Tellr vs Peec AI: A Mentions Dashboard vs a Program

In Tellr vs Peec AI, you are choosing between two models. Peec AI is a self-serve AI search analytics platform that tracks how often, where and how favorably AI engines mention your brand. Tellr is a managed earned-visibility program that produces the content, Reddit replies and ad creative that change those answers. Peec AI tells your team where it is missing. Tellr's senior team does the work that changes it, under approvals and an audit trail. Both are reasonable purchases in October 2026, but they solve different problems, cost different amounts and need different teams around them.

What separates a mentions dashboard from a program

A mentions dashboard observes and reports what AI engines say about your brand. A program changes what they say by producing and placing the sources those engines cite. The first is passive monitoring and the second is active optimization, and that difference decides who on your team does the work.

Peec AI: the mentions dashboard

Peec AI is a Berlin-based, venture-backed company founded in 2025 that makes an AI search analytics platform for marketing teams. You load a library of prompts, pick engines and competitors, and Peec runs scans and reports the results. It measures:

• Brand mentions in AI-generated answers
• Citations, attributed down to the URL level
• Share of voice against named competitors
• Sentiment of each mention
• Position within AI answer shortlists

Data refreshes daily on paid plans. Plans are tiered monthly with unlimited seats, and a 7-day free trial needs no credit card. Peec stops at reporting and recommendations. Nothing in its feature set covers writing briefs, publishing articles, outreach or creative, and it does not estimate traffic volumes or pipeline conversions. Success with Peec means your team reads the data correctly and ships the fixes itself.

Tellr: the program

Tellr is a premium earned-visibility agency whose senior team runs one governed program on Tellr's own platform. It writes comparison pages, reviews and answer-shaped articles from the brand's knowledge base and real user reviews, publishes them to the client's CMS, places guideline-checked Reddit replies and produces ad creative. Every draft is checked against a brand brief and claim guardrails, then passes an approval gate. Tracking is there to choose the next piece of work, and success means the brand's citation share for category queries rises week over week. Pricing is scoped per engagement on a demo call. Tellr is not built for launches that need results within three weeks.

• Reddit: subreddit mapping, a daily thread radar and replies behind an approval gate
• Content: pages built to be quoted by ChatGPT, Perplexity and Google AI Overviews
• Answer visibility: weekly tracking of who Google and AI Overviews cite
• Paid media: category ad intelligence and ready-to-run creative

Tellr and Peec AI compared on eight dimensions

Peec AI wins on breadth and frequency of monitoring. Tellr wins on the ability to change outcomes, because it produces the sources the engines cite. The table compares both models on the points that matter when you buy for an enterprise marketing team.

A dashboard that refreshes daily gives you more data points, but the AI answer only moves when a new source gets cited. Actionability decides ROI, because it separates influencing outcomes from observing them. If you are also weighing other trackers, our roundup of AI visibility tools and platforms covers the wider field.

How to judge the measurement behind each approach

AI visibility data is only as trustworthy as its prompt set, run frequency, sample size and collection method, so check those four things before you trust any trend line. Language models are non-deterministic. The same prompt can return a different shortlist on two runs minutes apart.

Prompt selection

Build the prompt set from real buying questions, split across funnel stages. For example, a cloud security vendor might track 150 prompts:

1. Discovery, non-branded (about 50%): "best cloud security platform for a 5,000-person company"
2. Consideration, comparison (about 30%): "Wiz vs Orca for multi-cloud"
3. Decision, branded (about 20%): "is [brand] SOC 2 compliant", "[brand] pricing"

Branded prompts inflate visibility scores, because engines almost always mention the brand you name. Non-branded discovery prompts show whether you are found at all. Deduplicate before you start, because duplicate prompts double-count the same answer.

Frequency, sample size and variance

Run each prompt more than once per period and track the average. As an illustrative rule, run each prompt at least three times per reporting window, and treat any share-of-voice move under five points on a set of fewer than 100 prompts as noise until it holds for three consecutive periods. Peec's daily refresh helps smooth variance. Tellr's weekly tracking matches a program that ships work every week.

Logged-in, browser and API results

API responses often differ from what a signed-in user sees, because consumer apps add web search, memory and personalization. Peec's browser session emulation gets closer to the consumer view. Location matters too. An AI Overview in Frankfurt can cite different domains than one in Chicago, so confirm that tracking runs in the markets where your buyers sit.

