Peec AI vs Otterly vs Profound: which should you buy?

First, a disclosure: I’m the founder of CiteLyzer, another tool in this category. That makes this a practitioner’s buying guide, not a neutral review - so instead of scoring competitors feature by feature (any such table would be stale in a quarter), it gives you the questions that decide the purchase, whatever you end up choosing.

What do Peec, Otterly and Profound have in common?

All three sit in the same category: AI visibility platforms (also called GEO or AEO tools). They periodically run prompts against AI engines, detect whether your brand is mentioned in the answer text and whether your domain is cited as a source, and turn that into metrics over time - mention rate, citations, share of voice.

Where they differ is mostly positioning. Broadly: entry-level tools optimise for a fast, affordable start; mid-market tools add team features, more engines and deeper competitive views; enterprise platforms add scale, integrations, and procurement-friendly packaging. Each of the three names leans toward a different point on that spectrum - and pricing pages change often enough that you should check them the week you buy, not trust a blog post.

How to choose: a three-step decision framework

Instead of starting from feature lists, start from your own constraints. Three steps settle most purchases:

• Step 1 - budget and scale. Solo founder or single brand: you want a low-commitment start (monthly billing, small plan, or a one-off report). Agency with client reporting: you need multi-brand workspaces and white-label-ish exports. Enterprise: procurement, SSO and SLAs start to matter more than the metric itself.
• Step 2 - goal: monitoring or benchmarking. Monitoring answers “is my visibility moving after what I shipped?” - it needs consistent, repeated measurement of YOUR prompts. Benchmarking answers “where do I stand in my category?” - it needs a competitor set and share-of-voice views. Most tools do both, but each leans one way; buy for the question you’ll actually ask weekly.
• Step 3 - hard requirements. Count them before the demo: which AI engines are covered (and in which country editions), how often prompts re-run, whether mentions are detected in your language (including inflected brand forms in Slavic languages), export/API access, and how many team seats you need.

What a 1:1 comparison can’t settle

Even a careful side-by-side table hides real differences. Keep these seven caveats next to any comparison you read:

• Engine coverage differs by plan, not just by product - two tools “both covering ChatGPT” may cover it at very different depths.
• Refresh frequency is usually plan-gated too; a cheap plan measuring weekly answers a different question than a daily one.
• Language handling varies wildly: tools built for English markets often miss non-English prompts and inflected brand names entirely.
• Answer volatility means two tools can measure the same brand honestly and still show different numbers - AI engines don’t answer twice the same way.
• Prompt-set quality shapes everything: the same tool with badly chosen prompts measures a market you’re not actually selling in.
• Team features (seats, workspaces, client reports) are where mid-market and enterprise pricing really diverges - not in the core metric.
• Data access (exports, API) decides whether the tool fits your reporting stack or becomes another silo.

How this kind of tool works - and how to read the numbers

Whatever you buy, the mechanics are the same: the tool runs your prompt set against each engine on a schedule, normalises the answers, detects mentions and citations, and aggregates them into trends. Three reading rules keep the numbers honest:

• Trust the trend, not the single run. One measurement is a snapshot of a moving target; a series tells you whether visibility is actually rising. For monitoring your own progress, week-over-week direction matters more than any absolute number.
• Read mentions and citations separately. A mention (your name in the answer) builds awareness; a citation (your domain as a source) builds traffic and trust. A tool that blends them can’t tell you which problem you have.
• Judge share of voice inside your prompt set. SoV only means something against the competitors and prompts you chose - it’s a benchmark of your category as you defined it, not of the whole internet.

Where CiteLyzer fits on this map

CiteLyzer is the lean end of the spectrum, built for one job: measuring whether AI engines mention and cite a brand, across five engines (ChatGPT, Gemini, Perplexity, AI Overviews and AI Mode), with mentions and citations tracked separately, share of voice against your competitor set, and recommendations written for a business owner rather than an SEO specialist.

Its differentiator is market depth over breadth: prompts run in the market’s own language with inflected brand-name detection (built Polish-first, where brand names decline through seven grammatical cases), and country editions of engines are measured rather than just the US ones. What you won’t find is enterprise packaging - no SSO, no dozens of integrations, no consultant team. If you’re a global enterprise, one of the three names above may fit better; if you want an affordable, language-aware tracker you can start small with, that’s the niche CiteLyzer was built for.

Bottom line

Peec, Otterly and Profound are all legitimate answers to different questions. Decide your budget tier, decide whether you’re monitoring or benchmarking, count your hard requirements - engines, languages, refresh rate, seats - and the field usually narrows to one or two candidates on its own.

And whichever tool you pick: check that it measures the market you actually sell in, in the language your customers ask in. That single criterion eliminates more wrong purchases than any feature table.