Answer Capsule
Profound is a strong fit for enterprise teams that need recurring, prompt-level AI citation auditing across major answer engines, and a weaker fit for buyers who want a fixed-price, one-time human audit. Three of the seven platforms in this study named Profound during the ranking stage — DeepSeek, Google, and OpenAI — and all three placed it at rank 1. The strongest reason to consider it is its citation-source analysis: cited URLs and domains, competitor citation rankings, citation-share trends, and prompts where competitors are cited but the buyer is not [1]. The main limitation is commercial opacity: Enterprise pricing, exact engine coverage, historical retention, and independent validation of citation accuracy are not publicly established [2].
Research Snapshot
| Field | Finding |
|---|---|
| Platform mentions in ranking stage | 3 of 7 platforms (DeepSeek, Google, OpenAI) |
| Share of included platform responses | 42.9% |
| Average listed rank | 1.0 |
| Best listed rank | 1 |
| Relevant product/model/plan | Profound Answer Engine Insights, particularly the Enterprise plan |
| Overall use-case fit | Strong for recurring enterprise citation auditing; mixed-to-uncertain for one-time or budget-constrained audits |
| Research date | 2026-09-17 |
Why Profound Qualified for This Study
Questions This Section Answers
- Is Profound a good choice for AI Citation Audit Services at an enterprise scale?
- How many AI platforms named Profound when asked to recommend AI citation audit services?
Profound qualified because three of the seven platforms in this study named it during ranking discovery, and each of those three placed it first. DeepSeek, Google, and OpenAI all listed Profound at rank 1, producing an average listed rank of 1.0 across the platforms that named it [3].
That is a narrow but unanimous signal. Four of the seven platforms — Anthropic, Grok, Kimi, and Perplexity — evaluated Profound's fit but did not name it in their ranking stage, so the 42.9% mention share should be read as partial coverage rather than broad consensus. The platforms that did name it converged on the same reason: Profound tracks citations and cited sources at the prompt level across generative answer engines, which maps directly onto the audit criteria in this study [4].
Fit ratings diverged once platforms moved from ranking to evaluation. Google and Grok rated Profound a strong fit; OpenAI, Anthropic, and DeepSeek rated it good; Perplexity rated it mixed; Kimi rated it uncertain. That spread is itself a finding — the disagreement is concentrated in how much of Profound's citation-audit capability is publicly verifiable, not in whether the product exists.
The Product, Model, Plan, or Service Most Relevant to AI Citation Audit Services
Questions This Section Answers
- Which Profound plan should a buyer choose if they need multi-engine AI citation auditing rather than ChatGPT-only tracking?
- Is Profound Answer Engine Insights a software platform or a done-for-you AI citation audit service?
The relevant product is Profound Answer Engine Insights, and the plan that matters for a real multi-engine citation audit is the Enterprise tier, not Starter or Growth. Profound's public pricing page lists Starter at $99 per month billed yearly and Growth at $399 per month billed yearly, with Enterprise priced as custom [6]. Independent reviews describe Starter as ChatGPT-only with roughly 50 prompts and Growth as covering three engines with roughly 100 prompts, with broader engine coverage gated behind Enterprise [7].
That gating is the central product-fit issue for this use case. A citation audit that only sees ChatGPT is not a cross-platform audit. Buyers who need Claude, Gemini, Copilot, Meta AI, Grok, or DeepSeek citations are directed to a sales conversation rather than a published plan [9].
Profound is also a software platform, not a consulting deliverable. Public materials describe monitoring, analysis, and reporting surfaces; they do not establish that Profound sells a managed, analyst-led audit with a written findings document. Buyers who want a one-time human-produced audit should treat that as an open question to confirm in the sales process.
What the AI Platforms Agreed About
Questions This Section Answers
- What do multiple AI platforms agree Profound does well for AI citation auditing?
- Does Profound show which specific URLs and domains AI engines cite?
