Comparison
Peec AI vs Ternith
Peec AI is a dedicated AI-visibility platform — it tracks your brand across AI platforms with four scored metrics: Visibility, Share of Voice, Sentiment, and Position. Ternith answers a different question: which of three patterns is showing up in your results, and where to start.
Peec AITracks the number.
TernithExplains it.
Side by side
| Peec AI | Ternith | |
|---|---|---|
| What their published research shows | Peec AI has published population-scale research on AI search, including a Listicle Rank Effect study analyzing nearly 200,000 AI responses and more than 5.7 million data points across eight AI engines, from September 2025 through March 2026. The study finds that a brand’s rank in a frequently AI-cited listicle strongly correlates with its position in the AI’s answer, and states its own limit: this is “observational research, not a randomized experiment,” reporting “observed associations” rather than a proven cause. | Ternith does not produce population science. It answers a question Peec AI’s research doesn’t ask at the brand level — what is happening to this brand, sorted into one of three patterns: discoverability, compellingness, or positioning. |
| What the metrics measure for a single brand | Peec AI’s four brand metrics are Visibility (the percentage of AI responses that mention your brand), Share of Voice (your mentions as a percentage of all tracked brands mentioned), Sentiment (a 0–100 score built from the language around your mentions), and Position (your average rank when mentioned). All four are percentages, scores, or rankings, refreshed daily. | Ternith returns a named diagnosis, not a number. It backs that diagnosis with two measurement runs on separate days, and it reports a finding only when both runs agree. |
| What their own data says about listicle evidence | Peec AI’s Listicle Rank Effect study reports that “five strong placements in frequently AI-cited third-party sources will matter more than 50 placements in articles AI engines never retrieve” — and limits the finding to listicles that are “frequently retrieved,” not every listicle on the web. | Ternith’s own carefulness about listicle evidence runs on a different axis: not how often a page gets retrieved, but how specific the retrieved evidence is to one brand. When a compellingness reading in a Ternith diagnosis is dominated by listicle or directory pages that name many brands at once, Ternith says so and treats the reading as needing corroboration from the rest of the evidence, rather than counting a shared mention the same as a page written about the brand specifically. |
| What you learn about your brand | Peec AI returns four brand-metric scores — Visibility, Share of Voice, Sentiment, and Position — shown with change indicators against the previous period of the same length. | Ternith delivers a diagnosis with full evidence: every observation, every page each AI actually read, and what the measurement does and doesn’t settle. On the OpenAI and Anthropic legs, it checks the pages, too — how well each one supports your relevance, not just whether your brand appeared. You can walk a client through it. |
| Source checking | Peec AI tracks two separate things: whether your brand is mentioned (“brand visibility”) and whether your domain or content was used or cited (“source visibility”) — and states plainly that “you can be visible as a source without being visible as a brand.” It reports how often a domain or URL was retrieved and how often it was explicitly cited. | On the OpenAI and Anthropic legs, Ternith checks not just whether a page was retrieved but how well it supports your brand’s relevance — the difference between a page being found and a page making the case. |
| Platforms covered | Peec AI’s Starter, Pro, and Advanced plans let you choose 3 of 6 base platforms — ChatGPT, Google AI Mode, Google AI Overviews, Microsoft Copilot, Perplexity, and Gemini. Enterprise adds five more as API-only models — Claude Sonnet 4, GPT-5 Search, Deepseek, Qwen, and Mistral — for up to 11 tracked models total. Claude coverage is Enterprise-only. | Ternith runs three independent measurement legs — OpenAI, Anthropic, and Google — on every diagnosis. It covers fewer sources than Peec AI’s eleven-model Enterprise ceiling, but each leg — including Anthropic — runs in every diagnosis, not only at the top tier or as a paid add-on. |
| Pricing | Peec AI is a subscription tiered by prompts tracked and models chosen: Starter at $95/month (50 prompts, 3 models, 1 project), Pro at $245/month (150 prompts, 3 models, 2 projects), and Advanced at $495/month (350 prompts, 3 models, 5 projects), all with daily tracking; Enterprise is custom-priced for unlimited projects and up to 11 models. Extra models beyond the chosen 3 cost $30–$140 a month depending on plan, and annual billing saves 15%. | Ternith uses per-diagnosis pricing. You pay for a measurement when you need one; there is no subscription. |
How Peec AI works
Peec AI is a dedicated AI-visibility platform. It tracks four brand-metric scores — Visibility, Share of Voice, Sentiment, and Position — refreshed daily across up to 11 AI models at its top tier, with change indicators against the previous period. It has also published population-scale research on AI search, including a Listicle Rank Effect study analyzing nearly 200,000 AI responses and 5.7 million data points across eight AI engines. That study finds a brand’s rank in a frequently AI-cited listicle strongly correlates with its position in the AI’s answer, and states its own limit honestly: “observational research, not a randomized experiment.” For ongoing monitoring, competitive benchmarking, and understanding how listicle placement relates to visibility at the category level, that is genuinely useful.
