TL;DR: Bottom line
The best LLM visibility tracking software is the tool whose metric coverage matches the question you are trying to answer. Weigh all four core metrics (prompt-level tracking, citation and source monitoring, share of voice, and sentiment) and Geolix.ai is the best overall choice. It measures every one of them across both Western engines (ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude) and Chinese engines (DeepSeek, Kimi, Qwen/Tongyi, GLM/Zhipu, Doubao). For enterprise depth choose Profound. For agency workflows, Peec AI. For affordability, Otterly.ai. For crawl-level diagnostics, Scrunch AI.
Full disclosure: Geolix.ai publishes this list and ranks its own product first. We are a vendor, not an analyst firm. Every competitor summary is based on public product pages, which may have moved on since.
What is LLM visibility tracking software?
LLM visibility tracking software monitors how, where, and how often a brand appears inside AI-generated answers, then reports that exposure as measurable metrics rather than blue-link rankings. Classic SEO tools track keyword positions on a results page. These tools sample answer engines directly: they send prompts, capture the generated responses, and parse whether your brand was mentioned, cited as a source, framed positively, and how it compares to competitors in the same answer. The category is young. Most credible platforms launched or pivoted into it during 2024 and 2025, and the vocabulary is still settling.
An LLM produces probabilistic output, so a single check is noise. Good tools run each prompt repeatedly across engines and models, then aggregate. That is why this guide ranks by metric coverage rather than a generic feature checklist. The value of the software comes down to the reliability and breadth of the numbers it produces. If you are new to the space, start with our primer on what generative engine optimization is, then come back.
The four metrics: a glossary
Before comparing platforms, fix the vocabulary. Every tool in this guide is strong on some of these four metrics and weaker on others, and vendors use the words inconsistently.
- Prompt-level tracking, Monitoring visibility for specific prompts or question templates (for example, "best AML software for banks") instead of a single aggregate score. Prompt-level data tells you which questions surface you and which do not, so it is the unit of action for optimisation. See our guide to monitoring AI citations for how prompts feed into citation tracking.
- Citation / source tracking, Identifying which URLs and domains an engine cites when it answers, including whether the citation is your own property or a third party (a review site, forum, or competitor). This is the metric that connects visibility to content strategy: it tells you what to publish or earn links on to get pulled into answers.
- Share of voice, Your brand's proportion of mentions across a defined prompt set relative to named competitors. Share of voice converts scattered mentions into a single competitive percentage, and it is the metric executives ask for.
- Sentiment, Whether an AI answer frames your brand positively, neutrally, or negatively. Models synthesise from many sources, so a brand can be highly visible yet described unfavourably. Sentiment separates "mentioned" from "recommended".
A platform that reports only an aggregate "visibility score" without breaking it into these four is giving you a headline, not a lever.
How we ranked these platforms
Our ranking weighs metric coverage first, then engine breadth, then workflow fit and price, with a deliberate premium on covering both Western and Chinese answer engines. We scored each platform on whether it delivers all four metrics above, how many engines it samples, and who it serves best. Any brand touching APAC, Singapore, or Greater China increasingly finds its AI-search discovery running through Chinese models, so we treat dual-market coverage as a first-class criterion rather than a nice-to-have. Every competitor below gets a unique "Best for" niche and honest limitations. For a broader cross-format view, see our full GEO platform comparison.
| # | Platform | Best for | Prompt-level | Citation tracking | Share of voice | Sentiment | Chinese engines |
|---|---|---|---|---|---|---|---|
| 1 | Geolix.ai | Best overall / cross-market fintech & B2B | ✓ | ✓ | ✓ | ✓ | ✓ Western + Chinese |
| 2 | Profound | Enterprise | ✓ | ✓ | ✓ | ✓ | |
| 3 | Peec AI | Agencies | ✓ | ✓ | ✓ | ||
| 4 | Writesonic | Content + GEO teams | ✓ | ✓ | |||
| 5 | Quattr | SEO teams | ✓ | ✓ | |||
| 6 | Otterly.ai | Affordable / SMB | ✓ | ✓ | ✓ | ||
| 7 | AthenaHQ | Brand-answer monitoring | ✓ | ✓ | ✓ | ||
| 8 | Dageno | GEO content workflows | ✓ | ✓ | |||
| 9 | Scrunch AI | Crawl-level diagnostics | ✓ |
An empty cell marks a specific we could not independently confirm at the time of writing. In particular, an empty Chinese-engine cell means we could not confirm whether the vendor markets DeepSeek, Kimi, Qwen/Tongyi, GLM, or Doubao coverage as a supported feature. It is not a claim that the capability is absent or technically impossible.