Platforms broadly agreed that Profound's core strength is citation-source visibility rather than generic brand mention tracking. Profound's own documentation states that the Citations product analyzes which sources AI pulls from, including cited pages, domains, competitor citation rank, publishers, and pages gaining or losing citation share [10]. Independent reviews describe the same capability at domain and individual page level, showing which content assets drive citation wins [11].
Platforms also agreed on competitor citation comparison. Profound states it identifies prompts where competitors receive citations but the buyer does not, and identifies publishers producing the most citations in a category [10]. Independent reviews describe citation categories that classify sources as Owned, Competitor, Earned Media, PR Wire, Social, or Institution, with filtering and benchmarking against specific competitors by platform, topic, or prompt [13].
A third area of agreement was historical tracking. Profound documentation states that citation-share trends can be tracked over time and that the Citation Share chart shows day-over-day changes with a rankings table comparing the buyer's citation share to competitors [15]. Independent reviews describe monthly citation drift of 40–60% across major platforms, which is the argument for continuous tracking rather than a one-time snapshot [17].
Agreement on these three points was strong across the platforms that examined the product. It was not unanimous across all seven, because four platforms did not name Profound in ranking and one, Kimi, characterized it as a monitoring tool that "measures, and it writes nothing" [18].
Where the AI Platforms Disagreed or Were Uncertain
Questions This Section Answers
- Is Profound's Enterprise pricing publicly available, and what do third parties say it costs?
- Does Profound provide independently verified measurement of how citations affect recommendations or revenue?
The sharpest disagreement is about pricing. Profound's public pricing page lists Starter and Growth figures but describes Enterprise only as tailored [19]. Third-party reviews put Enterprise deployments at $2,000–$5,000 or more per month depending on platform count, seats, and features [20]. One platform reported a wider range of $2,000–$8,000 per month depending on prompt volume and competitor depth [22]. DeepSeek's research, dated 2026-01-15, found no verified public list price at all and rated pricing confidence low [23]. These figures conflict and none is confirmed by Profound.
Engine coverage is the second conflict. Public materials describe different coverage levels, including three named engines in the plan comparison and up to nine engines for Enterprise [19]. Independent reviews describe ten or more engines including ChatGPT, Perplexity, Claude, Gemini, Copilot, Grok, DeepSeek, Meta AI, and Google AI Overviews [24]. The exact engine list in a buyer's negotiated package is not publicly determinable.
Recommendation impact is the third and most consequential uncertainty. Profound publicly emphasizes visibility, citations, rankings, sentiment, and competitive presence [19]. Some independent reviews claim Profound connects citation data to site outcomes including traffic and pipeline through GA4 integration, enabling revenue attribution [25]. OpenAI's evaluation states directly that the reviewed sources do not establish independent causal attribution from citation changes to recommendations, traffic, leads, or revenue [19]. Perplexity reached the same conclusion, finding no verified recommendation-impact measurement method suitable for audit-grade decisioning [27].
Two further uncertainties are worth flagging. First, benchmarking depends on opt-in network participation and may not represent the entire U.S. market or every category [28]. Second, no platform established independent validation of Profound's citation accuracy, sampling methodology, or data completeness [19].
Use-Case-Specific Features and Capabilities
Questions This Section Answers
- Does Profound support source-gap analysis that shows which prompts competitors win and the buyer does not?
- Can Profound export citation data as CSV or JSON for an internal audit workflow?
