LLM Pulse

Overview

LLM Pulse is an AI search visibility platform for monitoring how brands and competitors appear in AI-generated answers. Its public product surface combines prompt tracking, brand visibility, citation-source analysis, sentiment, share of voice, content recommendations, AI traffic analytics, exports, API access, and agency-oriented white-label options.

The product is positioned between a lightweight prompt tracker and a larger enterprise intelligence platform. Its self-serve plans publish EUR pricing and include five core AI surfaces, while Enterprise adds custom volumes, more models, white-label capabilities, enhanced security, and custom integrations.

• Best for: Brands, agencies, and marketing teams that want transparent pricing, recurring AI answer monitoring, citation analysis, and integrations.
• Not ideal for: Buyers requiring a deeply documented enterprise governance program on a self-serve plan, or teams expecting unlimited prompts at entry-level pricing.
• Starting price: €49/month on monthly Starter billing.
• Free trial: 14 days according to the official FAQ and pricing page.
• Primary strength: A broad self-serve AI visibility workflow with agency reporting options.
• Evidence confidence: Medium. Official pricing and feature documentation are detailed; independent user evidence is still very limited.

Who should use LLM Pulse?

Best fit

• Agencies that need multi-client projects and white-label reporting.
• Marketing teams tracking brand and competitor visibility across several AI search surfaces.
• SEO and GEO consultants who want prompt, citation, sentiment, and share-of-voice data in one workspace.
• Teams that want a public self-serve price before entering procurement.
• Brands that need CSV, Excel, Looker Studio, API, or MCP-based access to visibility data.
• Buyers who want prompt research, query fan-out, recommendations, and GEO writing features alongside monitoring.

Not a strong fit

• Enterprises that require a fully audited security and data-governance package before a custom procurement review.
• Teams that need hundreds or thousands of prompts on a low-cost plan.
• Buyers who need every AI model, including Claude, Copilot, Grok, DeepSeek, and Meta AI, included in self-serve plans.
• Teams looking for a traditional SEO suite with deep backlink, technical audit, and keyword-rank coverage.
• Buyers who treat visibility or citation metrics as proof of traffic, pipeline, or revenue.
• Teams that want a managed GEO strategy rather than a software-led monitoring workflow.

Quick facts

Fact	Details
Primary use case	AI search visibility, citations, sentiment, competitors, and AI traffic
Main category	AI Search Monitoring
Starting price	€49/month monthly; €41/month equivalent on annual billing
Free trial	14 days, according to the official FAQ and pricing page
Starter	1 project, 50 tracked prompts, 5 competitors, weekly tracking
Growth	2 projects, 150 tracked prompts, 10 competitors, weekly tracking
Scale	5 projects, 450 tracked prompts, 15 competitors, weekly tracking
Enterprise	Custom projects, prompts, models, integrations, and security features
Core AI surfaces	ChatGPT, Perplexity, Google AI Mode, Google AI Overviews, and Gemini
Additional models	Enterprise can add models such as Claude, Copilot, Grok, DeepSeek, and Meta AI
Team members	Unlimited on the public plan comparison
White label	Enterprise on the pricing table; agency pages describe partial and full white-label options
Last reviewed	August 19, 2026

AICiteKit editorial verdict

LLM Pulse is a credible candidate for agencies and small-to-mid-sized teams that want more than a basic mention tracker but do not want to begin with a demo-only enterprise platform. Its public pricing is easy to understand, its five-model base covers the major surfaces many teams track first, and its product includes a substantial set of operational features around prompts, citations, exports, and integrations.

Its agency positioning is especially notable. The official agency materials describe custom branding, domain options, multi-client management, client-ready reports, and a partner program. The official FAQ distinguishes partial white-label, full white-label on a custom domain, and embedded dashboards. These are strong vendor-published capability claims, but buyers should still verify the exact white-label tier, branding controls, client permissions, and contract terms in a trial or sales demonstration.

The evidence is weaker for outcome claims. A G2 profile shows 5.0/5 from one review, while Capterra currently shows zero user reviews. That is not enough to establish broad satisfaction, support quality, or reliable citation and revenue improvement.

