Best LLM Monitoring Tools in 2026 (Brand Visibility, Not Observability)

Search for LLM monitoring tools and you get two product categories in one page. One set watches what large language models say about your brand: which prompts mention you, which pages they cite, which competitor appears instead. The other watches your own LLM application in production: token spend, latency, failed tool calls, eval scores. Nothing says which one a vendor sells, so a marketing lead and a platform engineer both land here and both leave annoyed.

This post is about the first kind. If you came for the second, skip to the short section near the end.

What LLM brand monitoring actually captures

You give the tool prompts, it sends them on a schedule to ChatGPT, Perplexity, Gemini, Google AI Mode, AI Overviews and whatever else it supports, and it parses the answers it stores.

• Mentions. Whether the answer named your brand and where, since fourth in a list is not the recommendation: see tracking brand mentions.
• Citations and sources. The URLs behind the answer, and the field showing which sites the models read: see tracking which sources AI cites.
• Share of voice and competitors. Your mentions as a share of voice across all tracked brands on one prompt set, with the same metrics for rivals you nominate. Comparable inside a tool, never across two.
• Sentiment. Catches the model that recommends you while calling you expensive.
• The answer text. Underrated: most of the insight comes from reading twenty responses.

What it cannot tell you

There is no rank. An AI answer is a paragraph, not a list of ten links. A “position” is the order brands appear in prose, a proxy and nothing more: see AI rank tracking myths.

There is no impression count. No assistant publishes how many people asked a question, so the estimated impressions some tools show are modelled from search volume. Google is the partial exception: Search Console’s Generative AI performance report counts how often your links appeared in AI Overviews and AI Mode, with no clicks, CTR or position.

Answers vary between runs. Ask the same model the same question twice and the brands and sources can change, which is why volume matters more than dashboard design.

People ask me which LLM monitoring tool is the best one. Honestly? The one whose numbers you can explain to your boss. If a dashboard gives you a score and you can’t open the answers behind it, you’re buying a number, not an insight.

How to choose an LLM monitoring tool

Eight things decide the fit; our piece on choosing an AI visibility tool goes deeper.

1. Model coverage at the price you will pay. Nine engines in the marketing often means four on the entry plan.
2. Cadence. Daily costs more and earns it during a launch; weekly gives cleaner trend lines.
3. Citations as a first-class data type you can group, filter and export.
4. Locales and languages. Several self-serve products cap you at one of each.
5. Competitor benchmarking on the same prompts, and whether changing the list resets history.
6. Exports and API. Ask whether the API is included or an add-on.
7. Seat model. One seat on an entry plan breaks any team that shares reporting.
8. Price per tracked answer, not per prompt. This one reorders the market.

The arithmetic: a weekly prompt yields about 4.33 answers per model per month, a daily prompt about 30. So 100 weekly prompts on three engines is roughly 1,300 answers a month, while 50 daily prompts on one engine is about 1,500. Divide price by answers before comparing quotes. The GEO metrics guide covers what to do with them.

The eleven tools at a glance

Figures are as published when we checked in October 2026, in the currency each vendor’s page showed us, and several vendors reprice often.

1. LLM Pulse

This is our tool, so read the watch-outs with that in mind. It tracks ChatGPT, Perplexity, Google Gemini, Google AI Mode and Google AI Overviews on every plan. DeepSeek, Grok, Claude, Microsoft Copilot, Meta AI, Naver AI Briefing, Naver AI Tab, Baidu AI, Qwen, Doubao and Alexa for Shopping (formerly Amazon Rufus) are paid add-on models. MiniMax, Mistral, Walmart Sparky and Brave AI are available through Talk to sales, and the team sets them up for approved paid accounts.

It treats citations as a real object: which domains the models cite in your category, which of your pages appear, and the page content behind each cited URL. Around the core metrics sit prompt research with query fan-out, AI Model Insights, GEO Writer, GEO Testing, reputation monitoring, ChatGPT Ads tracking and Reddit Intelligence.

