Peec AI ↗
Peec AI: A more focused AI-search analytics alternative for teams comparing visibility, position, sentiment, citations, and competitor metrics.
← All toolsAnother direction / 01 Another direction / 02 Another direction / 03 Another direction / 04 Another direction / 05
The selection guideSource-backed research ↗
Analytics / AI visibility & analytics
Profound
Enterprise AI search visibility, citation intelligence, and AEO workflows
Visibility analytics
Why it stands out
Strong breadth across visibility, citations, prompt demand, crawler activity, and AI referrals
Source review: · Public-source research, not a hands-on test
↗ Best for
Enterprise SEO, content, PR, and marketing-operations teams that need a shared AI-search measurement layer
! Know before you buy
The public plan comparison does not expose a current numeric Enterprise price, historical retention terms, or all usage allowances.
01 / Editorial assessment
Is Profound for you?
The AICiteKit take
Profound belongs on the shortlist for organizations treating AI search as a cross-functional measurement program rather than a one-off SEO experiment. Its official materials describe a coherent loop: discover demand with Prompt Volumes, measure brand and competitor visibility with Answer Engine Insights, inspect crawler and referral behavior with Agent Analytics, then use Agents to turn findings into reviewed content work. The evidence is strongest for product existence, named workflows, trial limits, enterprise controls, and the availability of a large G2 review sample. It is weaker for causal business outcomes. Profound’s customer stories report large visibility or signup improvements, but those are vendor-selected case studies and cannot establish that Profound caused the full result. Neither a visibility score nor a citation count proves qualified traffic, conversions, pipeline, or revenue.
A good fit if you are…
- Enterprise SEO, content, PR, and marketing-operations teams that need a shared AI-search measurement layer
- Brands monitoring competitors, citations, sentiment, and prompt-level presence across several answer engines
- Organizations with Cloudflare, AWS, Vercel, Netlify, Akamai, or comparable infrastructure access for crawler analytics
- Agencies with clients that can support custom contracts, data governance, and analyst-led reporting
- Teams that want prompt-demand research connected to content prioritization rather than a standalone scorecard
Consider another option if…
- Startups that need a transparent monthly price and self-serve multi-engine coverage
- Buyers who want a small set of manual prompt checks rather than a recurring measurement program
- Teams without a stable prompt taxonomy, regional sampling plan, or owner for evidence review
- Agencies that require fully white-label reporting; the independent review checked for this reports no white-label reporting
- Anyone treating crawler requests as proof of citations or treating AI visibility as a substitute for analytics and experiments
02 / Scope, not promises
Features & coverage
- Enterprise engines
Custom capability for ChatGPT, Perplexity, Google AI Mode, Gemini, Microsoft Copilot, DeepSeek, Claude, Google AI Overviews, and Exa Search
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Quick facts- Prompt frequency
Daily for Enterprise; trial is daily for 7 days
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Quick facts- Prompt Volumes
Official feature page describes 1.5B+ real-user conversations, demand data, trend tracking, and content-gap discovery
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Quick facts- Main use case
AI-search visibility, citation, prompt-demand, crawler, and attribution analytics
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Quick facts- Trial
Free; 50 unique prompts daily for 7 days
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Quick facts- Trial engines
ChatGPT, Gemini, Google AI Overviews
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Quick facts
Answer Engine Insights
The vendor describes visibility scoring, sentiment, competitive benchmarking, and citation analysis across major answer engines. The practical value is prompt-level diagnosis: which questions mention the brand, which competitors appear, and which domains are cited. Ask for raw-answer retention, model/version metadata, sampling rules, and the exact definition of every score before using it in a client or board report.
Citation analysis
Profound’s citation feature is designed to show the URLs and domains influencing AI answers, including competitor citations. This can inform digital PR, content refreshes, and source-gap analysis. A cited page is evidence of what appeared in a sampled answer; it is not proof that the page is the sole cause of the answer or that outreach will reproduce the result.
Prompt Volumes
The official feature page says Prompt Volumes is based on 1.5B+ real user conversations and can surface demand, content gaps, and trend movement. This is a vendor-reported dataset-size claim, not an independently audited measure of every market’s demand. Treat the output as a directional planning input. Confirm coverage, geography, language, freshness, methodology, and whether the displayed volume is an estimate before comparing it with search-volume data from another provider.