Bottom line: Consider LLM Pulse when transparent self-serve pricing, multi-surface monitoring, agency delivery, and integrations matter. Before choosing it for a large agency or regulated enterprise, verify prompt capacity, data retention, model coverage, API limits, white-label scope, and security documentation in writing.

What the workflow looks like

1. Create a project for a brand, domain, or client.
2. Add competitors, markets, locales, and tracked topics.
3. Select or generate prompts around discovery, comparison, product fit, alternatives, and brand accuracy.
4. Run the prompt panel across the supported AI surfaces on the selected cadence.
5. Review mentions, positions, sentiment, share of voice, citations, and competitor movement.
6. Inspect which domains and URLs support the answer and where the brand has a source gap.
7. Export or connect the findings to Looker Studio, API, MCP, or internal reporting.
8. Use recommendations or GEO Writer for a bounded content or source action.
9. Retest the same prompt panel and compare answer evidence, not only a score.

This is a monitoring-and-action loop. It does not prove that a content change caused a citation, referral, or sale.

Core features

1. Prompt tracking

LLM Pulse tracks a defined set of customer questions across the AI surfaces included in the selected plan. The FAQ describes prompts such as category, comparison, and product-recommendation queries, with configurable language and locale.

A useful prompt panel should include:

• Branded questions;
• Category discovery;
• Problem and use-case questions;
• Competitor comparisons;
• Alternative queries;
• Pricing and feature questions;
• Objections and risk questions;
• Regional variations;
• Prompts where competitors are already visible.

The Starter plan allows 50 tracked prompts, Growth 150, and Scale 450. These are project-level plan limits, not a measurement of total customer demand.

2. AI model and surface coverage

The public pricing page lists five core surfaces on every plan:

• ChatGPT;
• Perplexity;
• Google AI Mode;
• Google AI Overviews;
• Google Gemini.

Enterprise can add more models, with the FAQ naming Claude, Copilot, Grok, DeepSeek, and Meta AI as possible additional coverage. Buyers should ask for the current model list, regional availability, sampling method, and whether all model outputs include complete answer text and source links.

Do not treat a five-surface monitoring plan as universal AI coverage. It is a defined sample of selected surfaces.

3. Mention, position, and visibility tracking

The platform describes metrics such as mention rate, AI Visibility Score, position, sentiment, and share of voice. These metrics can help answer:

• Does the brand appear for a defined prompt set?
• How often does it appear compared with competitors?
• Is it recommended early or late in the answer?
• Does the brand description change by model or market?
• Are competitors gaining share of voice?

A score is a directional benchmark. It should always be accompanied by prompt definitions, model or surface, date, location, language, denominator, and answer evidence.

4. Citation source analysis

Citation analysis identifies domains and pages that AI answers reference. This can help a team investigate:

• Which owned pages are cited;
• Which third-party sources support competitor answers;
• Which publishers or review sites shape the category narrative;
• Whether the cited source is current and factually accurate;
• Which source gaps could be addressed through content, PR, reviews, or documentation.

A cited URL is evidence that a source appeared in a captured answer. It does not prove that the URL caused the recommendation, that the source was the only evidence used, or that a person clicked it.

5. Sentiment analysis

LLM Pulse describes sentiment tracking for brand and competitor mentions. Use it to identify recurring wording or themes in a defined sample, such as:

• Positive or negative product descriptions;
• Accuracy problems;
• Repeated complaints;
• Competitor advantages;
• Differences between branded and category prompts.

AI sentiment is an interpretation of generated answers, not a replacement for customer research or a validated brand-perception survey. Re-run the same prompt panel before concluding that sentiment changed.

6. Share of voice and competitor benchmarking

Share of voice can make competitive movement easier to explain than a standalone brand score. A useful comparison shows:

prompt group + model + date + brand set + mention/recommendation rule

Ask whether the platform counts a passing mention, a recommendation, a citation, or a position-weighted result. The denominator and scoring formula matter more than the label.

