Peec AI and Profound are two of the better-known tools for generative engine optimization (GEO), the practice of improving how a brand appears in AI-generated answers. On their feature pages they look almost interchangeable: both run a list of prompts through AI answer engines every day and report visibility, share of voice, sentiment and citations.
The trade-offs that matter to a buyer sit in three places the feature pages don't put side by side: how each tool collects its answers, how it turns those answers into numbers, and how it is packaged and sold. Each suits a different kind of team; there is no universal winner.
This comparison draws on each vendor's public documentation, pricing pages and changelogs, read on 14 and 15 October 2026, not on hands-on use. When we say a capability is "not documented publicly as of October 2026", we mean we couldn't find it, not that the product lacks it.
Where do the answers come from?
The first trade-off is whether the tool shows what real users see. It can capture the consumer interface, meaning the chat app a person actually uses. Or it can send the prompt to the model through an API (application programming interface), the channel developers use. The two can return different answers.
Both vendors say they capture the consumer interface. Peec's documentation says it "uses UI scraping technology to interact with AI platforms exactly as real users do". Profound's documentation, last updated September 2026, says it "captures AI responses directly from the consumer browsing experience rather than from model APIs". Both are vendor claims; we found no independent test of either.
Peec's claim does not cover every model it sells. Its pricing page, read 15 October 2026, gives several Enterprise models an "API" label, including Claude Sonnet 4, Grok, DeepSeek and Mistral. So Claude coverage from Peec is API testing. It shows what the model says when asked directly; it does not show what a person using the Claude app sees.
Coverage also depends on the plan. Peec's self-serve plans include 3 models, chosen from ChatGPT, Google AI Mode, Google AI Overviews, Microsoft Copilot, Gemini and Naver AI. More models can be bought as paid add-ons from the dashboard, and that add-on list includes Perplexity. The API-labelled models are listed only on Enterprise. A third-party tracker dates a change to these terms to 21 September 2026, so older reviews may describe different plans.
Profound's free trial covers 3 engines: ChatGPT, Gemini and Google AI Overviews. Its Enterprise plan lists up to 9, including Claude, Perplexity and DeepSeek, and labels none of them as API. Profound's own pages disagree on the exact list, so ask for it in writing. For a wider view, see which GEO tools track ChatGPT, Claude, Perplexity and Gemini.
Why can't you compare a Peec score with a Profound score?
Once the answers are collected, each tool turns them into metrics with the same names but different formulas, so a score from one can't be read against a score from the other.
Visibility is the share of answers that mention your brand, but the two tools count "answers" differently. Peec divides the responses that mention your brand by all responses. Profound divides the runs that mention your brand by the runs that mention any brand, leaving out answers that name no brand.
Profound then adds a second step. It calculates visibility for each AI model separately and averages the models with equal weight. If your brand appears in 40% of one model's answers and 60% of another's, Profound reports 50%, even when the second model ran twice as many prompts. Pooling all the answers would give about 53%.
The two steps pull in different directions. Leaving out no-brand answers raises Profound's figure. Equal weighting can raise or lower it, depending on which models mention you most. So on the same answers, Profound's number can come out higher or lower than Peec's. What this means: neither formula is wrong, but they answer different questions, and a gap between the two numbers tells you nothing about which tool sees you better.
The other headline metrics diverge in the same way:
- Sentiment. Peec scores the tone of the language around your brand on a 0–100 scale. Profound reports the share of claims about your brand that are positive. One is a tone score and the other a ratio, so they can't be compared.
- Citations. Peec separates sources the AI retrieved while answering from sources it actually cited in the text. Profound's documented citation metrics, Citation Share and Citation Coverage, count cited URLs. A retrieved-but-not-cited measure is not documented on Profound's public pages as of October 2026. See what a sources report counts.
Both tools can also rewrite history: in each, editing settings such as brand names or aliases recalculates past numbers. Compare trends inside one tool, and record your settings before you report a number. See why past visibility numbers can change.
What can you take out of each tool for reporting?
Those numbers then have to reach a manager or a client, and here the packaging starts to show.
Every Profound plan includes Custom Dashboards, which can be shared by link or email and downloaded as a PDF.
