AI Visibility and How do I Measure It? - Conductor: https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF1mHcjYtZO8XebJx8OuZTNsbe4KTb8iYadkgt9oCRXOSLxSMPTuGO7AZx2lF-7cmJTFQMU8YmpsllHj_TNv6Z5EUDsQW1cRPufbcOOl8qWjGoAJaW4-458EvpI-gF-qGM-XM7YsraUPR7cVp1AwQ==
- Pricing | Conductor: https://www.conductor.build/pricing
- Conductor — Win in AI Search: https://www.conductor.com/
- What is Conductor AI? A Breakdown for Enterprise Marketing Teams: https://www.conductor.com/academy/conductor-ai/
- Conductor AI: Understanding Your Brand's Visibility in AI Search: https://www.conductor.com/docs/platform/learning-center/library/conductor-ai-understanding-your-brands-visibility-in-ai-search/
- Partners - Meet Our Platform Collaborators: https://www.conductor.com/partners/
- AI Search Performance | Conductor Features: https://www.conductor.com/platform/features/ai-search-performance/
- Multi-Engine AI Visibility & Tracking: https://www.conductor.com/platform/features/ai-search-performance/ai-engine-llm-coverage/
- Mention & Citation Tracking for AI Visibility: https://www.conductor.com/platform/features/ai-search-performance/ai-mention-citation-tracking/
- Intelligent Prompt Generation & Tracking: https://www.conductor.com/platform/features/ai-search-performance/ai-tracking-customization/
- Conductor Data API: Build with AEO Search Intelligence: https://www.conductor.com/platform/features/data-api/
- Enterprise AEO & SEO Platform | Conductor Intelligence: https://www.conductor.com/platform/intelligence/
- Plans for enterprises at every stage of growth: https://www.conductor.com/pricing/
- Official pricing and terms source: https://www.conductor.com/legal/terms-of-use/
Additional AI research evidence140 records
- AI research evidence record openai:c2
- AI research evidence record openai:c1
- AI research evidence record openai:c5
- AI research evidence record anthropic:12-1
- AI research evidence record anthropic:41-1
- AI research evidence record openai:c0
- AI research evidence record deepseek:c1
- AI research evidence record deepseek:c3
- AI research evidence record anthropic:4-12
- AI research evidence record anthropic:25-3
- AI research evidence record openai:c1
- AI research evidence record openai:c0
- AI research evidence record openai:c4
- AI research evidence record openai:c6
- AI research evidence record google:1.1.6
- AI research evidence record anthropic:3-4
- AI research evidence record anthropic:43-5
- AI research evidence record anthropic:43-6
- AI research evidence record anthropic:43-7
- AI research evidence record kimi:georion-1
- AI research evidence record anthropic:17-4
- AI research evidence record openai:c1
- AI research evidence record anthropic:25-3
- AI research evidence record anthropic:27-1
- AI research evidence record anthropic:6-10
- AI research evidence record openai:c2
- AI research evidence record anthropic:13-2
- AI research evidence record grok:0
- AI research evidence record perplexity:c1
- AI research evidence record anthropic:18-5
- AI research evidence record openai:c4
- AI research evidence record anthropic:22-6
- AI research evidence record anthropic:22-9
- AI research evidence record anthropic:26-2
- AI research evidence record anthropic:26-8
- AI research evidence record anthropic:26-9
- AI research evidence record anthropic:4-13
- AI research evidence record anthropic:27-2
- AI research evidence record openai:c5
- AI research evidence record openai:c7
- AI research evidence record anthropic:43-5
- AI research evidence record google:1.1.3
- AI research evidence record anthropic:41-1
- AI research evidence record anthropic:41-2
- AI research evidence record anthropic:6-2
- AI research evidence record grok:3
- AI research evidence record grok:15
- AI research evidence record anthropic:26-12
- AI research evidence record anthropic:26-13
- AI research evidence record google:1.1.7
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:13-3
- AI research evidence record anthropic:11-6
- AI research evidence record anthropic:12-14
- AI research evidence record anthropic:17-3
- AI research evidence record anthropic:17-4
- AI research evidence record anthropic:12-2
- AI research evidence record anthropic:12-6
- AI research evidence record openai:c9
- AI research evidence record anthropic:18-5
- AI research evidence record openai:c2
- AI research evidence record anthropic:41-1
- AI research evidence record anthropic:41-2