7. Prompt research and query fan-out

Prompt research and query fan-out are intended to expand a seed topic into natural-language questions. This can help a team discover how customers ask AI about:

• Products and alternatives;
• Category problems;
• Use cases;
• Competitor comparisons;
• Pricing and implementation;
• Local or regional needs.

Generated prompts should be reviewed before being added to a KPI panel. Automatically generated questions can be redundant, unrealistic, or too broad to support a business decision.

8. Recommendations and GEO Writer

The official site describes recommendations and GEO Writer as action features connected to visibility gaps. A useful recommendation should identify:

• The prompt or topic where the gap was observed;
• The competitor or source appearing instead;
• The missing claim, evidence, or page;
• The proposed content or source action;
• The reviewer or owner;
• The next measurement window.

GEO Writer can accelerate drafting, but generated content still needs factual review, brand review, source verification, and an editorial decision. A draft that is optimized for likely retrieval is not proof that it will be cited.

9. LLM Pulse Agent

The LLM Pulse Agent is described as a conversational layer over project data. It can answer questions about visibility trends, citations, sentiment, share of voice, competitors, and usage, and can launch actions such as adding prompts, adding competitors, creating annotations, triggering recommendations, or starting GEO Writer tasks.

The pricing page lists the Agent on Growth and higher plans. Buyers should verify action permissions, audit logs, user roles, model usage, and whether agent actions can modify client projects without approval.

10. AI traffic analytics

Growth and higher plans list AI Traffic Analytics. The public FAQ also describes integrations with Google Analytics 4, Plausible, Piano Analytics, PostHog, Adobe Analytics, and Adobe CJA.

This can help connect:

AI visibility observation → detectable referral session → analytics outcome

It still does not capture every influenced visit, and an attributed conversion is not automatically causal revenue from a citation. Check the integration’s referral definitions, session stitching, attribution window, and handling of direct or untagged traffic.

11. Exports and integrations

The public pricing and FAQ materials describe:

• CSV export on all plans;
• Excel exports;
• Looker Studio on Scale and above in the pricing table;
• REST API on Scale and Enterprise;
• MCP integrations on all plans;
• Web analytics integrations;
• Custom integrations on Enterprise.

Verify current quotas, API endpoints, authentication, rate limits, export fields, and whether full answer text and cited URLs are included in the selected plan.

12. Agency white-label delivery

The official agency materials describe:

• Custom branding and domain;
• Multi-client dashboard;
• Team access controls;
• Client-ready white-labeled reports;
• Partial white-label on a vendor subdomain;
• Full white-label on an agency custom domain;
• Embedded dashboard integration;
• Unlimited seats;
• Agency partner training and sales materials.

The public pricing table places White Label under Enterprise, while the agency pages promote white-label access and agency-specific pricing. That apparent packaging difference is important: ask for the exact plan, add-on, minimum commitment, and domain setup required for the feature you need.

AI engine and platform coverage

Plan	Publicly stated coverage	What to verify
Starter	ChatGPT, Perplexity, Google AI Mode, Google AI Overviews, Gemini	Sampling, regional availability, response count, and weekly schedule
Growth	Same five core surfaces	Whether analytics and sentiment are available in all locales
Scale	Same five core surfaces plus broader analytics and integrations	API, Data Studio, custom reports, GEO testing, and ChatGPT Shopping limits
Enterprise	Core surfaces plus additional models on request	Full model list, daily cadence, regions, security, retention, and custom integrations

The public page lists five models/surfaces for every plan and names additional Enterprise options. Do not assume that Enterprise coverage applies to self-serve plans.

Pricing and plan limits

Prices below reflect the official pricing page checked on August 19, 2026. Prices are EUR monthly unless otherwise stated; VAT and applicable taxes are excluded.

