TL;DR: If your goal is to measure AI visibility reliably — not generate content — the monitoring-first shortlist is Otterly.AI ($29/mo entry), Peec AI (analytics depth, agency seats), Scrunch AI (enterprise, hallucination detection), Brandlight (enterprise governance), Ahrefs Brand Radar (benchmark any brand against a 405M-prompt corpus), and Semrush's toolkit (inside an existing stack). Stride and Profound also monitor well but bundle bigger platforms around it. This guide covers what monitoring should measure, the share-of-voice formula, and how the eight compare — criteria stated first.
Stride publishes this guide and is included below. Evaluation criteria are stated explicitly so you can weigh our inclusion accordingly.
What is AI search monitoring?
AI search monitoring (often "AI visibility monitoring") is the ongoing measurement of how AI engines — ChatGPT, Perplexity, Gemini, Claude, Copilot, Google's AI Overviews — answer the questions your buyers ask, and where your brand sits in those answers. A monitoring tool repeatedly runs a tracked prompt set against each engine and records four things: mentions (is your brand named), citations (are your pages used as sources), sentiment (how the answer characterizes you), and competitive context (who else appears).
This is a different job from GEO optimization — the content and technical work of improving those answers, which our main tools guide covers across both halves. Monitoring's job is to be trustworthy: consistent methodology, honest handling of noise, and numbers you'd stand behind in a board deck.
The reason monitoring is a continuous discipline rather than a quarterly check is volatility:
Only 49% of brands that appeared in AI answers were still visible three weeks later, across a 481-site study of ChatGPT, Perplexity, and Google AI Overviews (Advanced Web Ranking, Nov 2025).
Answers churn constantly. A tool that samples once and declares victory — or crisis — is measuring noise.
How we evaluated these tools
- Monitoring depth — mentions vs citations separated; raw answers inspectable; sentiment tracked.
- Cadence and alerting — how often prompts run, and whether meaningful changes reach you without logging in.
- Share-of-voice measurement — competitive normalization, not just your own counts.
- Data trustworthiness — smoothing/noise handling, methodology transparency, stable prompt sets.
- Price for a monitoring seat — what you pay if measurement is all you want.
Comparison table
| Tool | Best fit | Engines covered | Starting price | Standout capability |
|---|---|---|---|---|
| Otterly.AI | SMB monitoring on a budget | 6 (some via add-ons) | $29/mo | Daily tracking with the lowest transparent entry price |
| Peec AI | Agencies, mid-market analytics | 6 included; extra LLMs add-on | ~€89/mo | Mention-vs-citation and source-gap analytics; unlimited seats |
| Scrunch AI | Enterprise B2B monitoring | 4 on Core; more on Enterprise (reported) | ~$250–300/mo (reported) | Hallucination detection; crawler analytics |
| Brandlight | Enterprise brand governance | Roster claimed broad; count unverified | Not published | Real-time drift alerts, SOC 2/SSO, BI connectors |
| Ahrefs Brand Radar | SEO teams benchmarking a market | 7 claimed (roster in flux) | From $199/mo + add-ons | 405M+ prompt corpus; measure competitors you don't own |
| Semrush AI Toolkit | Existing Semrush users | 5 | $99/mo add-on | Monitoring inside the SEO stack you already run |
| Stride | Shopify/DTC brands | 5 engines + Google AI Overviews (tier-dependent) | $99/mo | Product-aware monitoring tied to a fix pipeline |
| Profound | Enterprise, prompt-demand data | 6 core; ~10 Enterprise | Not published | Licensed real-user prompt volumes behind the tracking |
The monitoring-first tools
1. Otterly.AI
The lowest-friction way to start measuring: $29/mo, public pricing, 7-day no-card trial, daily tracking of mentions, link citations, position, and sentiment across six engines. Prompt caps are tight at entry (~15) and there's no deep analytics layer, but as a pure "are we visible, trending which way" instrument it does the job at a tenth of enterprise cost.
2. Peec AI
The strongest pure analytics among the affordable tools. Peec cleanly separates mentions from citations, analyzes which sources engines lean on in your category and where you're absent (source-gap analysis), and benchmarks share of voice against competitors — with unlimited seats on every plan, which makes it the default agency monitoring choice. From ~€89/mo with a 7-day trial; extra LLMs beyond the included six may cost per-model.
3. Scrunch AI
Monitoring-first for the enterprise: alongside standard mention/citation tracking, its hallucination detection (Enterprise tier) flags when engines state false things about your brand — the monitoring category's most direct answer to AI answers being wrong, not just missing you. Crawler analytics show how AI bots traverse your site. Reported Core pricing ~$250–300/mo with four engines; the fuller roster and hallucination work sit higher up.
4. Brandlight
Built for organizations where AI misrepresentation is a governance problem: real-time dashboards, drift alerts, sentiment and share of voice, enterprise security checklist (SOC 2, SSO, RBAC), and connectors into Looker Studio, GA4, and CRMs. Neither pricing nor an exact engine roster is published, so evaluation requires a sales process — the trade-off enterprise buyers expect and smaller teams shouldn't bother with.
5. Ahrefs Brand Radar
A different monitoring philosophy: instead of tracking only your configured prompts, Brand Radar runs a 405M+ search-backed prompt corpus, so you can measure AI share of voice for any brand in your market — including competitors who don't know they're being measured — plus which pages and domains engines cite. From $199/mo standalone with per-platform add-ons; custom prompt tracking requires an Ahrefs base plan, and total cost stacks fast. For market-level benchmarking, nothing else on this list matches the corpus.