How Ternith works
Ternith answers a different question: not how often, but which pattern is showing up. It runs a controlled measurement instrument that classifies the result into one of three patterns — discoverability, compellingness, or positioning — using rules it publishes. Every measurement runs twice on separate days; a finding is reported only when both runs agree. When they don’t, you get the full evidence instead of a guess — and if your result is inconclusive, the next measurement is on us. On the OpenAI and Anthropic legs, the diagnosis also records which pages each AI actually read and how well they support your brand’s relevance, not just whether your brand appeared — and when that evidence leans on listicle or directory pages naming many brands at once, Ternith says so rather than counting it the same as a page written about you specifically. The output is evidence you can hand to a content team or present to a client — not a number, but a place to start.
When to use which
Peec AI
Ongoing AI visibility monitoring
You run an in-house brand or SEO team and want a recurring visibility number across models. Peec AI gives you four trended scores, refreshed daily.
Peec AI
Benchmarking listicle and citation performance
You want to know which third-party listicles and cited domains correlate with your AI visibility, at the category level. Peec AI’s own research and its source-retrieval metrics are aimed at that.
Ternith
A client asks why they’re not showing up in ChatGPT
The client’s question isn’t about a number — it’s about a reason. A Ternith diagnosis points to which pattern is likely behind it and gives you evidence to brief the content team on what to change.
Ternith
Justifying a content strategy change to leadership
You need to explain why the team should shift budget from one content type to another. A Ternith diagnosis gives you a named pattern and an evidence trail you can present — not a graph that needs your interpretation.
Both
Your Visibility Score dropped — now what?
Suppose your Visibility Score in Peec AI fell month-over-month. The trend tells you something changed, but not what. Run a Ternith diagnosis: if the pattern is positioning, the AI is recommending you to one kind of buyer and a competitor to another, in the same category. Under Ternith’s rules, that reads as a messaging pattern rather than a findability one — a different place to look, not a separately proven cause.
Peec AI is best for
In-house SEO and marketing teams who want a recurring, scored view of AI visibility across multiple models, with daily tracking and change indicators they can watch over time. Teams that want listicle and citation-source benchmarking as part of their reporting.
Ternith is best for
SEO managers and consultants who need to tell a client or leadership what is actually wrong and where to start — not just that a number moved. Teams that need a stable, evidence-backed baseline before committing budget to content changes, and that want their Anthropic leg on every diagnosis, not gated behind an Enterprise plan or a paid add-on.
Common questions
Peec AI already tracks four scores across AI platforms. Why would I add Ternith?
Peec AI tells you your Visibility Score moved. It doesn’t tell you why. Suppose your score slipped and the trend line doesn’t say which fix to try. Ternith sorts the result into one of three patterns — the AI can’t find you at all, finds you but picks a competitor instead, or recommends you to one kind of buyer and a competitor to another — each pointing to a different place to look.
Can I use both together?
Yes — they pair well. Peec AI gives you four trending scores across models for ongoing monitoring. When one of them drops, run a Ternith diagnosis to see which pattern is showing up. One watches the trend, the other names the likely pattern.
What does “positioning” mean as a diagnosis?
Positioning means the AI recommends you to one kind of buyer and a competitor to another, in the same category. For example, suppose you win when someone asks about a premium option and lose when they ask about a budget one. Under Ternith’s rules, that reads as a messaging pattern — a different place to look than not being found at all, or found but passed over. Ternith shows you that split as a starting point for which message to test.