Plan	Monthly price	Projects	Prompts	Competitors/project	Response allowance	Tracking	Notable features
Starter	€49	1	50	5	50/week/model	Weekly	CSV, MCP, recommendations, 3 GEO Writer tasks
Growth	€99	2	150	10	150/week/model	Weekly	Sentiment, AI Traffic Analytics, Agent, 5 GEO Writer tasks
Scale	€299	5	450	15	450/week/model	Weekly	Reputation, GEO Testing, ChatGPT Shopping, custom reports, API, Data Studio, 15 GEO Writer tasks
Enterprise	Custom	Custom	Custom	Unlimited listed	Custom	Custom	Additional models, white label, SSO, custom integrations, enhanced security

Annual billing is advertised at a lower monthly equivalent, with the public pricing page listing approximately €41, €83, and €249 per month for Starter, Growth, and Scale respectively when billed annually. Confirm the final checkout amount, tax, currency conversion, cancellation terms, and any agency minimum before purchase.

The public comparison lists unlimited team members. This does not mean unlimited projects, prompts, responses, API calls, or client workspaces.

Strengths

• Transparent EUR self-serve pricing from €49/month.
• 14-day free trial publicly advertised.
• Five important AI search surfaces included across the self-serve tiers.
• Clear progression from 50 to 150 to 450 tracked prompts.
• Citation, sentiment, share of voice, and competitor workflows in one product.
• CSV, Excel, MCP, API, Looker Studio, and analytics integrations.
• Explicit agency positioning with white-label and custom-domain claims.
• Unlimited team-member claim can reduce seat-based agency costs.
• Recommendations, GEO Writer, and an Agent create an action layer beyond monitoring.

Tradeoffs and limitations

• The self-serve prompt limits can become restrictive for multi-brand or multi-market programs.
• Weekly tracking is the public default; daily cadence may require Enterprise or a custom arrangement.
• Additional models beyond the five core surfaces are Enterprise-oriented.
• The pricing table places White Label under Enterprise, while agency pages describe white-label access; contract terms need confirmation.
• Public security, retention, data-residency, and subprocessors documentation is less visible than the product feature documentation.
• The scoring formula and sampling methodology are not fully explained in the public materials reviewed.
• “AI traffic” and revenue-related metrics are attribution signals, not causal proof.
• Independent user feedback is extremely limited.
• A broad feature set can require more configuration and governance than a simple prompt tracker.
• Content recommendations and GEO Writer still require human factual and editorial review.

User reviews and market feedback

Evidence snapshot

Source	Public signal	What it supports	Confidence
G2 LLM Pulse profile	5.0/5 from 1 review when checked August 19, 2026	A very small user-satisfaction signal	Low
Capterra LLM Pulse	0 user reviews; product listing and feature description	Product discovery and current listing presence	Low for user experience; medium for listing facts
Capterra methodology	Capterra describes review verification and sponsored-profile disclosure	How to interpret the directory, not product effectiveness	Medium
Trakkr independent review	4.4/5 editorial assessment based on public pricing, product materials, and feature review	Practical workflow observations and tradeoffs	Medium-low; competitor relationship disclosed
Official pricing	€49 Starter, €99 Growth, €299 Scale, custom Enterprise; prompt and feature limits	Commercial terms and plan boundaries	High
Official agency page	Custom branding/domain, client dashboard, white-label reports, partner program	Advertised agency workflow	High for claim existence; not independent proof

Recurring positive themes

The independent sample is too small to claim a broad user consensus. The public product materials and the one available independent review suggest potential strengths around:

• Transparent pricing and a free trial;
• Strong self-serve coverage of five core AI surfaces;
• Prompt, citation, sentiment, and competitor workflows in one platform;
• Agency-oriented multi-project and white-label capabilities;
• Integrations and exports beyond a closed dashboard.

These are supported fit signals, not proof that users consistently achieve better citations or revenue.

Recurring concerns and tradeoffs

The evidence supports several buyer concerns:

• A small review sample makes support and usability difficult to generalize.
• Prompt limits can matter quickly for agencies and multi-market brands.
• The strongest model breadth, security, and white-label terms are Enterprise-oriented.
• Weekly tracking may be insufficient for teams that need rapid experiment feedback.
• Public governance documentation is less detailed than the feature pages.
• Competitor-authored reviews can be useful for tradeoffs but are not neutral.