The data gets out cleanly too: REST API, CLI, MCP server, signed webhooks with Zapier, Make and n8n connectors, a Data Studio (formerly Looker Studio) connector, a Power BI connector in private beta, CSV output that Tableau can read through its own REST connector, CSV exports and PDF reports. Search Console connects as a property so real queries feed prompt generation, AI Traffic analytics reports human visits from AI assistants, and Agent Analytics reads your logs for bot hits. Team members are unlimited, with white label and iframe embed for agencies.

When we built the citation views, I expected teams to care most about their own pages getting cited. The part they end up using is the list of other domains: the review sites, forums and comparison pages the models keep reading in their category. That list is usually a better outreach plan than anything an SEO audit hands you.

Two watch-outs. Weekly is the default cadence (daily is available on every plan at a higher price, monthly on request), and the allowance counts per week, per model, so a plan buys fewer individual answers than a tool running the same prompt count daily. Line the plans up on answers when you compare. Second, the surface area is large, and if you want one score on a dashboard each month, a smaller tool will feel lighter.

Pricing is Starter EUR 49/mo for 50 prompts, Growth EUR 99/mo for 150, Scale EUR 299/mo for 450, Scale+ EUR 599/mo for 1,200, Scale++ EUR 1,199/mo for 2,400, Enterprise custom, annual at ten times the monthly price. Per prompt that is EUR 0.98 on Starter down to EUR 0.50 on Scale+ and Scale++, and 50 prompts across five models is over 1,000 AI answers a month. Full pricing is on the site, along with how the API works. The trial requires a card.

2. Ahrefs Brand Radar

A small allowance of tracked prompts comes with paid Ahrefs plans, so existing Ahrefs customers already have some of this data. It covers AI Overviews, AI Mode, ChatGPT, Perplexity, Gemini, Copilot and Claude, reporting mentions, citations, share of voice and estimated impressions, with custom prompts checked daily.

Then you read the allowance, which Ahrefs meters in checks: one prompt, on one platform, once. Lite at EUR 119/mo includes 150 checks a month, Standard at EUR 229 includes 300 and Advanced at EUR 419 includes 600, which is 5, 10 or 20 prompts checked daily on a single platform. Spread them across several platforms and the prompt count shrinks, and Claude uses eight checks per update. Five prompts is a spot check. Scaling means the AI Visibility Index tier at EUR 179/mo or custom prompt packages from about EUR 47/mo.

3. Profound

Profound sells to enterprises, and a smooth security review is the honest reason to shortlist it: SOC 2 compliance and SSO/SAML come on its Enterprise plan. It no longer publishes a self-serve price. The pricing page offers a free seven-day trial with 50 prompts run daily across ChatGPT, Gemini and Google AI Overviews; everything else is Enterprise, quoted in a sales conversation, with up to nine answer engines and API access.

The trial is limited to one language and one region, with no history, exports or API, so it shows you the interface more than it tests the data. Budget for a sales cycle before you see a price.

4. Otterly.AI

Otterly has the lowest paid entry here: Lite at USD 29/mo for 15 prompts, Standard USD 189/mo for 100, Premium USD 489/mo for 400, Enterprise custom from 1,000. Cadence is daily, so 15 prompts produce roughly 450 answers per engine per month.

Base plans cover ChatGPT, AI Overviews, Perplexity and Copilot, while Google AI Mode, Gemini and Claude are paid add-ons, so two fast-growing Google surfaces sit outside the base price. The top self-serve plan stops at 400 prompts, so a large brand outgrows the ladder.

5. SE Ranking and SE Visible

SE Ranking sells AI search tracking two ways: inside its SEO platform, or as SE Visible standalone. SE Visible is EUR 80/mo for 75 prompts (Basic), EUR 169 for 200 (Core) and EUR 355 for 1,000 (Agency), billed monthly across five engines, with a 10-day trial. The Agency tier is one of the lowest per-prompt prices of any self-serve tool here.

Inside the main platform, Core at EUR 109/mo and Growth at EUR 235/mo each include 25 daily prompts across five LLMs, with more through an AI visibility add-on. Be clear internally about which product a quote refers to, and check the cadence: SE Visible runs daily, and the Agency tier can also run weekly.