6. Semrush AI Visibility Toolkit
Monitoring where your SEO already lives: prompt tracking, brand performance/sentiment, competitor comparison, and an AI-crawler site audit for $99/mo on top of a Semrush subscription, covering five engines. The 25-prompt default allowance is the main constraint. Right answer if consolidation beats best-of-breed for your team.
Monitoring inside bigger platforms
7. Stride
Stride (this publication) monitors mention rate, citation rate, sentiment, and share of voice across ChatGPT, Perplexity, Gemini, Claude (beta), and Grok plus Google AI Overviews depending on tier, from $99/mo — with scan cadence from weekly to daily by plan, smoothing that refuses to call a one-scan dip a trend, and raw answers kept inspectable per prompt and engine. The monitoring is product-aware (built for Shopify/DTC catalogs) and feeds a prioritized fix queue, which is the point of the platform — so if you want measurement strictly separated from any optimization layer, the tools above are purer fits. Entry-tier tracking is ChatGPT-only.
8. Profound
Profound's monitoring sits on the category's most distinctive data asset: licensed real-user prompt volumes, so tracking is weighted by what people actually ask rather than a guessed prompt list, across six-to-ten engines with sentiment, citations, and competitive benchmarks. It's sold as an enterprise platform (pricing not published) with automation and shopping modules around the monitoring core — more than a team that only wants measurement needs to buy.
How share of voice actually works
Share of voice (SoV) is the metric that turns monitoring from vanity counting into competitive position. The base formula:
AI share of voice = answers featuring your brand ÷ total measured answers
measured per engine over a defined prompt set and window. The competitor-normalized variant, which many tools display:
SoV (normalized) = your appearances ÷ Σ appearances of all tracked brands
so the competitive set sums to 100%. A worked example: across 40 tracked prompts on one engine, your brand appears in 12 answers, Competitor A in 22, Competitor B in 8. Simple SoV: 12/40 = 30%. Normalized: 12/(12+22+8) = 29%, against 52% for Competitor A — you're second of three, and the gap, not the 30%, is the story.
Three implementation choices change the number, so check them in any tool you evaluate: what counts as an appearance (an explicit name mention only, or also a citation of your domain — counting either is more forgiving and catches answers that link you without naming you); the sample floor (SoV over six answers is noise; refusing to render below a minimum sample is a feature, not a gap); and prompt-set stability (if the prompt set changes weekly, SoV isn't comparable across time).
Sentiment and "answer quality" monitoring
Presence is binary; how an answer frames you is where reputations move. Most tools on this list classify per-answer sentiment (positive/neutral/negative) toward your brand — useful as a trend, noisy as a data point. Two practices keep it honest: read the underlying answers before reacting to a classification, and only treat sentiment shifts sustained across scans and engines as real.
The adjacent frontier is factual accuracy — engines don't just omit brands, they sometimes misdescribe them. Scrunch's hallucination detection and Brandlight's drift alerting target exactly this, and it's worth asking any vendor how they'd surface a wrong answer, not just a missing one. One more reason to watch answers rather than assume good faith: Peec's 232,000-citation study found roughly 11% of AI citations in software niches come from vendors' own self-promotional listicles — engines mostly aren't filtering them yet — so the "neutral" answer describing your category may be built on a competitor's marketing.
The ecommerce angle
Monitoring a store differs from monitoring a SaaS brand in two ways. First, the prompt set: buyer questions cluster around products ("best X for Y", "A vs B", "is A worth it"), so a brand-only prompt set misses where DTC revenue actually moves — our citation tracking guide shows how product queries get sourced. Second, seasonality: Adobe measured holiday AI traffic to retail up 693% year over year in 2025, which means a store's monitoring cadence should tighten before peak season, precisely when volatility and competitor content pushes spike. Choose a tool whose cadence you can turn up when it matters.
Frequently asked questions
What is AI search monitoring?
AI search monitoring is the ongoing measurement of how AI engines answer questions relevant to your brand — whether you're mentioned, whether your pages are cited as sources, what sentiment the answers carry, and who else appears. It differs from optimization tooling in that its job is trustworthy measurement over time, not content production.
How is AI share of voice calculated?
The base formula is your brand's appearances divided by total measured answers in a prompt set, per engine. A competitor-normalized variant divides your appearances by the sum of all tracked brands' appearances, so shares total 100% across the competitive set. Check whether a tool counts only explicit name mentions or also counts citations of your pages — the choice changes the number.
How often should AI visibility be measured?
More often than feels intuitive. Advanced Web Ranking's 2025 volatility study found only 49% of brands remained visible in AI answers across a three-week window. Weekly tracking is a reasonable floor for a small brand; daily matters once you're actively working on visibility or in a volatile category like finance.
Why did my brand disappear from AI answers overnight?
Usually volatility, not catastrophe. AI answers vary run to run, engines update retrieval frequently, and a single measurement is noisy. Good monitoring tools smooth across multiple runs before declaring a trend. If a disappearance persists across scans and engines, then investigate — content changes, a competitor's new citation source, or crawler-access problems.
Is sentiment tracking in AI answers reliable?
It's directionally useful, not laboratory-grade. Tools classify each answer's tone toward your brand (positive, neutral, negative), typically with an LLM pass. Treat single-answer sentiment as noise and sentiment trends across many answers as signal — and read the underlying answers before acting on any negative classification.
Stride monitors AI visibility for Shopify and DTC brands. To see your current baseline before committing to any tool here, the free audit measures your visibility across a starter prompt set in about two minutes.