Profound
ToolEnterprise AI visibility platform
- Prompt tracking
- Competitor tracking
- Citation tracking
- Reporting
- Content recommendations
Editorial score breakdown
Scored from recorded research evidence. How scoring works.
Pros and cons
- Deep enterprise reporting
- Wide AI engine coverage
- Strong prompt analytics
- Higher price point
- Learning curve for small teams
Editorial review
Written from source-verified research (see Sources below and methodology). Vendor claims are labeled as such.
What Profound actually is
Profound's tagline calls it an enterprise AI visibility platform, but the current product is closer to an operating layer for answer-engine work than a tracking dashboard. Five surfaces make up the platform. Answer Engine Insights runs a defined prompt set daily and scores visibility, citations, sentiment, share of voice, and brand positioning. Prompt Volumes is a demand-research layer built, per the vendor, from licensed and anonymized real user prompts with panel projection. Agent Analytics ingests logs from CDN, cloud, and hosting integrations to show what AI retrieval bots actually fetch. Agents is a node-based workflow builder that can act on findings, calling APIs, generating content, and publishing. An enterprise layer of Knowledge Bases plus FactCheck compares model answers against an approved corpus of facts. The trajectory matters as much as the feature list. Over roughly a year the company shipped Query Fanouts, which exposes the retrieval queries generated from tracked prompts; announced a 35 million dollar Series B; introduced Agents alongside a 96 million dollar Series C in February 2026; and formally launched FactCheck in July 2026. The direction is consistent: from measuring AI answers toward automating the response to them. A vendor-described MCP server, launched in October 2025 and now exposing fifteen capabilities to tools like Claude Desktop and Cursor, extends the same idea, though which self-serve plans include it is not stated on the pricing page.
What day-to-day use looks like
Setup is prompt design, not dashboard reading. An admin selects the company, opens Prompt Designer, and adds prompts manually, from generated suggestions, or via bulk upload, tagging them for later segmentation. There is no instant baseline: first results typically arrive 24 to 48 hours after a prompt is added, then refresh daily on an Eastern Time cadence. Only admins can modify prompts, so the taxonomy work up front determines how useful the reporting is later. The working loop after that is filter, inspect, act. A practitioner filters a tagged prompt group, reviews the visibility, citation, or positioning changes, reads the captured answer and its cited source, and routes a gap into an Agent workflow. Documented examples include piping a visibility score through an LLM into Slack, and a Google-Search-to-LLM-to-WordPress publishing pipeline. Workflows are built on a canvas of inputs, conditions, loops, and processing nodes; they run manually, on a schedule, or against rows in Profound Sheets. The WordPress node writes posts through the REST API with an application password, and nine Google Workspace nodes cover Gmail, Docs, Sheets, and Slides. One metric detail worth internalizing early: Visibility Score is the share of responses mentioning your brand among responses that mention at least one brand, not a share of all collected responses. FactCheck runs on its own clock, with the vendor recommending roughly 100 to 200 factual prompts, a linked source-of-truth Knowledge Base, and about seven days of results before reviewing claim clusters.
Reading the pricing
The pricing table on this page shows the tiers; what it cannot show is how the meters interact. Every plan separately caps tracked prompts, monthly responses, and Agent credits, and a prompt is not a response: Starter's 50 prompts generate up to 1,500 responses a month and Growth's 100 prompts up to 9,000, because engine coverage and refresh frequency multiply. The functional gates matter more than the prompt counts. Starter is ChatGPT-only, one seat, one language and region, with no data export. Growth adds Perplexity and Google AI Overviews, three seats, and CSV/JSON export with all-time history, but still no platform API. Everything else, including the full ten-engine set, multiple companies, custom languages and regions, API access, SSO, and SOC 2 controls, is Enterprise, and the pricing FAQ steers any organization with more than three users or multiple brands there. The practical consequence is that teams can outgrow Growth on governance or geography before they exhaust its prompt allowance. In its bracket, the 99 dollar entry point sits against Semrush's standalone AI Visibility plan at 99 dollars per month per domain with 25 prompts, and Peec AI's published pricing from 95 dollars per month. Profound's Starter offers double Semrush's prompt count at the same price, but on a single engine. Both self-serve tiers are billed annually. Enterprise is custom; third-party reviews from Trakkr and Analyze AI have previously reported deals in the 2,000 to 5,000-plus dollar monthly range.