6. Scrunch AI

Scrunch bundles site auditing with answer tracking, which suits teams whose next question is what to change on the site. Core is USD 250/mo for 125 unique prompts, 5,000 responses a month, five site audits and one brand workspace, with a seven-day trial.

Core covers ChatGPT, Perplexity, AI Overviews and Copilot; the nine-engine coverage in the marketing is an Enterprise capability, so confirm where Gemini and AI Mode land before signing. One brand workspace also pushes a house of brands towards Enterprise quickly.

7. Searchable

Regions and seats are unlimited on every tier, which is the reason to look at it. Pro is USD 125/mo for 100 prompts per model and one project, Scale USD 400/mo for 500 and ten projects, and Enterprise USD 999/mo for 1,250 with unlimited projects, with a 14-day trial. Agencies get separate plans.

Base plans track three engines (ChatGPT, Google AI Overviews and Perplexity) and the rest are paid add-ons. A three-engine view of a five-engine market will mislead you about share of voice.

8. Rankability

Rankability sells to agencies, and AI tracking comes bundled with content production. Every plan includes 11 AI platforms checked daily, API and MCP access, unlimited client workspaces and unlimited team members. Starter is USD 97/mo for 100 tracked AI queries, Agency USD 297/mo for 300 and Agency Pro USD 497/mo for 500, with a seven-day trial that needs a card.

The volume ceiling arrives early at 500 queries, and much of the price pays for content projects, audits and keyword tracking. If you only want AI visibility data, you are buying a lot you will not use.

9. Siftly

Siftly has a free tier with 10 prompts on two engines, refreshed weekly, the cheapest way to see this data for your brand. Paid plans refresh daily: Starter USD 79/mo for 50 prompts on three engines, Growth USD 249/mo for 100 on five and Scale USD 599/mo for 150 on eight.

Engine count climbs faster than prompt count, so at USD 599 for 150 prompts the price per tracked prompt is high next to several tools above.

10. SISTRIX

SISTRIX is an established European SEO platform, and its prompt tracking is a module inside it, still in beta and included at no extra cost in every package. It covers ChatGPT, Perplexity, Google AI Overviews and Google AI Mode, with 100, 300, 600 and 1,500 prompts by plan from EUR 119/mo. For a team already on SISTRIX, one login can beat a slightly better standalone tool.

Gemini is missing from the tracked platforms, and a beta module inside an SEO suite moves at the suite’s pace. Check how often your prompts update on your package before relying on it for a launch.

11. LLMrefs

LLMrefs is one plan at 79 a month (USD, or EUR in Europe) for 500 tracked prompts across all the engines it supports, with weekly reports, API access, CSV export and unlimited projects and seats. On paper that is the most prompts for the money here, and unlimited projects suit consultants tracking several brands.

You track keywords, and the tool generates the prompts from them. That works for coverage and is weaker when you know the twelve questions that decide deals in your category.

If you meant the other kind of LLM monitoring

If you run an LLM in production and need to know what it costs, how slow it got and whether last week’s prompt change made outputs worse, nothing above helps. That category is LLM observability, a different search term.

Those platforms typically offer tracing across chains, agents and tool calls; eval suites scoring outputs against golden datasets as CI regression tests; dashboards for token spend, latency and error rates per model; guardrails screening for PII and prompt injection; and prompt versioning with side-by-side comparison.

We do not build any of that and have not benchmarked the vendors who do, so we will not rank them. Search for LLM observability or LLM evals, and check OpenTelemetry support early: the platforms that speak it are the ones you can leave later.

Picking one in practice

An in-house marketing team at one brand. Cover five engines, get citations you can act on, and pick a price that survives a budget review. Run weekly, and spend the first month reading answers before you trust the trend line.

An agency. The seat and project model decides this. Per-domain pricing multiplies painfully across a roster, so look for unlimited projects and seats and, if you report under your own brand, white label or an embeddable portal.

An enterprise. Procurement first: SOC 2, data residency, SSO, and whether the contract covers several regions and languages, which many self-serve products do not. Then integration, so the data lands beside organic and paid. Expect the prompt set itself to need real work: 2,000 careless prompts produce a very confident wrong answer.