- AI research evidence record openai:c0
- AI research evidence record anthropic:4-13
- AI research evidence record anthropic:27-2
- AI research evidence record anthropic:10-1
- AI research evidence record anthropic:18-18
- AI research evidence record openai:c1
- AI research evidence record anthropic:22-9
- AI research evidence record openai:c4
- AI research evidence record perplexity:c3
- AI research evidence record anthropic:23-9
- AI research evidence record openai:c7
- AI research evidence record anthropic:41-12
- AI research evidence record anthropic:18-19
- AI research evidence record anthropic:12-5
- AI research evidence record anthropic:12-13
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:13-3
- AI research evidence record anthropic:12-2
- AI research evidence record anthropic:12-6
- AI research evidence record anthropic:17-3
- AI research evidence record anthropic:17-4
- AI research evidence record google:1.2.4
- AI research evidence record kimi:georion-1
- AI research evidence record anthropic:17-8
- AI research evidence record anthropic:11-1
- AI research evidence record anthropic:18-17
- AI research evidence record google:1.2.1
- AI research evidence record anthropic:11-6
- AI research evidence record anthropic:24-5
- AI research evidence record anthropic:14-1
- AI research evidence record anthropic:18-3
- AI research evidence record anthropic:6-10
- AI research evidence record anthropic:14-3
- AI research evidence record anthropic:4-13
- AI research evidence record anthropic:27-2
- AI research evidence record anthropic:43-5
- AI research evidence record openai:c7
- AI research evidence record openai:c5
- AI research evidence record anthropic:17-13
- AI research evidence record anthropic:17-11
- AI research evidence record anthropic:6-8
- AI research evidence record anthropic:41-1
- AI research evidence record anthropic:41-2
- AI research evidence record anthropic:6-2
- AI research evidence record anthropic:12-5
- AI research evidence record anthropic:12-13
- AI research evidence record anthropic:12-14
- AI research evidence record anthropic:18-1
- AI research evidence record google:1.1.7
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:14-4
- AI research evidence record anthropic:8-4
- AI research evidence record anthropic:8-5
- AI research evidence record anthropic:8-6
- AI research evidence record anthropic:6-3
- AI research evidence record anthropic:6-4
- AI research evidence record anthropic:26-16
- AI research evidence record kimi:georion-1
- AI research evidence record kimi:ayzeo-1
- AI research evidence record kimi:ultrascout-1
- AI research evidence record anthropic:14-1
- AI research evidence record anthropic:18-3
- AI research evidence record openai:c2
- AI research evidence record openai:c6
- AI research evidence record openai:c4
- AI research evidence record anthropic:4-13
- AI research evidence record openai:c5
- AI research evidence record anthropic:43-5
- AI research evidence record anthropic:12-1
- AI research evidence record anthropic:17-3
- AI research evidence record kimi:georion-1
- AI research evidence record anthropic:41-1
- AI research evidence record anthropic:26-12
- AI research evidence record anthropic:26-13
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:23-9
Independent Sources
- Conductor Platform: Enterprise SEO & AI Content Intelligence: https://adambernard.com/kb/tools/seo-optimization/tools-seo-optimization-conductor/
- Conductor Pricing 2026: Plans, Costs & What You'll Actually Pay: https://checkthat.ai/brands/conductor/pricing
- best llm visibility tools 2026: https://contently.com/2026/03/18/best-llm-visibility-tools-2026/
- Conductor review 2026: pricing, pros and cons: https://growthmanager.ai/compare/conductor
- Conductor Review 2026: Pricing, Features, Pros & Cons: https://saleshive.com/vendors/conductor
- Conductor Pricing 2026: Custom Plans, No Free Trial: https://thatmarketingbuddy.com/pricing/conductor
- Conductor Review 2026: https://tooliverse.ai/tools/conductor
- Conductor Pricing 2026: No Public Price, ~$30k to $150k+/yr: https://trakkr.ai/reviews/conductor-review/pricing
- Frase vs Conductor: AI Visibility That Fixes Content: https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEa2Suoog625a3PErs8a9BRfMDf0qC4RXy-AORJZyTwFmQ5OinK1BB2VYfmWRxPgOTgWF1qCXON0tW76hb0YuticD-r_kdxl347xYNRkn22yerMGEFUwA==
