AI Visibility Tracker vs Profound

Profound is an enterprise answer-engine visibility platform: the vendor runs your prompts across up to nine AI engines, adds AI crawler and agent analytics, and sells it by subscription from $99/month at the entry tier, with enterprise quote-only. AI Visibility Tracker measures the same core thing — how often AI assistants cite your brand — as a macOS desktop app for $29 once, no subscription, running on your own API key with results stored on your own machine. If you need team seats, compliance paperwork or crawler data, Profound is the better product; if you need the measurement, the desktop app is usually enough.

Last updated 2026-07-28

What is Profound?

Profound is a cloud platform for tracking how brands appear in AI answers, aimed squarely at large brands and agencies. Its published tiers start at $99/month for a single seat, 50 prompts and ChatGPT only, rise to $399/month for three engines and 100 prompts across three seats, and become quote-only at enterprise, where coverage extends to up to nine answer engines including Copilot, Meta AI, DeepSeek and Google AI Overviews.

Its genuine differentiator is not the answer tracking, which several vendors do competently. It is Agent Analytics: measuring how AI crawlers fetch and interpret your site. Profound publishes scale figures in the billions of citations and crawler visits analysed daily, and offers SOC 2 Type II, SSO via SAML or OIDC, role-based access control and API access on the enterprise tier.

Where does Profound genuinely win?

In four places, and none of them are close calls. If any of these describe your situation, stop reading comparisons and go talk to them.

• Crawler and agent analytics. Knowing how often ChatGPT's or Perplexity's crawler fetches your pages, and what it appears to extract, is a genuinely valuable dataset that requires infrastructure at their scale. AI Visibility Tracker has no equivalent and no plan for one.
• Engine breadth at the top end. Up to nine answer engines including Copilot, Meta AI and DeepSeek versus five here. If Copilot matters to your buyers, this comparison ends there.
• Organisational fit. Seats, role-based access control, SSO via SAML or OIDC, SOC 2 Type II, automated backups and API access — the things that make a tool purchasable by a company rather than a person.
• Scale of measurement. Large prompt volumes across multiple markets, languages and brands, run by someone else's infrastructure on a schedule that does not care whether your laptop is open.

What exactly does AI Visibility Tracker do?

It asks the questions your buyers ask to five AI answer engines every day — ChatGPT, Claude, Gemini, Perplexity and Grok — checks each answer and its citations for your brand and your competitors, and reports the result as a Share of AI Answer score with a per-engine breakdown and a ranked list of the domains beating you.

Three implementation details are worth knowing because they determine whether the numbers mean anything. Every engine runs in its web-grounded mode, with no option to disable it: an ungrounded model answers from stale training data and fabricates citations that look entirely real once they are in a spreadsheet. Citations are read from each provider's structured grounding metadata rather than scraped out of the answer prose, because prose URLs are model output and model output can be invented. And the measurement models are fixed to consumer-representative tiers rather than being cost-optimised, because measuring ChatGPT with a cheap mini model measures a product nobody uses.

Everything is stored in a SQLite database on your own machine, including the full raw response from every call, so any number in the history can be audited back to the answer that produced it. API keys are encrypted with the operating system keychain and never written to that database in plaintext. There is no telemetry, no account, and no server of ours in the path. The details are in why web-grounded measurement is non-negotiable.

How do the two compare directly?

Is the measurement methodology comparable?

The discipline is the same on both sides — a fixed prompt set, grounded queries, citation checking, per-engine scoring — and the difference is what each side lets you inspect. With a cloud platform you are trusting a methodology you cannot audit: which model version represents each engine, whether grounding is on for all of them, and whether citations are read from provider metadata or parsed out of the answer text.

Those are the three questions worth asking any vendor in this category, including us. Our answers are specific and on the record: every engine runs in its web-grounded mode unconditionally; citations come from each provider's structured grounding metadata and never from a regex over prose; and measurement models are fixed to consumer-representative tiers rather than cost-optimised. Every raw response is kept locally, so any historical number can be traced back to the answer that produced it. See why web-grounded measurement is non-negotiable for the mechanism per engine.

What are AI Visibility Tracker’s real limitations?

It is a single-user desktop app, and every limitation follows from that. There are no team seats, no shared web dashboard, no SSO or SAML, no SOC 2 report, and no role-based access control — if procurement needs any of those, this is not a candidate and no amount of feature comparison changes that.

• macOS (Apple Silicon) or Windows (64-bit) — not Linux, and not a hosted option. The Windows build isn't code-signed yet, so it shows a SmartScreen warning on first run.
• Scheduled runs need your computer awake. A cloud platform runs at 3am regardless; this does not.
• You manage the API key and the spend. There is a cost preview and a per-run budget cap (default $5), but the account and the bill are yours.
• No crawler or agent analytics. Knowing how often ChatGPT's crawler hits your site is a genuinely useful, genuinely different dataset that platforms collect and this app does not.
• No multi-region or multi-language answer simulation. You measure from where you are.
• No vendor-curated industry benchmarks — you get your own numbers, not a comparison against a panel of brands you do not have access to.
• Prompt volume is bounded by your own API budget and patience rather than by a plan tier, which is an advantage until you want to run thousands of prompts across many markets, at which point managed infrastructure genuinely wins.

Why can this be a one-time price when everything else is a subscription?

Because the expensive, recurring part of AI visibility tracking — running thousands of grounded engine queries every month — happens on your own API key at cost, and the software runs on your computer instead of on infrastructure someone has to keep online for you. There is no per-seat server cost for us to recover monthly, so there is no monthly bill.

That is a genuine structural difference rather than a discount, and it cuts both ways. A cloud platform charges monthly because it is running queries for you, storing your history, keeping dashboards available to your team, and absorbing every provider API change. Pay $29 once and those things are yours to handle: your computer has to be awake for a scheduled run, your API key funds the queries, and your data lives in a file you are responsible for backing up.

So the choice is not really cheap versus expensive. It is whether you want a managed service or a tool. If you have an enterprise budget and a team that lives in shared dashboards, a platform is the better product. If you want the number on your own desk every morning without a recurring line item, that is what this app is for.

How current are these figures?

Competitor pricing below was read from each vendor’s own pricing page on 28 July 2026 and is quoted with the billing basis they display. Pricing in this category changes often — check the vendor’s page before making a decision on ours.