Profound covers most of the audit criteria in this study, with the strongest evidence behind cited URL and domain analysis, competitor benchmarking, and source-gap analysis.
| Audit criterion | Assessment | Evidence |
|---|---|---|
| Prompt-level citation data | Advantage | Structured prompts across AI platforms analyzing responses, citations, sentiment, rankings, and competitive presence; 100 tracked prompts and daily frequency in the standard comparison view |
| Cited URL and domain analysis | Advantage | Cited pages, domains, competitor citation rank, publishers, and pages gaining or losing citation share |
| Citation architecture mapping | Advantage | Citation Relationships chart visualizing how citations connect across answer engines and topics; export formats and graph granularity unclear |
| Source-gap analysis | Advantage | Prompts where competitors receive citations but the buyer does not, plus publishers producing the most citations in a category |
| Competitor benchmarking | Advantage | Benchmarking against more than 2 million pages, refreshed weekly, opt-in with aggregated and anonymized data |
| Historical tracking | Advantage | Citation-share trends over time; benchmarks refresh weekly; maximum retention period not published |
| Recommendation impact | Unclear | Visibility, citations, rankings, sentiment, and competitive presence are documented; causal attribution to recommendations, traffic, leads, or revenue is not established |
On data capture, Profound states it captures responses directly from the browser rather than through APIs, which it positions as showing what customers actually see when they query AI [30]. Independent reviews describe the platform tracking real user conversation data rather than simulated prompts [32].
On exports, Profound documentation states citation data exports directly as CSV or JSON [33]. Independent reviews conflict on whether that applies at every tier: one states that API access, unlimited exports, and CSV/JSON export are gated behind Enterprise, with Growth limited and Starter having no programmatic access [34]. Buyers should confirm export scope for their specific tier.
On governance, Profound states it is SOC 2 Type II compliant and supports SSO using SAML or OIDC with fine-grained role-based permissions [35]. These are company statements; the scope of the compliance representation was not independently verified in the reviewed sources.
Pricing, Fees, Contracts, and Ongoing Costs
Questions This Section Answers
- How much does Profound cost per month for Starter, Growth, and Enterprise, and are there setup or cancellation fees?
- What contract term does Profound require, and can a buyer cancel or get a refund?
Published pricing is limited to two self-serve tiers. Profound lists Starter at $99 per month when billed yearly and Growth at $399 per month when billed yearly, with two months free shown for annual billing [38]. Independent reviews report the same figures and describe Starter as ChatGPT-only with 50 prompts and one seat, and Growth as covering three engines with 100 prompts [39].
Enterprise pricing is custom and has no publicly verifiable total. Third-party estimates range from $2,000 to $5,000 or more per month [42], with one platform reporting $2,000–$8,000 per month [44]. These are third-party estimates, not confirmed quotes.
Contract terms are only partly documented. The public pricing page indicates annual billing for Starter and Growth but does not state cancellation, refund, renewal, minimum-term, or Enterprise termination terms [38]. Independent reviews state that self-serve plans are billed yearly and effectively annual-commitment, but the official site excerpt checked did not confirm cancellation terms [45]. One platform reported that some third parties mention one-time setup fees, but that this was not verified on the official site and should be treated as uncertain [46].
Additional cost surfaces are unclear. Whether Profound charges extra for higher prompt volumes, additional answer engines, additional regions or languages, implementation, data exports, API access, or professional services is not publicly specified [38]. Profound Agents use a separate credit-based model, with the self-serve Agency Growth plan including 400 credits per month per client workspace and additional thresholds requiring an Enterprise package (official:C2).
Best Suited For
Questions This Section Answers
- Which types of companies get the most value from Profound for AI Citation Audit Services?
- Is Profound worth it for a company that needs recurring multi-engine citation monitoring rather than a one-time audit?
Profound is best suited to enterprise marketing, SEO, communications, and digital teams that need recurring AI citation monitoring rather than a one-time report [47]. The product's value compounds with continuous tracking: citation-share trends, day-over-day changes, and weekly benchmark refreshes only produce signal if the buyer keeps the subscription running [48].
It also fits companies whose audit question is specifically "which sources and competitors do AI engines cite in our category." Profound's documented strengths — cited URL and domain analysis, competitor citation rank, publisher analysis, and prompts where competitors are cited but the buyer is not — answer that question directly [50].
