AI Search Discovery coverage for every answer surface shaping demand.
Track how buyers discover, compare, and validate brands across AI answers. prompts-gpt.com combines prompt monitoring, competitor share, citation evidence, AI crawler signals, and content agents into one repeatable visibility workflow.
Monitor brand discovery across the models buyers actually use.
The coverage layer keeps prompt results comparable across answer engines, so teams can see whether a miss is isolated to one model, tied to crawler access, or part of a broader citation gap.
ChatGPT
openai/gpt-4o
Google AI
google/gemini-2.0-flash
Google AI Mode
google/gemini-2.0-flash
Perplexity
perplexity/sonar
Google Gemini
google/gemini-2.0-flash
Anthropic Claude
anthropic/claude-sonnet-4
Microsoft Copilot
openai/gpt-4o-mini
Amazon Rufus
amazon/nova-pro
Meta AI
meta/llama-3.3-70b
Meta Llama
meta/llama-3.3-70b
DeepSeek
deepseek/deepseek-chat
Grok
xai/grok-3
Share of answer (API-based)
Brand keyword detected in API response text. Limitation: keyword matching cannot always distinguish genuine recommendations from passing references.
Expand category and comparison prompts where the brand is absent. Validate findings by checking consumer interfaces manually.
Citation quality (URL-extracted)
URLs extracted from API response text, classified by domain pattern. Limitation: API citations may differ from consumer-interface citations.
Prioritize source fixes before treating score movement as durable. Cross-reference with actual consumer interface citations.
Recommendation rank (heuristic)
Brand position estimated from text analysis. Limitation: AI responses don't have formal rankings — position is inferred from mention order.
Write comparison proof and objection handling for prompts competitors win. Verify position manually in consumer interfaces.
Source freshness (estimated)
Content freshness assessed from page content. Limitation: does not verify actual crawler access or index status.
Refresh answer-ready sections and validate crawler access after publishing.
Evidence before score
Many tools show an aggregate score first. Prompts-GPT.com keeps answer excerpts, citations, confidence, and source context visible before asking for a decision.
Prompt-to-monitor handoff
Prompt discovery, Prompt Studio, public checker, and saved monitors share the same buyer-question workflow so a useful prompt does not die as a one-off run.
Agent orchestration for execution
The CLI turns evidence into local agent runs, parallel reviews, pipelines, evals, and worktree diffs.
See your brand's AI visibility in 30 seconds.
Enter any domain and get an instant AI visibility report — brand mentions, citation sources, platform coverage, and competitor context. No signup required.
Composite score from mentions, citations, sentiment, and coverage
Mention rate per AI platform in one scan
Source classification: owned, competitor, Reddit, docs, reviews
Who else gets recommended when buyers ask about your category
Organized around the work teams actually need to finish.
The category is crowded with feature lists. Buyers usually decide based on whether the product helps them explain the answer, fix the gap, and prove the improvement to someone else.
For SEO and content teams
Move from directional AI visibility scores to exact answer evidence, source gaps, and a publishable backlog.
Review reports, cited domains, prompt gaps, and content briefs from one workflow instead of stitching dashboards together.
For agencies and operators
Turn one branded diagnostic into reusable monitors, executive reports, and client-facing proof.
Use recurring prompt sets, exports, and competitive context so monthly reporting does not depend on screenshots and manual retesting.
For technical and product-led teams
Escalate answer gaps into local implementation work with Prompt Studio and content briefs.
This is the market gap most monitoring-only tools leave open: evidence can hand off directly into workspace-ready prompt artifacts and content briefs.
Track the evidence behind every AI recommendation.
Competitors in this category sell dashboards. The useful feature set is narrower and harder: show the answer, the cited source, the competitor that won, and the next action that can change the next answer.
Share of answer
Measure how often your brand is mentioned, ranked, and recommended against named competitors for the same category prompts.