Who should buy it, and who should pass
The buyers who extract full value are teams with an actual answer-engine operating cadence: a brand or agency that will maintain a large tagged prompt program, review answer-level evidence regularly, and route findings into content or engineering work. Enterprise brands with accuracy exposure are the clearest fit for the top tier, because the FactCheck loop gives a fact-sensitive business a falsifiable pilot: seed an approved-facts Knowledge Base, monitor 100 to 200 factual prompts, verify the system surfaces known errors, correct the content, and measure whether the answers change. Agencies managing multiple brands land on Enterprise by definition, since multi-company support is gated there. The vendor itself positions Starter for small businesses and teams new to the category. Skip it, or at least pilot skeptically, in a few situations. If you need a one-off visibility report, the platform's workflow depth is overhead you will pay for and not use. If your market is outside the US, validate before trusting regional scores: one G2-hosted reviewer reported Canadian analysis surfacing US results without a country filter to isolate the target market, so a sensible pilot runs known country-sensitive prompts and audits the raw answers. If you need multi-engine coverage on a small budget, Starter's ChatGPT-only scope undercuts the headline price. And if your team has more than three users, needs multiple regions, or requires API access, you are an Enterprise negotiation rather than a 399 dollar self-serve customer, and should budget accordingly.
The evidence, weighed
Profound documents itself unusually well for this category, with a detailed help center, a public changelog, and disclosed methodology for Prompt Volumes: the vendor says the dataset is built from licensed, anonymized real prompts with panel projection to correct demographic, geographic, and churn bias, with US ChatGPT history beginning January 2025 and most other platforms and regions from July 2025. That is stronger disclosure than a bare proprietary-volume claim, but the inputs and model remain closed and cannot be independently reconstructed. The outcome numbers are vendor-reported. OpusClip's 45 percent visibility gain and top citation position in 30 days, Hone's 800 percent visibility increase, Arizona College's 51 percent improvement in AI-referral conversion, Ramp's seven-fold visibility, and GR0's account of a client growing from roughly 1,000 to 100,000 dollars in monthly AI-attributed sales all come from Profound's own customer gallery; they are selected narratives, not independent experiments. Third-party reviewer evidence is more mixed. G2 reviewers specifically praise access to the full answer and citation record for individual prompts, weekly visibility summaries, and hands-on strategy support. On the other side, reviewers report an Average Position metric that can be polluted by generic or undefined brand names, metrics that sound similar or occasionally appear inconsistent, prompt edits that sometimes fail on the first attempt alongside slow pages, and recommendations that point in the right direction but lack specificity about what to change and how to measure it. Some operational details are simply unpublished, including the enterprise data API's schemas and rate limits, Agent Analytics volume limits, and any alert-latency guarantee. None of this is disqualifying, but each item belongs on a trial checklist rather than being taken on faith.
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Frequently Asked Questions
>What is Profound best for?
Enterprise brands and mid-market SaaS
>What does Profound cost?
From $99/mo (billed annually). Engines are tier-gated: Starter is ChatGPT-only; Growth covers 3 engines; up to 10 on Enterprise. Enterprise deals were previously reported at $2,000-5,000+/mo by Trakkr and Analyze AI (third-party). See the vendor's pricing page for current details.
>Which AI engines does Profound cover?
ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews, Copilot. Engine coverage can be tier-gated — see the pricing notes and editorial review for specifics.
Sources
- Profound pricing (published plans) — checked 2026-07-23
- Profound reviews on G2 — checked 2026-07-23
- Profound $96M Series C at $1B valuation (SuperbCrew) — checked 2026-07-23
- Profound pricing review (Trakkr, third-party) — checked 2026-07-23
- Profound review (Analyze AI, third-party) — checked 2026-07-23
- Profound Series B announcement - customers, scale (PRNewswire) — checked 2026-07-23
- Profound free AEO Report — checked 2026-07-23
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