- Conductor Review 2026: Pricing, Features, Pros & Cons - SalesHive: https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEPyrSmstbL2weC6KiOPy6KHGuSraW0sJFWlQSCm0gOBMkqRI_IO7G4rJZldkeXhvkAN3KEIivLD-azEChwZYhiow4ARHZw3vG642HTQy51O82phi_SkDphtN76pw==
- Conductor AI Visibility: AI visibility vendor profile | GEO Compass: https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF5j-j0gYje08wfgu7qOcaEf6PETeSRfsiEghJwccBrwZN7xoRRvuSamIBOZvkQ9Ksi_IJgCvVwX6M1lPn0S2jiaaUju0AyYZhpd1OOnGfscq2zJFqH90TNeaPM8XXRRMWSRMtD6rC591nTGdtrCFB0ZH9w4f4yS4sa
- Conductor Pricing 2026: Plans, Costs & What You'll Actually Pay - CheckThat.ai: https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGGk6SRwRdyUU2TT48hfnRC2XBnu5rdD7SXjUt7makgkDeU1ZjXWxACb0qF8XRmycn3ZIqUD_oQqgryydXdkA860CGmwSHugFyg9LSMzen-AYD6PktqDJn3K643eR1lXYKcjw==
- Conductor AI Review 2026: Deep Dive into Features, Pricing & Better Alternatives: https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH0Zm1ddEZHkFuygcqKttfTNWPcVfQ_tcuf18Gw260nCAygNcyZIndQeOE2usS6eIhRg8BkuLgg4S7DAuCA7XC9X9A4MfEzLQ18RVg5DfMRgdDFlUOqrhJIrY7KtLLFdp0Qt_U=
- Conductor Review 2026: Pricing and AI Credits | EchoWi: https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH8BxRDugM_kAkoE7b793eSqf7YsF9PhCQ2VvcF0UoZQy_iw4IyYJ8gsfZiKf3vMFBScFZ3WXhGjfwFdZQOj81p-QW3B6g-Y-BuMkXdw38dwgOv1bG9s2QKYDuHzGk=
- KIME vs Conductor: A 2026 AI visibility tool comparison: https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHhvmvyM2PphB5uQg35ONvM1INGDuGZvv6GMVVPxIHREsJnG0hJkcEuF0e7fro_cGzPHdH-W3UHhQR8AOlrkUtkU1V9YG1nAbIxHztebNx9s1-J3jiGfsD3UKZ2-7cL5HlhWQ==
- What Is Conductor? Enterprise AEO & SEO Platform: https://www.ansvisor.com/ai-visibility-glossary/conductor
- Conductor Pricing (Capterra: https://www.capterra.com/p/137989/Conductor/
- Conductor (formerly Searchmetrics): Use-Cases, Insights: https://www.cuspera.com/products/conductor-formerly-searchmetrics-x-1297
- Conductor Introduces AgentStack to Scale AI Search Visibility: https://www.demandgenreport.com/industry-news/news-brief/conductor-introduces-agentstack-to-scale-ai-search-visibility/52636/
- Conductor Reviews 2026: Details, Pricing, & Features: https://www.g2.com/products/conductor/reviews
- Conductor AI Review (2026): Honest Buyer's Guide: https://www.tryanalyze.ai/blog/conductor-ai-review
- Conductor Software Pricing & Plans 2026: https://www.vendr.com/marketplace/conductor
Additional AI research evidence140 records
- AI research evidence record openai:c2
- AI research evidence record openai:c1
- AI research evidence record openai:c5
- AI research evidence record anthropic:12-1
- AI research evidence record anthropic:41-1
- AI research evidence record openai:c0
- AI research evidence record deepseek:c1
- AI research evidence record deepseek:c3
- AI research evidence record anthropic:4-12
- AI research evidence record anthropic:25-3
- AI research evidence record openai:c1
- AI research evidence record openai:c0
- AI research evidence record openai:c4
- AI research evidence record openai:c6
- AI research evidence record google:1.1.6
- AI research evidence record anthropic:3-4
- AI research evidence record anthropic:43-5
- AI research evidence record anthropic:43-6
- AI research evidence record anthropic:43-7
- AI research evidence record kimi:georion-1
- AI research evidence record anthropic:17-4
- AI research evidence record openai:c1
- AI research evidence record anthropic:25-3
- AI research evidence record anthropic:27-1
- AI research evidence record anthropic:6-10
- AI research evidence record openai:c2
- AI research evidence record anthropic:13-2
- AI research evidence record grok:0
- AI research evidence record perplexity:c1
- AI research evidence record anthropic:18-5
- AI research evidence record openai:c4
- AI research evidence record anthropic:22-6
- AI research evidence record anthropic:22-9
- AI research evidence record anthropic:26-2
- AI research evidence record anthropic:26-8
- AI research evidence record anthropic:26-9
- AI research evidence record anthropic:4-13
- AI research evidence record anthropic:27-2
- AI research evidence record openai:c5
- AI research evidence record openai:c7
- AI research evidence record anthropic:43-5
- AI research evidence record google:1.1.3
- AI research evidence record anthropic:41-1
- AI research evidence record anthropic:41-2
- AI research evidence record anthropic:6-2
- AI research evidence record grok:3
- AI research evidence record grok:15