Peec AI’s own research finds listicle rank strongly correlates with AI answer position. Does that mean listicle placement is all that matters?
Peec AI’s study is careful about this itself: the finding covers “frequently retrieved” listicles specifically, and the authors call it “observed associations,” not a randomized experiment. Ternith is careful about listicle evidence too, on a different question — not how often a listicle gets retrieved, but whether the retrieved evidence names one brand specifically. When a compellingness reading leans mainly on listicle or directory pages that name many brands at once, Ternith flags that and looks for corroboration before it counts the reading.
What does “compellingness” mean as a diagnosis?
Compellingness means the AI reads your pages but recommends a competitor instead. It finds you, but picks someone else. That is a different pattern from never being found at all — and a different pattern from a positioning problem, where the AI recommends you to one kind of buyer and a competitor to another.
AI answers change all the time. How does each tool handle that?
Peec AI runs daily — one AI answer per prompt per model per day — and shows a change indicator against the previous period. Ternith runs the same instrument twice on separate days and only reports a finding if both runs agree. SparkToro found the exact same recommendation list appears fewer than 1 in 100 times, so how a tool handles instability shapes what it can confidently report.
Peec AI covers up to 11 AI models at Enterprise, including Claude. Does Ternith cover Claude?
Yes. Ternith runs an Anthropic leg — Anthropic is the company behind Claude — on every diagnosis, alongside the OpenAI and Google legs. You don’t move to a higher tier, or pay for an add-on model, to get Anthropic coverage; it’s in every measurement.
How long does a Ternith diagnosis take?
Each measurement runs twice on separate days, so a diagnosis takes a minimum of two days from start to delivery. Peec AI updates its dashboard daily — if you need a number today, that’s what a monitoring tool is for.
What happens if Ternith can’t give me a clear answer?
Ternith runs twice on separate days and reports a finding only when both runs agree. If they don’t, the result is inconclusive — and it ships with the full evidence so you can see exactly what each run found. If your result is inconclusive, the next measurement is on us. A confident-sounding guess isn’t a diagnosis.
Does Ternith cover my category?
Ternith works across categories — it measures how AI systems respond to queries in your space, not from a fixed index. If you’re unsure whether your niche is a fit, the waitlist is the fastest way to ask.
Does Ternith show me how I compare to competitors?
Not as a leaderboard. Peec AI’s Share of Voice metric gives you a competitive percentage if a side-by-side number is what you need. Ternith diagnoses what’s happening to your brand specifically — whether the AI can’t find you, finds you but picks a competitor, or recommends you to one kind of buyer and not another.
Peec AI is a subscription. Is Ternith?
No. Ternith uses per-diagnosis pricing — you pay for a measurement when you need one, with no subscription. Peec AI is priced as a monthly subscription tiered by prompts tracked and models chosen, with paid add-ons for extra models.
Sources
Every claim on this page is drawn from the competitor's own published materials or independently verified research.
- Peec AI: The Listicle Rank Effect — verifies the ~200,000-response / 5.7-million-data-point / eight-engine sample, the listicle-rank-to-answer-position correlation, the “frequently retrieved” scope limit, and the “observational research, not a randomized experiment” caveat. Accessed 1 August 2026.
- Peec AI: Metrics overview — verifies the four brand-metric definitions (Visibility, Share of Voice, Sentiment, Position), the change-indicator mechanism, and the brand-visibility-vs-source-visibility distinction plus the source retrieval/citation metrics. Accessed 1 August 2026.
- Peec AI pricing — verifies the four plan tiers and prices, the prompt/project/model allowances per tier, daily/weekly tracking, the Enterprise 11-model roster including Claude Sonnet 4 as Enterprise-only, the additional-model add-on prices, and the 15% annual discount. Accessed 1 August 2026.
- SparkToro: AI tools are highly inconsistent when recommending brands — verifies the 1-in-100 finding on repeat recommendations; reused from both live entries, not re-fetched this session (§4.2.0). Accessed 22 July 2026.
Find out which pattern is behind it
A Ternith diagnosis points to where to start — not just whether a number went up or down.