Citation gap
See which owned pages, review sites, directories, forums, and media sources AI answers cite for competitors but not for you.
Prompt coverage
Group category, alternative, comparison, problem-aware, and research prompts so reporting matches real discovery journeys.
Action backlog
Turn misses into prioritized comparison pages, FAQs, schema fixes, llms.txt updates, media outreach, and content briefs.
Narrative drivers
Identify the domains, prompts, and sentiment patterns driving brand perception across AI answers. Surface top narrative contributors.
Prompt gap analysis
Find prompts where competitors are mentioned but your brand is absent. Turn coverage gaps into content briefs and outreach priorities.
Social thread intelligence
Track Reddit, Hacker News, LinkedIn, and other social threads that AI models cite during training. Identify discussions where your brand should be present.
Citation quality scoring
Score content across 6 dimensions AI engines reward: fact density, structured data, entity clarity, named frameworks, freshness, and answer readiness.
AI traffic attribution
Public 2026 studies now show meaningful movement in AI-driven discovery, but the mix varies sharply by engine, market, and measurement method. Use outside benchmarks as directional context, then validate per-engine traffic and conversion against your own analytics. Connect AI citations to site visits and conversions without treating public benchmarks as universal multipliers.
Citation velocity tracking
Measure week-over-week citation momentum. Know whether your brand is gaining or losing ground in AI answers — trajectory matters more than snapshots.
From AI search prompts to a ranked action backlog.
AI Search Discovery is not a single rank. It is the pattern of prompts, crawler visits, cited sources, competitors, sentiment, and model-specific visibility that determines whether AI agents can find and trust your brand.
Map AI agent discovery prompts
Group the questions people ask AI assistants when comparing vendors, products, categories, locations, and alternatives.
Connect crawls to citations
Compare how each supported answer surface mentions, ranks, cites, and frames your brand after agents and crawlers reach your pages.
Activate content agents
Prioritize owned-source fixes, third-party citation work, schema updates, and content briefs from answer evidence.
The feature bar is moving from dashboards to operating systems.
Monitoring still matters, but buyers now expect prompt intelligence, crawler proof, and implementation workflows. These are the product layers that keep appearing in competitive research and user feedback.
Monitor
Track 23 metrics across 12 configured engines with prompt-level answer evidence, citations, and competitor context.
Optimize
Turn misses into source fixes, FAQ updates, comparison pages, schema improvements, and prompt-gap prioritization.
Implement
Use content briefs, project workflows, free tools, and agent workflows to move from findings into shipped changes.
Orchestrate
Run parallel agents, chain pipelines, and evaluate results via CLI so AI visibility gaps can become local implementation work.
Crawler proof is still thin
Competitive pages increasingly mention sources and citations, but the strongest buyer need is still a provable path from crawler reads to answer evidence and page fixes.
Prompt intelligence is fragmented
Otterly, Peec, Semrush, Ahrefs, and Profound all emphasize prompt or question tracking. The gap is turning discovery prompts into saved monitors, briefs, and implementation queues.
Traffic attribution is inconsistent
AI referral conversion research is directionally strong but varies by study and industry. Product copy should show attribution as a workflow, not a guaranteed lift.
Implementation is the missing layer
Most platforms can identify misses and recommendations. Buyers still need a workflow that creates briefs, schema tasks, comparison pages, source outreach, and validation runs.
No agent orchestration for visibility
Multi-agent coding tools are growing quickly, and AI visibility platforms are adding recommendations. Public competitor materials do not show a visibility-focused CLI with parallel, pipeline, and eval modes.
MCP is becoming table stakes
Peec AI now documents native MCP integration and prompt workflows, and other vendors are broadening API access. Dashboards alone are no longer enough — SDK and MCP-style access make visibility evidence usable inside content, engineering, and reporting workflows.
