> ## Content Index > Fetch the complete content index at: https://www.reputation-insider.com/llms.txt > Use this file to discover other available public pages before exploring further. # Peec AI review - URL: https://www.reputation-insider.com/peec-ai-review/ - Published: 2026-09-21T07:14:04.000Z - Updated: 2026-09-21T07:25:53.000Z - Description: The Berlin startup tracks brand visibility and source attribution across major AI systems, with public pricing and a still-small independent review base. - Author: Levi Mastarel - Tags: Vendors, #main-vendors, AI visibility tools, AI reputation management, AEO, GEO, Reputation management Vendor review # Peec AI review Peec AI gives marketing teams detailed visibility into how brands appear across AI search, with public pricing, source-level evidence and strong agency tooling. Its measurement category is still young, and the independent review base remains small. Reviewed September 2026 Product record Category AI search analytics, GEO and brand visibility monitoring Buying route Public self-service plans plus enterprise contracts Primary buyers In-house marketing and SEO teams, brands and agencies Founded 2025 Headquarters Berlin, Germany Funding About $29 million disclosed Review basis Reputation Insider reviewed Peec AI's current product, pricing, agency, Actions, Brand Perception, AI Referrals, Agent Analytics, AI Shopping, MCP and integration materials; Terms of Service and Privacy Policy; current G2 and Capterra profiles; and independent reporting on the company. Measurement model ## Peec is built around repeated prompt tracking rather than a single AI visibility score Peec AI says it runs customer-defined prompts against selected AI systems on a recurring schedule and stores the resulting answers, brand mentions and sources. Its public methodology describes each individual prompt run against one model, location and date as the basic measurement unit. Standard tracking cadence **Daily** Self-service plans currently use daily tracking. This makes Peec more useful for examining movement over time than for treating one generated answer as a definitive representation of what every user will receive. Prompts **The customer controls the queries being measured** Teams can build a tracked prompt set around buying questions, brand terms, categories, personas and stages of the customer journey. Models **Results can be separated by AI system** Peec currently supports tracking across major answer and search products rather than collapsing all generated responses into one undifferentiated figure. Geography **Projects can distinguish performance by market** Geographic tracking is useful because an AI answer can differ according to the market from which the query is executed. Sources **The underlying response and cited URLs remain available for inspection** Buyers can move from an aggregate metric back to the individual answer and the sources that contributed to it. Peec publicly explains its prompt, model, geography and source framework in useful detail. The public materials reviewed by Reputation Insider do not fully specify every session-state or personalization variable needed for an outside researcher to reproduce every individual observation exactly. AI-generated answers are also inherently variable, so trend interpretation is more defensible than treating a single response as universal. Core analytics ## The main dashboard separates presence, competitive position and portrayal Peec's [core product](https://peec.ai/?ref=reputation-insider.com)measures several different questions about a brand instead of reducing AI search performance to whether the company was mentioned at all. Visibility **How often the brand appears** Visibility measures the proportion of tracked AI answers in which the monitored brand is present. Position **Where the brand appears relative to competitors** Position gives teams a way to distinguish simple inclusion from stronger prominence inside the answer. Sentiment **How the generated answer characterizes the brand** Sentiment adds reputational context when being mentioned positively, neutrally or negatively carries different commercial meaning. Sources and citations ## Source attribution is one of the more useful parts of Peec for reputation teams The platform records which domains and URLs are used or cited in tracked AI responses. That gives communications and reputation teams evidence about which external pages are contributing to an AI system's description of the company. Reputation use case **Teams can trace a generated claim back to the material influencing it** This is particularly useful when an unfavorable description is being supported by a review site, publisher, comparison page, community thread or outdated owned page. **Domain and URL detail** Peec lets teams inspect the publications and individual pages appearing across tracked answers rather than stopping at a source-category total. **Competitor source gaps** Teams can identify sources that repeatedly support competing brands while giving little or no visibility to their own. **Owned versus third-party influence** Source analysis can separate problems that can be addressed on a company's own site from those requiring PR, community or third-party work. **Historical comparison** Recurring runs make it possible to see whether a new source has entered the answer set or an established citation has disappeared. Actions ## Peec now tries to turn monitoring data into a prioritized work queue [Actions](https://peec.ai/product-actions?ref=reputation-insider.com)analyzes source patterns and competitive gaps, then suggests opportunities that a marketing team can review and decide whether to pursue. Owned media **Pages the company can create or improve** Recommendations can identify product pages, comparison pages, articles or other owned content associated with missed visibility. Editorial **Publications influencing the category** Peec can surface external editorial sources that receive citations and where competitors have stronger representation. UGC **Community sources that appear in answers** Reddit, forums and other user-generated sources can be separated from editorial and owned-media opportunities. Reference sources **Structured third-party pages can be identified separately** Directories, databases and reference sites can require different remediation from editorial outreach or content production. **Peec deliberately leaves execution with the customer.