Raw numbers are less clear. Profound's dashboard FAQ says dashboards "currently export only as PDF". Its changelog entry of 9 October 2026, however, describes an "Export as Zip" option that downloads each chart's raw data as a CSV file, a plain format any spreadsheet can open. Ask which description is current.
Profound's Enterprise plan adds file exports, an API that returns each individual answer, a Tableau connector and an MCP server. MCP (Model Context Protocol) lets an AI assistant such as Claude query the tool directly. Profound's MCP analytics tools are read-only; its prompt tools can edit prompts.
Peec documents CSV export from charts and of all the answers in a project. Its MCP server has both read and write tools, and the write tools are flagged so that clients such as Claude ask for confirmation first. See what an AI assistant gets from MCP access.
Plan gating at Peec is harder to pin down. Its API, like Profound's, is Enterprise-only. A Looker Studio connector is listed on the Advanced plan, but Peec's docs say it needs an API key. Automated reporting and shareable dashboards are also listed, but which plans include them could not be confirmed as of 15 October 2026.
What does each plan include, and what will it cost?
Packaging is where the two tools differ most. Peec sells published self-serve tiers; Profound sells one custom-priced plan after a free trial. Both reserve the API and single sign-on (SSO), which lets staff log in through the company's identity provider, for Enterprise.
| Peec AI | Profound | |
|---|---|---|
| Entry option | Self-serve tiers: 50, 150 or 350 prompts | Free 7-day trial: 50 fixed prompts |
| Engines below Enterprise | 3 included; extra models as paid add-ons | 3 on trial |
| Engines on Enterprise | Up to 13, from a list that includes 7 API-labelled models | Up to 9, none labelled API |
| API | Enterprise only | Enterprise only |
| SSO | Enterprise; SAML only, set up by Peec | Enterprise; SAML and OIDC, plus SCIM |
| Seats | Unlimited | Unlimited |
| Price | Published, in local currency | Custom quote |
The Enterprise engine counts are not like for like: Peec's includes API testing, while Profound presents its engines as consumer-interface capture. Sources: peec.ai/pricing, docs.peec.ai/sso, tryprofound.com/pricing, Profound SSO docs, all read 15 October 2026.
Peec's self-serve tiers run daily and cap the number of countries per project. For sign-on, Peec supports only SAML, the most common enterprise sign-on standard. It does not offer OIDC, a newer alternative standard, or SCIM, which adds and removes users automatically. We have not printed Peec's prices, because they load in local currency and third-party snapshots disagree.
Profound's trial uses a fixed prompt set with no history, exports, API or SSO. Its Enterprise plan adds all-time history, activity logs, and agents and content tools. See what a 7-day trial can prove.
On security, as of October 2026, Profound states it is SOC 2 Type II compliant, an independent audit of data controls, while Peec says it is "actively pursuing" that certification. See which GEO tools can show an independent security audit.
Which one fits your team?
These differences point to two different buyers.
Peec fits a team that wants to set itself up, pay a published price and check a prompt list regularly. The trade-off is that self-serve plans include 3 engines and a capped number of countries. Extra engines cost more as add-ons, and the API-labelled models, the API and SSO require Enterprise.
Profound fits a team ready to buy at enterprise level, in return for more engines, admin controls such as SCIM, and agents and content tools in one contract. The trade-off is that there is no published price and no paid entry tier for a single brand.
Public user feedback is thin, and each comment is one person's view. Mindy Faieta of Stateshift, a Peec customer, listed "Historical data only goes back to when you started tracking" among Peec's limitations in November 2025; her post predates several Peec releases. Profound's G2 reviews, read through the AWS Marketplace mirror, include Aman S., who in September 2026 praised "Being able to see exactly where a brand is cited" but called the tool "very expensive and complex". Two other recent reviewers there, writing on 27 August and 1 October 2026, mention a learning curve. Peec's G2 page could not be read.
Before you sign with either tool, get these five answers in writing:
- Which engines your plan covers, and whether each is captured from the consumer app or the API.
- The exact formula behind visibility, sentiment and citation metrics.
- Which setting changes rewrite past numbers.
- Which plan includes the API, the MCP server and any reporting connector.
- The current price and limits, dated.
For the same questions applied to more vendors, see our comparison of nine GEO platforms.