Peec AI

1. What Peec AI is and where it fits in GEO

Peec AI is an AI-search analytics platform for marketing teams and agencies. According to its official documentation, it repeatedly runs the prompts that matter to a brand, observes the resulting AI answers, and converts them into comparable measures: visibility, share of voice, position, sentiment, brand mentions, and cited or accessed sources.

The product is designed around a practical GEO loop. Teams define the questions and competitors that matter, choose engines and markets, examine where the brand appears, find the sources shaping those answers, and turn gaps into prioritized actions. Peec AI’s canonical product information describes this scope. It is not a model benchmark and it is not a general SEO rank tracker.

2. Core product areas

The official documentation describes the base loop around prompt-level visibility, position, sentiment, and sources. The vendor’s canonical product information adds current details about fanouts, crawl data, shopping, actions, exports, API, and MCP access.

3. Measurement model

Peec AI’s methodology description treats a single prompt run on one model, from one location and at one time, as the atomic observation. Product metrics aggregate those observations:

• Visibility: the share of observed answers where the brand appears.
• Share of voice: the brand’s mentions relative to all detected brand mentions.
• Position: the average ordering of the brand when it appears.
• Sentiment: the product’s score for how positively or negatively the brand is described.
• Sources and citations: pages accessed during answer formation versus the subset explicitly credited in the answer.

The vendor says most engine data is collected by simulating the consumer interface rather than by using model APIs alone. That is a useful design choice when the consumer product is the research target, but it does not make a single observation universal. Engine variation, location, personalization, UI changes, and prompt timing still require repeated sampling.

4. Engine coverage and pricing

The six default engines named on the Peec AI pricing page are ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, Gemini, and Microsoft Copilot. The vendor also offers other models as paid additions or higher-tier options. Availability should always be checked against the current plan rather than inferred from a platform-wide capability list.

As checked on 13 August 2026, the official pricing page and canonical product page list the brand Starter plan at $95/month, with 50 prompts, a choice of three default engines, one project, and daily tracking. Larger plans expand prompts, projects, markets, integrations, and support. Separate agency plans use a credit model.

The price is a dated fact, not a permanent product attribute. Compare the effective cost of the prompt × engine × country × frequency combination your program actually needs.

5. Fit and buying considerations

Peec AI is most differentiated by an analytics-first workflow and flexible ways to move results into reporting. That does not make every metric comparable with another vendor’s metric. Prompt construction, engine access method, geography, repetition, and aggregation rules need to be tested before switching tools or combining datasets.

6. Company, founders, and dates

The operating company is Peec AI GmbH, headquartered in Berlin. The company’s imprint names Marius Meiners, Daniel Drabo, and Tobias Siwonia as managing directors; its company information identifies them respectively as co-founder and CEO, co-founder and CRO, and co-founder and CTO.

Peec AI states that the company was founded in 2025 and that the product launched in February 2025. The .ai registry RDAP record reports that the current peec.ai domain was registered on 8 December 2024. These dates are compatible, but each describes a different event; the domain date is not substituted for the company or product date.

The official Series A announcement and independent TechCrunch coverage cross-check the founding team, Berlin base, February launch, and product focus.

7. Editorial assessment

Peec AI is a strong fit for teams that want a clean analytics-first GEO workflow, especially agencies managing multiple clients and in-house teams that need prompt, citation, and competitor evidence without starting from an enterprise-only sales process. Its actions layer makes the data more operational, while its API, export, and MCP options can fit a broader reporting stack depending on plan.

Evaluation should focus on evidence quality. Ask the vendor to show the raw captured answers behind a metric, rerun a small prompt set across your priority markets, and compare the result with a manual sample. A polished dashboard is useful only if the team can explain how a score was produced and what changed when an action was taken.