** Actions does not automatically write and publish the recommended content. Peec says the feature prioritizes opportunities and explains its reasoning, while the customer decides whether the recommendation is strategically appropriate. Product expansion ## Peec is expanding beyond basic prompt visibility into reputation, traffic and commerce measurement Several 2026 releases broaden the product from a GEO rank tracker into a wider AI-discovery analytics platform. Brand Perception ### AI-generated brand attributes can be measured separately from visibility The current product surfaces recurring descriptions attached to a brand, compares them with competitors and traces those descriptions to supporting sources. AI Referrals ### Traffic from assistants can be connected to website outcomes A Google Analytics connection shows sessions, engagement, conversions and revenue attributed to AI-assistant referrals. Agent Analytics ### AI crawler activity can be compared with citation performance Peec tracks which AI bots reach a website, the pages they request and whether technical controls block or allow them. AI Shopping ### E-commerce teams can monitor individual products in AI recommendations Shopping analytics adds SKU-level visibility, product position and source data for brands whose AI-search problem extends beyond corporate mentions. Data access and reporting ## Peec is unusually open about getting monitoring data out of its own interface Reporting options include CSV export, Looker Studio and programmatic access, reducing the need to use Peec's dashboard as the final reporting surface. Peec MCP **Visibility data can be queried from external AI tools** Peec's [MCP server](https://peec.ai/mcp?ref=reputation-insider.com)connects monitored data to compatible tools such as Claude, Cursor and workflow systems, allowing teams to build recurring reports and custom data workflows. **CSV and dashboards** Teams can export data for offline work or use Looker Studio to create internal and client-facing reporting. **API** Programmatic access supports organizations that want Peec data inside a wider BI, analytics or reporting environment. **MCP workflows** Agencies can automate recurring client summaries or combine Peec data with other sources without manually rebuilding the same report each week. Pricing ## Peec publishes self-service pricing and charges primarily around tracking volume Peec's [brand pricing](https://peec.ai/pricing?ref=reputation-insider.com)scales according to tracked prompts, models and project capacity. Annual billing currently carries a 15% discount. [Published pricing ↗ ](https://peec.ai/pricing?ref=reputation-insider.com) Starter **$95/mo** *50 prompts · 1 project* Three selected models, daily tracking and unlimited users. Pro **$245/mo** *150 prompts · 2 projects* Higher monitoring volume with the same daily tracking cadence and unlimited users. Advanced **$495/mo** *350 prompts · 5 projects* Adds broader multi-market use and more advanced reporting capacity. Enterprise **Custom** *Negotiated scope* Designed for wider model coverage, custom prompt volume, API access, SSO and dedicated support. Agency pricing **Separate multi-client plans** Peec also publishes agency packages: Essential at $245 per month, Growth at $495 and Scale at $795, with Comprehensive priced by agreement. Agency capacity is allocated across client projects rather than purchased as separate single-brand subscriptions. Pricing can rise when teams need more prompts or broader model coverage. Peec's own pricing FAQ says models beyond the included allocation can be added separately, so buyers should model the actual prompt × model combination they intend to monitor rather than compare plans only by the headline monthly fee. Contract and cancellation ## Peec's public terms are relatively clear for a young B2B SaaS product The current [Terms of Service](https://peec.ai/legal/terms-of-use?ref=reputation-insider.com)were last updated in December 2025 and apply only to business customers. Monthly subscription **Cancellation can take effect at the end of the current payment cycle** The public terms allow ordinary termination of a monthly subscription without requiring a longer notice period. Annual subscription **Thirty days' notice is required for the end of a 12-month term** If renewal has been agreed and notice is not given in time, the subscription can renew under the agreed commercial terms. Early exit **Prepaid fixed-term fees are generally not automatically refunded** The terms provide pro-rata refunds for future periods mainly when termination results from Peec's fault or an uncured breach by Peec. Customer references **Peec reserves a contractual right to identify customers publicly** The terms permit use of the customer's name and logo in factual marketing references, with an objection route available for legitimate reasons. **The legal definition of the service is narrower than some marketing language.** Peec's terms describe monitoring, source collection, sentiment indicators and prompt suggestions, while stating that the company does not guarantee prompt suitability or effectiveness and does not itself ensure improved visibility or sentiment. Buyers should therefore treat recommendations and visibility changes as measurement outputs rather than contractual performance commitments. Security and data posture ## Peec publishes useful infrastructure detail, but formal assurance is still developing The [Privacy Policy](https://peec.ai/legal/privacy-policy?ref=reputation-insider.com)was updated in January 2026 and describes Peec AI GmbH as the GDPR controller for relevant customer and website data. Encryption **Peec says data is encrypted in transit and at rest** The privacy documentation also describes restricted internal access, credential controls and regular security maintenance. Infrastructure **Core application data is hosted on Google Cloud** Firebase and Google Cloud services