- AI research evidence record anthropic:26-12
- AI research evidence record anthropic:26-13
- AI research evidence record google:1.1.7
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:13-3
- AI research evidence record anthropic:11-6
- AI research evidence record anthropic:12-14
- AI research evidence record anthropic:17-3
- AI research evidence record anthropic:17-4
- AI research evidence record anthropic:12-2
- AI research evidence record anthropic:12-6
- AI research evidence record openai:c9
- AI research evidence record anthropic:18-5
- AI research evidence record openai:c2
- AI research evidence record anthropic:41-1
- AI research evidence record anthropic:41-2
- AI research evidence record openai:c0
- AI research evidence record anthropic:4-13
- AI research evidence record anthropic:27-2
- AI research evidence record anthropic:10-1
- AI research evidence record anthropic:18-18
- AI research evidence record openai:c1
- AI research evidence record anthropic:22-9
- AI research evidence record openai:c4
- AI research evidence record perplexity:c3
- AI research evidence record anthropic:23-9
- AI research evidence record openai:c7
- AI research evidence record anthropic:41-12
- AI research evidence record anthropic:18-19
- AI research evidence record anthropic:12-5
- AI research evidence record anthropic:12-13
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:13-3
- AI research evidence record anthropic:12-2
- AI research evidence record anthropic:12-6
- AI research evidence record anthropic:17-3
- AI research evidence record anthropic:17-4
- AI research evidence record google:1.2.4
- AI research evidence record kimi:georion-1
- AI research evidence record anthropic:17-8
- AI research evidence record anthropic:11-1
- AI research evidence record anthropic:18-17
- AI research evidence record google:1.2.1
- AI research evidence record anthropic:11-6
- AI research evidence record anthropic:24-5
- AI research evidence record anthropic:14-1
- AI research evidence record anthropic:18-3
- AI research evidence record anthropic:6-10
- AI research evidence record anthropic:14-3
- AI research evidence record anthropic:4-13
- AI research evidence record anthropic:27-2
- AI research evidence record anthropic:43-5
- AI research evidence record openai:c7
- AI research evidence record openai:c5
- AI research evidence record anthropic:17-13
- AI research evidence record anthropic:17-11
- AI research evidence record anthropic:6-8
- AI research evidence record anthropic:41-1
- AI research evidence record anthropic:41-2
- AI research evidence record anthropic:6-2
- AI research evidence record anthropic:12-5
- AI research evidence record anthropic:12-13
- AI research evidence record anthropic:12-14
- AI research evidence record anthropic:18-1
- AI research evidence record google:1.1.7
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:14-4
- AI research evidence record anthropic:8-4
- AI research evidence record anthropic:8-5
- AI research evidence record anthropic:8-6
- AI research evidence record anthropic:6-3
- AI research evidence record anthropic:6-4
- AI research evidence record anthropic:26-16
- AI research evidence record kimi:georion-1
- AI research evidence record kimi:ayzeo-1
- AI research evidence record kimi:ultrascout-1
- AI research evidence record anthropic:14-1
- AI research evidence record anthropic:18-3
- AI research evidence record openai:c2
- AI research evidence record openai:c6
- AI research evidence record openai:c4
- AI research evidence record anthropic:4-13
- AI research evidence record openai:c5
- AI research evidence record anthropic:43-5
- AI research evidence record anthropic:12-1
- AI research evidence record anthropic:17-3
- AI research evidence record kimi:georion-1
- AI research evidence record anthropic:41-1
- AI research evidence record anthropic:26-12
- AI research evidence record anthropic:26-13
- AI research evidence record google:1.1.9
- AI research evidence record anthropic:23-9
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
- 43
- Ranking mentions
- 2 of 7
- Platform share
- 29%
- Final consensus rank
- #10
Research trail and source mix
Configured platforms
openai, anthropic, deepseek, grok, perplexity, kimi, google
Source mix
22 independent · 21 company-owned
Evidence support
36 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 e547d06311ec3de0f2d11710de8c8686fc1433a5fbdb0fe13c7bc0aac39d62bc