Agent Analytics
Profound describes infrastructure-level monitoring for AI bots, AI-sourced visits, conversion events, rendering issues, structured-data gaps, and response-time problems. This can extend a visibility report into technical diagnosis, but it requires correct server-log or platform integration. AI crawler requests are not user visits, and AI-referred sessions do not prove that a cited page caused the visit.
Agents and content workflows
The vendor describes templates, custom agent building, brand context, briefs, content creation, and publishing integrations with human checkpoints. G2 product materials also describe agents for research and content operations. Treat this as workflow automation, not autonomous editorial authority: review generated claims, citations, disclosures, internal links, and publishing permissions.
A focused evaluation workflow
- Define the measurement scope. Select brand, product, category, comparison, reputation, and factual-accuracy prompts. Freeze the language, region, answer engine, model where available, and collection date.
- Use demand signals carefully. Prompt Volumes can identify recurring or emerging questions, but a high-volume prompt is not automatically a qualified buyer intent signal.
- Track answers and sources. Record the full answer, brand position, competitor mentions, sentiment label, cited URLs, and whether a URL is a direct citation or only a brand mention.
- Investigate the gap. Compare competitors and source domains, then assess whether the gap is content quality, authority, product data, technical accessibility, or prompt-sampling noise.
- Connect infrastructure signals. Agent Analytics can add crawler and AI-referral observations, but crawler activity, referral visits, and citations must remain separate metrics.
- Create reviewed actions. Agents can help draft briefs or content workflows. Human reviewers still need to check factual accuracy, originality, legal risk, brand voice, and whether the proposed source strategy is realistic.
- Re-measure consistently. Keep the same baseline prompt set long enough to identify directional change, and maintain a separate exploratory set for new questions.
03 / Commercial boundaries
Pricing & limits
Terms below reflect the 2026-10-12 source review, not a new live quote. Confirm currency, billing term, tax and required scope with the provider.
- Pricing at a glance
Current public access: A free trial provides 50 unique prompts daily for 7 days across ChatGPT, Gemini, and Google AI Overviews. Enterprise terms are custom.
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Overview
- Trial — free
The current official pricing page lists a free trial with limited AI Marketer credits, 50 unique prompts run daily for 7 days, and ChatGPT, Gemini, and Google AI Overviews. The FAQ states that trial users receive a recommended prompt set and cannot customize prompts. It also lists 5 Prompt Volumes searches, no history, no exports, no API, and no ChatGPT Shopping. The trial is useful for checking whether the interface exposes the evidence your team needs. It is not a representative test of ongoing Enterprise coverage: the duration, engines, prompt set, history, and exports are all constrained.
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Plans, pricing, and limits- Enterprise — custom
The official page lists tailored prompt tracking, up to nine answer engines, custom regions and languages, ongoing daily tracking, all-time history, CSV/JSON exports, API access, unlimited seats and domains, dedicated support options, and SSO/SAML with SOC 2 compliance. It also says Agents use credits and that usage depends on workflow complexity. No current numeric Enterprise price was exposed by the official pricing page checked on October 12, 2026. G2’s pricing page, last updated April 29, 2026, still displays five provider-supplied editions beginning at $99/month and says there is no free trial; that commercial snapshot conflicts with the current official page’s Trial/Enterprise presentation. Current third-party pricing research also describes Agency Growth at $99/month plus $399/month per client workspace, while warning that the billing term and some agency limits are not publicly stated. That agency offer is not a brand self-serve price. None of these figures should populate the schema’s starting price while the current official page presents the public brand offer as Trial plus custom Enterprise. Ask sales to put plan, credits, prompt limits, retention, engines, API, support, overages, agency workspace terms, and renewal terms in writing.