Where visibility data misleads

Visibility data misleads when teams read movement as market position, because a mention does not mean the brand influenced a buying decision. These interpretation errors apply to any dashboard, including the tracking inside a program.

Sentiment skew is where the two models split most clearly. Say a 2023 thread calling your product "overpriced and slow" is cited in 30% of answers about your category. A dashboard flags the negative sentiment. A program fixes it. A governed, factual reply in a live thread, a current comparison page and a review roundup built from recent user reviews give engines better sources to cite. Our guide to tracking what the models say about you covers how to spot these source problems week by week.

Validating influence on pipeline

Neither approach proves revenue alone. Peec does not estimate traffic or pipeline, and Tellr's tracking measures citations, placements and rankings. Validate with three signals together:

1. AI referral sessions in GA4 (referrers such as chatgpt.com and perplexity.ai) landing on the pages you created
2. Branded search impressions in Search Console rising after citation share rises
3. A "where did you first hear about us" field on demo forms, coded by source

Turning visibility data into work every week, month and quarter

A dashboard only pays off when someone turns its output into shipped work on a fixed schedule, and a program has that schedule built in. The table below shows who does each job under each model.

Organizational requirements

Running a dashboard well takes people more than budget. Plan for:

• An owner who reads the data at least weekly and turns it into briefs
• Writers who can produce comparison pages and answer-shaped articles
• A community manager who knows subreddit rules and has time for Reddit
• Legal or brand review for anything posted under the company's name

A program shifts that load to the vendor. Your team supplies the brand brief, approves drafts and steers priorities. The budget is higher and the internal headcount is lower.

Time to value

Peec gives useful data fast. Reviewers describe being up and running with minimal configuration and seeing results immediately. Changing answers takes longer under either model. In week one, Tellr's onboarding builds a category map of the threads, queries and AI answers that matter. In week two it agrees the brief and guardrails, then moves to weekly work. First citation gains arrive once published pages get indexed and picked up, which takes months rather than days.

What Peec AI users say about the gap between data and action

Peec AI users rate the platform highly for tracking. Their main complaint is the gap this comparison is about: it shows visibility but does not tell them how to improve it. As of October 2026, Peec AI holds a 4.8 out of 5 rating on G2 across 21 reviews.

Reviewers single out prompt tracking and competitor visibility, and often say it surfaced competitors they had not seen in traditional SEO. They value the MCP integration and responsive onboarding support, and several call it the best value for money in the GEO space.

What users like

• Strong visibility, sentiment and competitor tracking across ChatGPT and Perplexity
• A source and citation view that shows which URLs the models cite and which pages to target

What users criticize

• Limited actionable recommendations tied to the reviewer's business context
• Extra models such as Grok or Claude locked behind higher tiers
• Onboarding that generates overlapping suggested prompts needing manual cleanup
• No page-level AEO readiness feature, which some competitors offer

Which approach fits your team

Peec AI fits teams that want affordable, broad monitoring and have the staff to act on it. Tellr fits enterprises that want the replies, pages and creative produced under governance. Role and company size decide most of it.

A scoring model you can use

Score each option from 1 to 5 on five criteria and weight them. Here is an example weighting for an enterprise demand gen team: ability to change outcomes 30%, citation share and position measurement 20%, governance 20%, pipeline validation support 15%, sentiment insight 15%. A team with ten writers and a community manager might cut "ability to change outcomes" to 10% and raise measurement breadth, which tilts the result toward a dashboard.

Signals you have outgrown a mentions dashboard

• The weekly report flags the same gaps for three months running because nobody has time to fix them
• Competitors own the Reddit threads and comparison pages that AI answers cite
• Legal blocks Reddit activity because there is no approval trail
• Leadership asks what changed, not what the chart shows

Buyer checklist

1. What share of our prompts are non-branded discovery queries?
2. How many runs per prompt per period, and how is variance handled?
3. Is collection by browser session, API or panel, and in which locations?
4. Who writes, approves and publishes the fix, and how long does each step take?
5. What audit trail exists for every Reddit reply and published claim?
6. How will we connect citation gains to referral traffic, branded search and demo forms?

For a related comparison against another tracker, see Tellr vs Profound. The short version of Tellr vs Peec AI is this. If your team will execute, buy the dashboard. If your team needs the execution done with guardrails and approvals, buy the program.

FAQ