How much should buyers trust the evidence?

Trust the published price and plan table provisionally because they are direct, date-checked official evidence. Treat the G2 rating as a low-confidence signal because it is based on one review. Treat Capterra as a listing with no user sample. Treat the Trakkr review as a useful but commercially interested comparison: Trakkr is a competing product, so its favorable or unfavorable comparisons should be independently checked.

There is not enough independent evidence to claim that LLM Pulse reliably improves AI citations, traffic, pipeline, or revenue.

AICiteKit interpretation

LLM Pulse has one of the clearer public agency and self-serve stories in this category. Its strongest evidence is commercial transparency and feature breadth; its weakest evidence is independent user scale and independently verified business outcomes. The white-label capability is explicitly advertised, but buyers should confirm the exact Enterprise or agency contract terms before promising a fully rebranded client portal.

What to verify during a trial or demo

1. Create a project for one real brand and add a representative prompt panel.
2. Confirm the exact five AI surfaces and response cadence in your target market.
3. Open full answer records and check whether cited URLs, positions, dates, and locales are visible.
4. Compare the platform’s mention and citation counts with a manually reviewed sample.
5. Test prompt limits, response accounting, historical retention, and export fields.
6. Connect a non-production analytics property and inspect referral definitions before using AI traffic claims.
7. Ask for current security, DPA, subprocessors, retention, deletion, and data-residency documentation.
8. Request a written white-label quote showing custom domain, branding, client permissions, embed mode, report exports, and vendor-brand removal.
9. Confirm whether white label requires Enterprise, a minimum number of projects, annual billing, or an agency-partner agreement.
10. Test a client-facing report with an answer capture, cited URL, recommendation, limitation, and agency branding.
11. Ask what is logged when the LLM Pulse Agent creates prompts, annotations, or GEO Writer tasks.
12. Rerun the same prompt panel after a bounded change rather than judging the product from one answer.

Recommended workflows

For a small brand team

Start with the 14-day trial and a focused 25–50 prompt panel. Cover branded, category, comparison, and high-intent use cases. Use Starter if weekly tracking and five core surfaces are enough. Export the baseline before changing content.

For an agency evaluating white label

Do not start by promising a white-label portal to clients. First confirm the exact contract tier, custom-domain setup, client isolation, seat policy, report branding, and data permissions. Run one test client through the workflow and inspect both the client dashboard and exported report.

For source and citation analysis

Use citation source analysis to identify which domains and pages appear in competitor answers. Classify the opportunity before acting:

owned content gap
→ refresh or create a page
third-party source gap
→ PR, review, publisher, or community strategy
technical access gap
→ engineering or technical SEO review
accuracy gap
→ correct first-party and external facts

A citation gap is a diagnostic signal, not a guarantee that publishing a similar page will earn the same citation.

For AI traffic measurement

Connect analytics only after defining:

• Which referrers count as AI traffic;
• Whether UTMs are required;
• Attribution window;
• New versus returning sessions;
• Conversion definition;
• Treatment of direct and untagged traffic;
• How influenced but non-referral visits are handled.

Report AI traffic separately from AI visibility and citation rates.

Competitor comparison

Tool	Best fit	Key difference from LLM Pulse
Otterly.AI	Broad self-serve AI visibility monitoring	Strong monitoring and Looker Studio workflow; official docs say no native white label
Peec AI	Source-gap and competitor citation analysis	More focused on source intelligence and citation opportunities
Profound	Enterprise answer intelligence	More enterprise-oriented; pricing and procurement are less self-serve
AthenaHQ	Specialized GEO diagnosis and actions	More action-oriented GEO positioning; verify agency white-label scope
GrackerAI	B2B SaaS and cybersecurity	Narrower vertical focus; Enterprise lists white-label exports and SSO/SAML
PromptWatch	Prompt and crawler-oriented workflows	Different emphasis on crawler and referral signals
Rankscale	AI visibility and agency reporting	Compare project limits, reporting, prompt cadence, and white-label terms

LLM Pulse is most compelling when the buyer wants transparent pricing plus a broad set of monitoring, action, integration, and agency features. It is less compelling when the buyer needs independently proven enterprise outcomes or a deeply documented governance package before trial.