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Plans, pricing, and limits
- Free access & trial
Free; 50 unique prompts daily for 7 days
Archived research · Research dated 2026-10-12; confirm current termsResearch excerpt · Quick facts
Pricing context & qualifications
Trial — free
The current official pricing page checked on October 12, 2026 lists a free trial with limited AI Marketer credits, 50 prompts run daily for 7 days, and ChatGPT, Gemini, and Google AI Overviews. The page lists 5 Prompt Volumes searches, no history, no exports, no API, and no ChatGPT Shopping. Confirm whether the recommended prompt set and customization restrictions shown in the account flow still apply before treating the trial as a representative test.
The trial is useful for checking whether the interface exposes the evidence your team needs. It is not a representative test of ongoing Enterprise coverage: the duration, engines, prompt set, history, and exports are all constrained.
Enterprise — custom
The official page lists tailored prompt tracking, up to nine answer engines, custom regions and languages, ongoing daily tracking, all-time history, CSV/JSON exports, API access, unlimited seats and domains, dedicated support options, and SSO/SAML with SOC 2 compliance. It also says Agents use credits and that usage depends on workflow complexity.
No current numeric Enterprise price was exposed by the official pricing page checked on October 12, 2026. G2’s pricing page, last updated April 29, 2026, shows provider-supplied Enterprise contact pricing and review text about unclear tier visibility and Enterprise-gated history/API; older provider-supplied self-serve figures still conflict with the current official Trial/Enterprise presentation. Current third-party pricing research also describes Agency Growth at $99/month plus $399/month per client workspace, but that agency offer is not a brand self-serve price. None of these figures should populate the schema’s starting price while the current official page presents the public brand offer as Trial plus custom Enterprise. Ask sales to put plan, credits, prompt limits, retention, engines, API, support, overages, agency workspace terms, and renewal terms in writing.
04 / The tradeoffs
Strengths & weaknesses
Reasons to shortlist
- Strong breadth across visibility, citations, prompt demand, crawler activity, and AI referrals
- Consumer-facing answer-engine monitoring is positioned separately from static API-only checks
- Enterprise security and access-control claims are documented on the official feature page
- G2 provides a substantial public review sample compared with many newer GEO products
- Citation and competitor views can produce concrete source and content investigation tasks
Reasons to pause
- Current public pricing is quote-led; a historic third-party price may no longer describe the current commercial model
- Trial coverage is narrow, short, and based on a recommended prompt set, so it cannot validate all Enterprise workflows
- Prompt and visibility metrics are sampling-dependent and can change with answer-engine behavior
- Vendor case studies and customer logos are not independent causal evidence
- Agents may accelerate production but do not remove fact-checking, editorial governance, or CMS risk
The public plan comparison does not expose a current numeric Enterprise price, historical retention terms, or all usage allowances.
05 / Choose by the job
Alternatives to consider
Editorial fit comparisons—not performance rankings or claims that one option always wins.
Otterly.AI ↗
Otterly.AI: A lower-cost monitoring option for teams that prioritize prompt tracking and practical visibility reporting over enterprise infrastructure.
AI Search Console ↗
AI Search Console: Consider when the immediate requirement is a narrower monitoring workflow rather than a broad enterprise AEO operating layer.
AirOps ↗
AirOps: Worth comparing when content workflow governance and production execution matter as much as visibility measurement; verify the current product scope and price separately.
Manual evidence stack
Manual evidence stack: For a small pilot, a versioned prompt set, browser/API captures where permitted, server logs, analytics referrals, and a citation ledger may be more transparent than a large platform, although it carries maintenance cost.
06 / What we can substantiate
Reviews & evidence
The directly checked G2 listing reports positive themes around visibility data, citation clarity and competitive intelligence, while individual seller-invited reviews flag high cost, unclear tier visibility, Enterprise-gated history/API, and limited practical value relative to price. The Scalenut review also says teams need prioritization and existing SEO resources; it is commercially conflicted because Scalenut markets an alternative. These are directional usability and buying-friction signals, not proof of traffic, citation lift or revenue improvement.
AICiteKit assessment: public-source research, not a hands-on product test. Official materials establish stated scope; reviews are dated and may concern the broader platform. Neither establishes guaranteed citations, traffic or revenue.
Sources & original verification dates
Original review evidence & date context
Preserved from the published research. Dates, review counts and product-scope qualifications below have not been refreshed by this layout migration.