Organizations with enterprise procurement requirements are a third fit. Profound states it offers multiple companies, tailored prompt tracking, dedicated Slack support, and SSO/SAML plus SOC 2 compliance on Enterprise [47]. Independent reviews describe SOC 2 Type II certification as a key reason Profound won customers including Samsung, L'Oreal, and U.S. Bank [51]. Those customer claims are company and review-reported, not independently verified here.
Probably Not Best Suited For
Questions This Section Answers
- Who should not choose Profound for AI Citation Audit Services?
- Is Profound a poor fit for a buyer who needs a fixed-price, one-time citation audit?
Profound is probably not the right choice for buyers who need a fixed-price, one-time audit rather than a recurring software subscription [52]. Every published tier is a subscription, and the audit-shaped deliverables a consulting buyer expects — a written findings document, qualitative source evaluation, outreach recommendations — are not established in the reviewed materials.
It is also a poor fit for small teams that need broad platform coverage at the lowest possible cost. Multi-engine tracking starts at the Growth tier, and the engines beyond the three named in the plan comparison require Enterprise [52]. Buyers whose audit scope is a handful of prompts on one engine will be paying for capacity they do not use.
Finally, Profound is not suited to buyers who require independently verified causal measurement of AI recommendations, conversions, or revenue impact [52]. The platform documents exposure and citation metrics; the reviewed sources do not establish that citation changes cause recommendation or revenue changes.
When Another Option May Be Better
Questions This Section Answers
- What is a better alternative to Profound for a buyer with a sub-$400 per month AI citation audit budget?
- When is a specialist one-time audit service a better choice than Profound's subscription platform?
A lower-cost AI visibility platform may be better when the buyer needs basic monitoring across a small prompt set and does not need enterprise governance [54]. Independent reviews name Otterly.AI, Scrunch AI, and Knowatoa as entry-level citation tracking options without enterprise gatekeeping, and Cairrot, Trakkr, and AthenaHQ as broader multi-LLM coverage at lower tier pricing [55].
A specialist research or consulting service may be better when the buyer needs a one-time human audit, qualitative source evaluation, outreach recommendations, or manually validated recommendation analysis [54]. Independent reviews describe one-time audit offerings with pre-registered prompt sets and confidence intervals, and full audits priced in the $2,000–$2,500 range [56]. Those are competitor-published prices and should be verified directly.
Another platform may be better when required AI engines, regions, languages, API access, or historical retention are not included in the negotiated Profound package [54]. Buyers with international or non-English audit requirements should confirm scope before committing, because Enterprise documentation notes custom language and region support while Growth-tier scope is unclear [58].
Questions to Verify Before Buying
Questions This Section Answers
- What should a buyer confirm with Profound before signing an Enterprise contract for AI citation auditing?
- Can Profound export full historical citation data with timestamps, prompts, engines, and cited URLs?
The following questions are drawn from the verification lists the platforms supplied. They are the items most likely to change a purchase decision.
- Which exact answer engines, models, shopping surfaces, and recommendation platforms are included in the proposed Enterprise package [59]?
- What are the monthly prompt, response, user, domain, competitor, language, region, and company limits [59]?
- Can every response be exported with timestamp, prompt, model or engine, cited URL, cited domain, citation position, and competitor comparison [59]?
- How are citations collected, deduplicated, sampled, and validated, and what are the known blind spots [59]?
- What historical retention period is included, and are raw response archives available after cancellation [59]?
- Does Profound measure only exposure and citations, or can it connect citation changes to qualified traffic, recommendations, leads, or revenue [59]?
- What are the annual commitment, renewal, cancellation, refund, implementation, support, data-processing, and overage terms [59]?
- What exactly is covered by the stated SSO/SAML and SOC 2 representations, and can the buyer review applicable security documentation [59]?
- Does the purchase include a managed audit or only access to the software platform [59]?
- Does the Growth plan include export of full historical citation data in machine-readable format, or is that gated to Enterprise [60]?
- Which specific traffic and revenue metrics does GA4 integration capture from citations, and is attribution last-click, first-click, or multi-touch [61]?