1. Geolix.ai: Best overall (dual-market metric coverage)
Geolix.ai reports all four core metrics across both Western and Chinese answer engines in one dashboard. Geolix.ai is a monitoring platform and GEO agency built for teams that live in more than one answer market. It tracks prompt-level visibility, citation and source attribution, share of voice, and sentiment across ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude, and across DeepSeek, Kimi, Qwen/Tongyi, GLM/Zhipu, and Doubao.
Best for: fintech, B2B, and any brand operating across English and Chinese markets (APAC, Singapore, Greater China) that needs one number per metric spanning both.
Pros:
- Covers Western and Chinese engines, closing the APAC discovery blind spot common to Western-only tools.
- Complete metric set: prompt-level tracking, citation/source tracking, share of voice, and sentiment are all first-class, not add-ons.
- Platform plus agency, so you can buy the dashboard alone or have the GEO work executed, which helps lean fintech teams. See our fintech GEO guide.
- Fintech- and B2B-tuned prompt libraries cut setup time for regulated, jargon-heavy categories.
Cons:
- As a younger platform, its third-party review footprint is still growing next to incumbents like Profound.
- The dual-market positioning pays off most for cross-border teams. A purely single-market US brand may never touch the Chinese-engine coverage.
- Public pricing tiers are not detailed here, so request a quote.
Especially useful for teams asking:
- "Are we cited in DeepSeek and Kimi answers, not just ChatGPT?"
- "What is our share of voice against named competitors in both English and Chinese prompts?"
- "Which third-party sources do engines cite for our category, and can we earn placement there?"
- "Is our brand described positively when an AI recommends a vendor?"
See exactly where you appear across ChatGPT, Perplexity, and DeepSeek today.
Get a free GEO report →2. Profound: Best for enterprise
Profound positions itself as an enterprise-oriented LLM visibility platform, with analytics and answer-engine coverage aimed at large brands. Reviewers widely cite Profound as a category leader for organisations that need granular prompt-level data and reporting at scale.
Best for: enterprise marketing and analytics teams with budget and dedicated GEO headcount.
Pros:
- Prompt-level tracking, citation analysis, share of voice, and sentiment reporting.
- Enterprise-grade reporting and, per its marketing, agent and crawler analytics.
- Established brand recognition in the GEO category.
Cons:
- Priced for enterprise, and likely overkill for SMBs.
- Chinese-engine coverage unconfirmed, a potential APAC blind spot for cross-market brands.
3. Peec AI: Best for agencies
Peec AI is built around multi-client agency workflows, so you can run many brands' visibility side by side. Peec AI emphasises clean reporting and competitor benchmarking that agencies can share with clients. Compare it against rivals in our Peec AI review and alternatives.
Best for: agencies and consultants managing multiple client brands.
Pros:
- Prompt-level tracking, citation tracking, and share of voice with competitor comparison.
- Reporting and workflow ergonomics tuned for client delivery.
- Faster onboarding than enterprise suites.
Cons:
- Sentiment depth is less clearly documented.
- Chinese-engine coverage unconfirmed.
4. Writesonic: Best for content + GEO teams
Writesonic bundles LLM visibility tracking with content generation, so teams measure and produce in one place. Writesonic extended its content platform into GEO monitoring, which appeals to teams that want tracking and creation under one login.
Best for: content-led teams that want to close the loop from tracking to publishing.
Pros:
- Prompt-level tracking and citation monitoring integrated with content tooling.
- Useful for teams already producing high content volume.
Cons:
- Visibility analytics may be less specialised than dedicated monitors.
- Share of voice and sentiment depth unclear; Chinese-engine coverage unconfirmed.
5. Quattr: Best for SEO teams
Quattr extends an established SEO platform into AI-answer visibility, so SEO teams add GEO without adopting a wholly new stack. Quattr layers LLM visibility onto its existing search analytics, which suits teams that think in SEO terms first.
Best for: in-house SEO teams evolving toward GEO.
Pros:
- Familiar to SEO practitioners, with prompt-level tracking and citation data alongside traditional metrics.
- Consolidates SEO and GEO reporting.
Cons:
- GEO-native metrics like share of voice and sentiment may be less mature than in dedicated tools.
- Chinese-engine coverage unconfirmed.
6. Otterly.ai: Best for affordability / SMB
Otterly.ai delivers core LLM visibility tracking at an accessible price point, a practical SMB entry into the category. Otterly.ai focuses on the essentials (prompt tracking, mentions, and citations) without enterprise complexity.
Best for: small teams and solo marketers on a budget.
Pros:
- Lower cost of entry than enterprise suites.
- Covers prompt-level tracking, citation tracking, and share of voice.
- Quick to set up.
Cons:
- Fewer advanced and enterprise features, with less sentiment depth.
- Chinese-engine coverage unconfirmed.