are used for authentication, databases and application infrastructure. Processors **Several external SaaS providers participate in the service** Peec identifies providers including PostHog, Intercom and Sentry and says data-processing agreements are in place with its processors. Formal assurance **Public materials describe SOC 2 as work in progress** Reputation Insider did not identify a current public SOC 2 report or ISO 27001 certificate for Peec AI itself. Enterprise buyers requiring certification should request the latest assurance package during procurement. Buyer fit ## Peec is most useful when a team already knows which AI-search questions it needs to monitor Suitable for ### Brands and agencies building a repeatable AI-search measurement program SEO, digital PR, brand and reputation teams can use Peec when they need to monitor a defined set of customer questions across several AI systems and compare changes over time. The source-level data is particularly useful for teams whose work includes earned media, third-party reviews, reference sites or other external material that can influence AI answers. Agencies gain additional value from multi-client projects, pitch workspaces and reporting integrations that make the product easier to operationalize across accounts. Not suitable ### Teams looking for conventional reputation monitoring or fully automated execution Peec does not replace news monitoring, social listening, review monitoring or other systems designed to detect reputation issues across the wider public web. Companies expecting the software to automatically produce and publish the content required to improve AI visibility will still need a separate execution workflow. Very early brands with little presence in AI answers may also have less material to interpret until their broader web footprint and category visibility become substantial enough to generate useful comparative data. ## Pros - Public self-service pricing makes initial budget comparison easier than with fully sales-led AI-search vendors. - Prompt-level history and source attribution give teams access to the evidence beneath aggregate visibility metrics. - Brand Perception adds reputational context beyond simple mention frequency. - Agency plans are designed around multi-client work rather than requiring a separate account for every brand. - MCP, API, CSV and Looker Studio options make the data relatively portable. - Recent product releases connect AI visibility with crawler activity, referrals and product-level shopping discovery. ## Cons - The independent user-review corpus is still small for a product being considered by enterprise marketing teams. - Additional model coverage can increase cost beyond the headline self-service plan price. - AI-generated answers remain variable, so individual tracked responses should not be treated as universal customer experience. - Public methodology does not expose every execution and session-state variable required for complete external replication. - Some user feedback still points to manual filtering and reporting work when deeper analysis is required. - Peec remains an AI-search analytics product rather than a substitute for broader reputation, media or social monitoring. Independent user evidence ## Early reviews are strongly positive, but the sample remains too small to treat the rating as mature G2 is currently the main software-review source with a meaningful Peec AI user corpus. Capterra has created a product profile but does not yet display a user rating. 4.7 / 5 G2 21 reviews when checked in September 2026 No rating Capterra Product profile live; no user-review score when checked ### Ease of setup is a recurring strength Recent verified G2 users describe onboarding and the dashboard as straightforward, including teams that wanted AI-search data without building their own tracking infrastructure. ### Source and citation data receives consistent praise Reviewers repeatedly mention the ability to inspect citations, compare prompt performance and follow visibility changes over time as useful parts of the product. ### Deeper reporting can still require manual work One verified G2 reviewer specifically noted that valuable analysis can depend on exports, filtering and additional report setup despite the clean interface. Peec AI launched in 2025 and is still changing quickly. Aggregate reviews therefore combine experiences across different versions of the product, while several major capabilities covered in this review were added during 2026\. External evidence: [G2](https://www.g2.com/products/peec-ai/reviews?ref=reputation-insider.com)and [Capterra](https://www.capterra.com/p/10030058/Peec-AI/?ref=reputation-insider.com). Reputation Insider verdict ## Peec AI is a serious measurement product for teams that want to inspect the evidence behind AI visibility Its strongest characteristic is the connection between a tracked prompt, the generated answer and the sources behind it. That makes the platform useful for reputation and communications work where teams need to understand which external material is influencing an AI system's description of a brand. The newer perception, referral and crawler products extend the use case beyond a simple GEO dashboard. The main caution is methodological: AI answers vary, and Peec's metrics are observations from a controlled monitoring system rather than a census of every answer delivered to every user. Buyers should judge the product on whether its prompt set, geographic configuration and model coverage reflect the decisions they actually need to measure. A well-configured project can provide useful longitudinal evidence; a weak prompt framework will produce precise-looking data around the wrong questions. Strongest use case Brands and agencies running structured AI-search visibility and source-attribution programs Most useful capability Connecting AI-generated brand claims to the domains and URLs influencing them Main limitation A young measurement category with variable model outputs and a still-small independent review base Reputation Insider view A credible AI-search monitoring option when prompt design and measurement methodology are treated as part of the purchase