- Does Profound offer a free trial or proof-of-concept period to validate citation accuracy against your brand before committing to an annual contract [62]?
Final AI Consensus Verdict
Profound is a strong fit for enterprise teams seeking recurring AI citation auditing and competitive source intelligence across major answer engines, and a weak fit for buyers who need a one-time human audit, transparent fixed pricing, or independently validated causal measurement. Three of seven platforms named it in ranking, all at rank 1, and the platforms that examined it agreed on its core capabilities: cited URL and domain analysis, competitor citation comparison, citation-share tracking, citation-relationship mapping, benchmarking, and historical monitoring [63].
The consensus breaks down on commercial and methodological questions. Enterprise pricing is unquoted and third-party estimates conflict, ranging from $2,000 to $8,000 or more per month [68]. Engine coverage is described inconsistently across public materials [63]. Recommendation-impact attribution is claimed by some independent reviews and explicitly unestablished by others [72]. No platform established independent validation of citation accuracy or sampling methodology.
Treat Profound as an observability and benchmarking platform, not as independently proven causal measurement of recommendation or revenue impact. Obtain a written Enterprise quote and technical validation of engine coverage, raw citation exports, historical retention, methodology, and contract terms before purchase [63].
How This Review Was Produced
This review was produced from seven platform research responses collected for the AI Citation Audit Services study, using the run research date of 2026-09-17 as the study date. Each platform independently evaluated Profound's fit against the same audit criteria: prompt-level citation data, cited URL and domain analysis, citation architecture mapping, source-gap analysis, competitor benchmarking, historical tracking, and recommendation impact.
Platform mentions in the ranking stage were counted separately from fit evaluation. Three platforms — DeepSeek, Google, and OpenAI — named Profound during ranking discovery, and all three placed it at rank 1. The remaining four platforms evaluated fit without naming Profound in their ranking stage.
Fit ratings were recorded as supplied: Google and Grok rated Profound a strong fit; OpenAI, Anthropic, and DeepSeek rated it good; Perplexity rated it mixed; Kimi rated it uncertain. This article preserves those ratings rather than averaging them, because the disagreement is substantive.
The broader AI Citation Audit Services index covers how Profound compares with other providers evaluated in this study.
Methodology Limitations
Several limitations apply to this review and should be weighed before acting on it.
Platform-reported research dates differ from the authoritative run date. Six platforms reported 2026-09-17, but DeepSeek reported 2026-01-15, roughly eight months earlier. DeepSeek's pricing findings in particular may be stale, and its conclusion that no public list price exists conflicts with the Starter and Growth figures other platforms retrieved [74].
Citations are platform-reported evidence, not independently verified facts. The supplied URLs were collected from platform responses and were not independently validated during the writing stage. Company-owned sources such as Profound's pricing page and help documentation describe the product as the company describes it; independent reviews and directories were treated as a separate evidence class but are not audits either.
No platform established independent validation of Profound's citation accuracy, sampling methodology, data completeness, or recommendation-impact attribution [75]. One platform noted that accuracy estimates in third-party reviews are directional rather than audited [76].
Conflicting product names, pricing, and capabilities were not resolved by guessing. Where sources disagreed — Enterprise cost, engine count, export gating, and recommendation attribution — this review describes the conflict and directs buyers to verify rather than selecting one figure.
Benchmarking coverage depends on opt-in network participation and may not represent the entire U.S. market or every category [77]. Prompt-volume limits on the Growth tier may be inadequate for verticals with large buyer-journey query sets [78].
Finally, platform agreement on a product's capabilities does not prove product quality. The consensus described here reflects what the platforms reported, not an independent performance test.
Explore more ai citation authority building guidance in the category directory.