Evidence snapshot
| Evidence layer | Direct source and observed signal | What it supports | What it cannot prove |
|---|---|---|---|
| Official pricing | Profound pricing, checked 2026-10-12 | Trial limits, Enterprise/custom model, engine and export boundaries | A universal monthly price, ROI, or guaranteed outcomes |
| Official product | Features, checked 2026-10-12 | Named workflows, integrations, security claims, vendor-stated engine coverage | Independent accuracy, market representativeness, or causality |
| Official citation workflow | Citation analysis, checked 2026-10-12 | Product capability to inspect cited URLs and competitors | That a citation will persist or drive conversions |
| Official Agent Analytics | Agent Analytics, checked 2026-10-12 | Server-log AI crawler visibility, attribution, benchmarking, bot verification, and listed integrations | That crawler access caused citations, traffic, or conversions |
| Independent review platform | G2 reviews, checked 2026-10-12; 4.5/5 from 1,137 reviews shown | Directional usability/value feedback and recurring themes | GEO accuracy, citation lift, traffic, or revenue |
| Independent pricing snapshot and review text | G2 pricing, checked 2026-10-12; provider-supplied Enterprise contact pricing and reviewer comments praising data depth while flagging unclear pricing and Enterprise-gated history/API | Historical/current-context signal about price transparency and feature gating | The G2 snapshot is provider-supplied and not a definitive current contract |
| Commercial third-party review | Scalenut review, checked 2026-10-08 | Hands-on directional observations: useful visibility data, need for strategy, smaller-team friction | Neutral product scoring; the author sells a competing platform |
| Commercial third-party pricing review | Trakkr pricing review, pricing checked 2026-09-17 | Current-vs-historical brand pricing distinction and agency price signal: $99/month plus $399/month per client workspace | Neutral pricing evidence; Trakkr sells a competing tool and does not establish contract terms |
| Commercial third-party pricing review | Arobis pricing review, pricing verified 2026-10-01 | Confirms the current Trial/Enterprise brand presentation and documents the agency add-on boundary | Neutral pricing evidence; Arobis markets a competing service and its observations are not a vendor contract |
| Vendor-selected case studies | Profound features, checked 2026-10-08 | Vendor-reported Ramp, Hone, and OpusClip outcome claims | Independent attribution or reproducibility |
Recurring positive themes
The directly checked G2 listing shows a large review sample—4.5/5 from 1,137 reviews—and positive comments around an intuitive interface, actionable visibility data, and competitive intelligence. The Scalenut review similarly describes the visibility layer as useful for finding mentions, citations, sources, and competitors. These signals support a conditional claim that many users find the product useful for organizing AI-search intelligence, but G2’s product and pricing information is partly provider-supplied and should not be treated as neutral validation of current commercial terms.
Recurring concerns
The directly checked G2 pages show provider-supplied Enterprise contact pricing rather than a transparent public matrix. A G2 pricing review praises the depth of the data but flags high cost, unclear tier visibility, and Enterprise-gated history/API; another review describes limited practical value relative to price. Scalenut’s review also warns that teams still need prioritization and existing SEO resources, and that smaller teams may feel stretched; its commercial relationship lowers neutrality. Trakkr and Arobis independently document the newer agency pricing boundary, but both are commercially interested sources, so use them to frame buyer questions rather than as neutral market pricing.
AICiteKit interpretation
Confidence is medium for product scope, current trial boundaries, and the existence of user feedback. Confidence is lower for current self-serve prices reported by G2 or secondary pages because they conflict with the current official offer, and for all outcome claims. The evidence supports evaluating Profound as an enterprise measurement and workflow platform; it does not support promising a fixed citation lift, ranking improvement, traffic increase, or revenue result.
Research notes & unresolved discrepancies
- This page refreshes previously published research with a direct October 12, 2026 check of the official pricing, Prompt Volumes, Agent Analytics, citation, and current G2 review pages. It is not a hands-on test or an outcome benchmark; refer to source-specific dates and qualifications in the research context below.
Layout migration: October 4, 2026. The original MDX research is retained in the repository; this reorganization does not refresh its factual verification dates.