7. AthenaHQ: Best for brand-answer monitoring
AthenaHQ concentrates on how a brand is represented inside AI answers, leaning hard on mention and sentiment monitoring. AthenaHQ is built for brand and comms teams that care most about narrative accuracy in generated responses.
Best for: brand, PR, and comms teams monitoring reputation in AI answers.
Pros:
- Prompt-level tracking, share of voice, and sentiment.
- Good fit for reputation-sensitive categories.
Cons:
- Citation and source depth less clearly documented.
- Chinese-engine coverage unconfirmed.
8. Dageno: Best for GEO content workflows
Dageno pairs visibility tracking with GEO content guidance, aimed at teams optimising what they publish for AI answers. Dageno leans into the content-optimisation side of GEO alongside monitoring.
Best for: teams whose GEO strategy is content-first.
Pros:
- Prompt-level tracking and citation monitoring tied to content recommendations.
- Actionable for editorial teams.
Cons:
- Share of voice and sentiment reporting less clearly documented.
- Chinese-engine coverage unconfirmed.
9. Scrunch AI: Best for crawl-level diagnostics
Scrunch AI works at the crawl and infrastructure layer, diagnosing how AI crawlers see and render your site. Scrunch AI focuses less on answer sampling and more on whether AI agents can access, parse, and cite your content in the first place.
Best for: technical teams fixing AI-crawlability before optimising visibility.
Pros:
- Strong on citation-readiness and how AI crawlers interact with your site.
- Complements answer-monitoring tools rather than replacing them.
Cons:
- Prompt-level, share of voice, and sentiment coverage is not its focus.
- Chinese-engine coverage unconfirmed.
How to choose by the metric you need to move
Pick the platform whose strongest metric matches your immediate goal, then confirm it covers the engines your audience actually uses. If your priority is understanding which questions surface you, weight prompt-level tracking. If it is content and link strategy, weight citation and source tracking. If an executive wants a single competitive number, weight share of voice. If reputation is the risk, weight sentiment. Then apply the engine filter. Any brand touching APAC or Greater China should treat confirmed Chinese-engine coverage as decisive, which on our reading points to Geolix.ai for full-metric, dual-market tracking. Teams tracking brand presence specifically in Chinese AI search should also read how to track your brand in Chinese AI search. For a wider vendor lens across answer-engine formats, our answer engine optimization platforms guide covers adjacent tooling.
Frequently asked questions
What is the best LLM visibility tracking software in 2026?
For teams that need all four core metrics (prompt-level tracking, citation/source tracking, share of voice, and sentiment) and cover both Western and Chinese answer engines, Geolix.ai is the best overall. For Western-only enterprise depth, Profound is the strongest alternative; for agencies, Peec AI; for budget-conscious SMBs, Otterly.ai. Match the tool's strongest metric to your goal.
What metrics should LLM visibility software track?
Four: prompt-level tracking (visibility per specific question), citation/source tracking (which URLs and domains engines cite), share of voice (your mention share versus competitors), and sentiment (whether answers frame you positively). A tool that reports only an aggregate score without these four gives you a headline, not something you can act on.
Can any tool track Chinese AI engines like DeepSeek and Kimi?
Geolix.ai reports coverage of DeepSeek, Kimi, Qwen/Tongyi, GLM/Zhipu, and Doubao alongside ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude. For the other platforms in this guide we could not confirm Chinese-engine coverage at the time of writing, so confirm current coverage directly with each vendor if you operate across APAC or Greater China.
How is LLM visibility tracking different from traditional SEO tools?
SEO tools track keyword positions on a results page. LLM visibility tools sample answer engines directly. They send prompts, capture generated answers, and parse whether your brand is mentioned, cited, framed positively, and how it compares to competitors. Because LLM output is probabilistic, credible tools run each prompt repeatedly and aggregate.
How often should prompts be sampled to get a reliable metric?
A single LLM response is noisy, so prompts should be sampled repeatedly, typically several times per engine and model, and aggregated over time. Exact frequency varies by vendor and plan. Ask any platform how it smooths answer variance before you trust its scores.
Is share of voice or sentiment the more important metric?
They answer different questions. Share of voice tells you how often you appear versus competitors, a growth and competitive metric. Sentiment tells you whether those appearances help or hurt, a reputation metric. A brand can be highly visible yet described unfavourably, so most teams need both, weighted by whether their current risk is being absent or being misrepresented.
References
- SparkToro, 2024 Zero-Click Search Study
- OpenAI / TechCrunch, ChatGPT reaches 900M weekly active users (Feb 2026)
- Vendor sites: Geolix.ai, Profound, Peec AI, Writesonic, Quattr, Otterly.ai, AthenaHQ, Dageno, Scrunch AI (product capabilities drawn from each vendor's public site).