Sources
Company-Owned Sources
- GEO Audit — Measure where you stand in AI search: https://becited.io/services/geo-audit
- Pricing — Cited Digital AEO Audits, Fix Packs, and Monitoring: https://citeddigital.co/audit/pricing.html
- Audits — Clear Cited (Starter, Full, Comprehensive: https://clearcited.com/pricing/audits/
- Answer Engine Insights Overview | Profound Knowledge Base: https://help.tryprofound.com/articles/3443229936-answer-engine-insights-overview
- About Answer Engine Insights: https://help.tryprofound.com/articles/3443229936-answer-engine-insights-overview?lang=en
- Interpret Answer Engine Insights v2: https://help.tryprofound.com/articles/5194011335
- Citation Share Node: https://help.tryprofound.com/articles/6399057996-citation-share
- Add Pages to Watched Pages in Answer Engine Insights | Profound University: https://university.tryprofound.com/courses/profound-101
- Profound — AI Search & Answer Engine Insights: https://www.tryprofound.com
- Agent Templates - Profound: https://www.tryprofound.com/agent-templates
- Introducing Citation Decay in Profound: https://www.tryprofound.com/blog/citation-decay
- Google AI Mode: How to Rank and Get Cited - Profound: https://www.tryprofound.com/blog/google-ai-mode-aeo
- Profound vs AthenaHQ: Which platform is right for your brand?: https://www.tryprofound.com/blog/profound-vs-athenahq
- The first benchmark for AI Search: https://www.tryprofound.com/features/agent-analytics/benchmarking
- Answer Engine Insights: #1 AI Search Visibility Platform: https://www.tryprofound.com/features/answer-engine-insights
- AI Citation Analysis Tool for AEO | Profound: https://www.tryprofound.com/features/answer-engine-insights/citations
- Track Prompt & Keyword Volume Across AI Conversations: https://www.tryprofound.com/features/prompt-volumes
- Pricing - Profound: https://www.tryprofound.com/pricing
Additional AI research evidence78 records
- AI research evidence record openai:c2
- AI research evidence record openai:c1
- AI research evidence record openai:c1
- AI research evidence record deepseek:c1
- AI research evidence record google:profound-insights
- AI research evidence record openai:c1
- AI research evidence record anthropic:10-13
- AI research evidence record anthropic:18-1
- AI research evidence record anthropic:18-21
- AI research evidence record openai:c2
- AI research evidence record anthropic:21-1
- AI research evidence record anthropic:21-2
- AI research evidence record anthropic:2-2
- AI research evidence record anthropic:19-8
- AI research evidence record openai:c3
- AI research evidence record anthropic:2-6
- AI research evidence record anthropic:1-10
- AI research evidence record kimi:trirankai_2026
- AI research evidence record openai:c1
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:16-1
- AI research evidence record grok:8
- AI research evidence record deepseek:c4
- AI research evidence record anthropic:7-7
- AI research evidence record anthropic:29-1
- AI research evidence record anthropic:29-2
- AI research evidence record perplexity:c7
- AI research evidence record openai:c5
- AI research evidence record grok:4
- AI research evidence record anthropic:4-4
- AI research evidence record anthropic:4-5
- AI research evidence record anthropic:21-15
- AI research evidence record anthropic:19-13
- AI research evidence record anthropic:12-7
- AI research evidence record anthropic:4-12
- AI research evidence record anthropic:4-13
- AI research evidence record anthropic:4-14
- AI research evidence record openai:c1
- AI research evidence record anthropic:12-6
- AI research evidence record anthropic:12-7
- AI research evidence record anthropic:18-1
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:16-1
- AI research evidence record grok:8
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c5
- AI research evidence record openai:c1
- AI research evidence record openai:c3
- AI research evidence record openai:c5
- AI research evidence record openai:c2
- AI research evidence record anthropic:17-3
- AI research evidence record openai:c1
- AI research evidence record anthropic:18-21
- AI research evidence record openai:c1