FAQ

Is LLM Pulse a GEO or AI visibility tool?

It is both an AI visibility monitoring and GEO action platform. Its core workflow tracks AI answers, mentions, citations, sentiment, and competitors, then adds recommendations, GEO Writer, analytics integrations, and agency reporting.

How much does LLM Pulse cost?

The public monthly plans checked on August 19, 2026 were €49 for Starter, €99 for Growth, and €299 for Scale. Enterprise pricing is custom. Annual billing shows lower monthly equivalents, and taxes are excluded.

Does LLM Pulse offer a free trial?

Yes. The official pricing page and FAQ advertise a 14-day free trial. Verify whether the trial includes every feature in the selected tier and whether any usage limits apply.

Does LLM Pulse support white-label reporting?

Yes, the official agency materials advertise white-label options, and the FAQ describes partial white-label, full white-label on a custom domain, and embedded dashboards. The public pricing table lists White Label under Enterprise, so agencies should obtain written confirmation of the required plan, add-ons, project minimums, and branding scope.

Which AI models does LLM Pulse track?

The public plans list ChatGPT, Perplexity, Google AI Mode, Google AI Overviews, and Gemini. Enterprise can add other models, including Claude, Copilot, Grok, DeepSeek, and Meta AI, subject to the current offering and contract.

Does LLM Pulse show citations?

The platform describes citation-source analysis that shows domains and pages referenced by AI answers. Verify whether the selected plan exposes full answer text, source URLs, citation position, date, model, and locale.

Does LLM Pulse prove AI-attributed revenue?

No. It can connect visibility and detectable referral signals to analytics under an attribution model. That does not prove that a citation or AI answer caused a sale or pipeline outcome.

Is the LLM Pulse G2 rating reliable?

The G2 profile showed 5.0/5 from one review when checked on August 19, 2026. That is a low-confidence user signal and should not be treated as broad customer consensus.

Who should choose LLM Pulse over Otterly.AI?

Choose LLM Pulse when agency white label, sentiment, AI traffic analytics, GEO Writer, prompt research, and integrations are central. Choose Otterly.AI when broad self-serve monitoring and Looker Studio are more important and a native white-label portal is not required.

Sources and verification

• LLM Pulse pricing — official plan prices, prompts, projects, AI surfaces, response allowances, integrations, white-label placement, and trial; checked August 19, 2026.
• LLM Pulse agency solution — official claims about custom branding, domains, client dashboards, white-label reports, and partner program; checked August 19, 2026.
• LLM Pulse FAQ — official explanations of models, cadence, metrics, exports, API, analytics, and white-label modes; checked August 19, 2026.
• LLM Pulse Agent — official description of the conversational agent and project actions; checked August 19, 2026.
• G2 LLM Pulse profile — 5.0/5 from one review when checked August 19, 2026; low-confidence user evidence.
• Capterra LLM Pulse listing — listing, feature description, and zero-review state; checked August 19, 2026.
• Trakkr LLM Pulse review — competitor-authored practical review; used for workflow tradeoffs and explicitly treated as commercially interested evidence; checked August 19, 2026.
• AICiteKit Otterly.AI review — comparison of monitoring, citation analysis, reporting, and agency limitations.
• AICiteKit GrackerAI review — comparison of B2B SaaS focus, Enterprise controls, and white-label claims.

This page separates official feature and pricing claims from independent user evidence. It does not claim that LLM Pulse guarantees AI citations, rankings, traffic, pipeline, or revenue.

Last reviewed

August 19, 2026.

Data confidence: Medium. Official pricing, feature, and agency claims are directly linked. Independent user evidence is limited to one G2 review, zero Capterra reviews, and a competitor-authored review. No AICiteKit hands-on trial has been completed.