- AI research evidence record anthropic:10-7
- AI research evidence record kimi:clearcited_2026
- AI research evidence record kimi:becited_2026
- AI research evidence record anthropic:18-21
- AI research evidence record openai:c1
- AI research evidence record anthropic:12-7
- AI research evidence record anthropic:29-1
- AI research evidence record perplexity:c1
- AI research evidence record openai:c1
- AI research evidence record openai:c2
- AI research evidence record openai:c3
- AI research evidence record openai:c4
- AI research evidence record openai:c5
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:16-1
- AI research evidence record grok:8
- AI research evidence record anthropic:7-7
- AI research evidence record anthropic:29-1
- AI research evidence record perplexity:c7
- AI research evidence record deepseek:c4
- AI research evidence record openai:c1
- AI research evidence record grok:4
- AI research evidence record openai:c5
- AI research evidence record anthropic:18-1
Independent Sources
- 5 Best AI Visibility Tools for Enterprises in 2026 - AiTLAS: https://aitlas.com/blog/best-ai-visibility-tools
- AI Citation Tracking: How to Monitor Brand Citations in AI Answers - Ansvisor: https://ansvisor.com/blog/ai-citation-tracking
- What is the pricing structure for Profound's answer engine insights suite: https://answers.org/profound/what-is-the-pricing-structure-for-profound-s-answer-engine-insights-suite
- Best AEO Citation Tracking Tools 2026 (Profound vs Goodie vs Otterly) | AO Network: https://aonetwork.com/tools/best-aeo-citation-tracking-tools
- Profound Pricing 2026: What It Actually Costs: https://arobis.ai/blog/profound-pricing
- Profound Review 2026: AI Visibility Tracking Tested: https://blog.contentforce.ai/profound-ai/
- Profound Review & Pricing Comparison: Evaluate Profound Against Top AEO Tool Alternatives - Cairrot: https://cairrot.com/alternatives/profound-review-price-comparison-top-alternatives/
- Profound AI Visibility Tool: Deep Dive Review for B2B SaaS Teams | Discovered Labs: https://discoveredlabs.com/blog/profound-ai-visibility-tool-review
- Profound Review (2026): Is the Enterprise AI Visibility Tool: https://dupple.com/learn/profound-review
- Profound vs Semrush AI Toolkit | AI Visibility Tool Comparison - Elmo: https://elmo.ai/comparisons/profound-vs-semrush-ai-toolkit
- Profound Review 2026: Pricing & Is It Worth It? - Geoptie: https://geoptie.com/blog/profound-review
- Profound Review: Is It the Best AEO/GEO Platform for AI Search in 2025?: https://nicklafferty.com/reviews/profound-best-aeo-geo-platform-for-ai-search/
- Profound AI Review for 2026: Is It Worth the Investment? - Radarkit: https://radarkit.ai/blog/profound-ai-review/
- Profound Review 2026: Features, Limits and Verdict | Trakkr: https://trakkr.ai/reviews/profound-review
- AEO / AI Visibility Audit — $399 one-time | TriRank - AI Search Visibility: https://trirankai.com/audit
- Profound Review (2026): Is It Worth It for Enterprise AEO? - Vismore: https://vismore.com/blog/profound-review-aeo
- Profound Review & Pricing (2026) | AI SEO Compare: https://www.aiseocompare.com/tools/profound
- Profound Review (2026): The Enterprise AEO Platform: https://www.arfadia.com/blog/profound-review/
- Profound company profile: https://www.crunchbase.com/organization/profound-2e18
- Profound Pricing 2026: https://www.g2.com/products/profound/pricing
- Profound product listing: https://www.g2.com/products/profound/reviews
- Profound Review 2026: Features, Pricing, Honest Limits: https://www.get-ryze.ai/blog/profound-review-2026
- Profound AI Data Accuracy Review (2026) | AI Visibility Metrics: https://www.getaiso.com/evaluate-profound-ai-data-accuracy
- Profound Review 2026: Does This Enterprise GEO Platform Deliver?: https://www.getmint.ai/blog/profound-review
- Profound AI review for agencies (2026): is it worth it for client AI visibility? | Rankability Blog: https://www.rankability.com/blog/profound-ai-review/
- Best AI Citation Tracking Tools for AI Visibility (2026: https://www.therankmasters.com/insights/ai-visibility/best-ai-visibility-tools-citation-tracking
- Profound AI Review 2026: Limits, Pricing & Results - Analyze AI: https://www.tryanalyze.ai/blog/profound-ai-review
Additional AI research evidence78 records
- AI research evidence record openai:c2
- AI research evidence record openai:c1
- AI research evidence record openai:c1
- AI research evidence record deepseek:c1
- AI research evidence record google:profound-insights
- AI research evidence record openai:c1
- AI research evidence record anthropic:10-13
- AI research evidence record anthropic:18-1
- AI research evidence record anthropic:18-21
- AI research evidence record openai:c2
- AI research evidence record anthropic:21-1
- AI research evidence record anthropic:21-2
- AI research evidence record anthropic:2-2
- AI research evidence record anthropic:19-8
- AI research evidence record openai:c3
- AI research evidence record anthropic:2-6
- AI research evidence record anthropic:1-10
- AI research evidence record kimi:trirankai_2026
- AI research evidence record openai:c1
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:16-1
- AI research evidence record grok:8
- AI research evidence record deepseek:c4
- AI research evidence record anthropic:7-7
- AI research evidence record anthropic:29-1
- AI research evidence record anthropic:29-2
- AI research evidence record perplexity:c7
- AI research evidence record openai:c5
- AI research evidence record grok:4
- AI research evidence record anthropic:4-4
- AI research evidence record anthropic:4-5
- AI research evidence record anthropic:21-15
- AI research evidence record anthropic:19-13
- AI research evidence record anthropic:12-7
- AI research evidence record anthropic:4-12
- AI research evidence record anthropic:4-13
- AI research evidence record anthropic:4-14
- AI research evidence record openai:c1
- AI research evidence record anthropic:12-6
- AI research evidence record anthropic:12-7
- AI research evidence record anthropic:18-1
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:16-1
- AI research evidence record grok:8
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c5
- AI research evidence record openai:c1
- AI research evidence record openai:c3
- AI research evidence record openai:c5
- AI research evidence record openai:c2
- AI research evidence record anthropic:17-3
- AI research evidence record openai:c1
- AI research evidence record anthropic:18-21
- AI research evidence record openai:c1
- AI research evidence record anthropic:10-7
- AI research evidence record kimi:clearcited_2026
- AI research evidence record kimi:becited_2026
- AI research evidence record anthropic:18-21
- AI research evidence record openai:c1
- AI research evidence record anthropic:12-7
- AI research evidence record anthropic:29-1
- AI research evidence record perplexity:c1
- AI research evidence record openai:c1
- AI research evidence record openai:c2
- AI research evidence record openai:c3
- AI research evidence record openai:c4
- AI research evidence record openai:c5
- AI research evidence record anthropic:13-2
- AI research evidence record anthropic:16-1
- AI research evidence record grok:8
- AI research evidence record anthropic:7-7
- AI research evidence record anthropic:29-1
- AI research evidence record perplexity:c7
- AI research evidence record deepseek:c4
- AI research evidence record openai:c1
- AI research evidence record grok:4
- AI research evidence record openai:c5
- AI research evidence record anthropic:18-1
Verify this research
Review the study details behind this page or download the public machine-readable verification record.
- Study date
- September 17, 2026
- Platforms analyzed
- 7
- Source records
- 45
- Ranking mentions
- 3 of 7
- Platform share
- 43%
- Final consensus rank
- #1
Research trail and source mix
Configured platforms
openai, anthropic, deepseek, grok, perplexity, kimi, google
Source mix
27 independent · 18 company-owned
Evidence support
19 direct · 13 partial
Important limitation
Use the run research_date as the study date. Platform-reported dates are provenance metadata and do not independently prove freshness.
Source snapshot SHA-256 020e329752086182fd309165d29aa68715105da02821eb0c85c4a7fa25354769