Brand monitoring tools are converging on AI
Yext Scout, BrandBeacon, Trackerly, and ClayHog now offer AI-specific brand monitoring alongside traditional brand tracking. The category boundary between brand monitoring and AI visibility is dissolving.
Keyword-to-prompt expansion eliminates setup friction
SEOmonitor generates 50K+ prompt variations per keyword automatically. This eliminates the manual prompt setup barrier that slows adoption on prompt-based platforms.
Citation absorption matters more than raw citation counts
2026 GEO research separates source selection from answer absorption: pages can be cited without shaping the final answer. Product surfaces should expose evidence quality, answer excerpts, and source influence rather than counting URLs only.
Repeated evidence beats one-off score precision
Recent AI Overview and GEO studies show wide variance by query form, engine, and source behavior. Free checks should be useful, but paid value must come from repeated monitors, confidence labels, and trend comparison.
Research applied
What the 2026 competitor sweep changed.
Source visibility is separate from brand visibility
Peec's public docs frame AI visibility as two distinct jobs: explicit brand mentions and source/citation visibility. Product surfaces should show both so teams know whether to fix recognition, citations, or both.
Peec metrics docs
Prompt capacity and country coverage affect measurement quality
Otterly's April 8, 2026 pricing help page shows explicit prompt caps by plan and add-on engine coverage. Product setup should push users toward enough buyer-intent coverage instead of over-trusting one-off checks.
Otterly pricing help
SEO suites are bundling AI reporting with existing workflows
Semrush's AI Visibility Toolkit now exposes prompt research, competitor research, cited pages, source opportunities, and large prompt-database reporting inside the broader suite. Prompts-GPT must emphasize implementation handoff and CLI orchestration, not just another report.
Semrush Visibility Overview report
See it in action — no signup required
Run a free AI visibility check on any domain. See brand mentions, citations, competitor context, and improvement opportunities in under 30 seconds.
Brand detection
See whether AI engines mention, rank, and recommend your brand
Citation analysis
Discover which sources AI trusts for your category
Action queue
Get specific next steps to improve AI visibility
23-Metric System
Measure the signals behind agent-driven discovery.
Each scan captures the outcome and the evidence behind it: where the brand appeared, which crawlers reached it, which competitors displaced it, which sources were cited, and what content-agent action should move the next answer.
Baseline
AI Visibility Score
A rollup score for whether the brand is mentioned, cited, recommended, and framed well across monitored prompts.
Presence
Brand Mention Rate
How often the brand appears in AI visibility answers across the tracked prompt set.
Presence
Answer Position
Average placement when the answer lists vendors, products, agencies, or recommended sources.
Competition
AI Share of Voice
The brand's share of answer mentions compared with named competitors in the same prompt cluster, weighted by prompt intent and audience reach.
Message
Narrative Drivers
Top cited domains and specific prompts shaping the brand's story, revealing influential publishers for outreach and the exact queries driving conversation.
Competition
Competitor Pressure
Prompts where competitors appear ahead of the brand or own the recommendation completely.
Message
Sentiment Quality
Whether answer wording is positive, neutral, mixed, or negative when the brand is mentioned.
Sources
Owned Citation Share
How often answers cite owned pages instead of third-party, competitor, community, or directory sources.
Sources
Source Quality Score
A quality read on the sources shaping the answer, including owned pages, reviews, media coverage, listicles, Reddit, YouTube, and news.
Technical
Crawler Citation Match
How often cited pages have recent AI crawler activity, so crawler access can be connected to later answer evidence.
Action
Opportunity Backlog
Open fixes generated from missed mentions, weak citations, competitor wins, content gaps, and readiness issues.
Demand
Prompt Volume
Estimated monthly search demand behind tracked prompts, derived from real search behavior rather than synthetic queries.
Presence
Geo Distribution
Geographic breakdown of brand mentions across countries and regions where AI platforms reference the brand.
Sources
Citation Quality Score
How citation-ready your content is across 6 dimensions: fact density, structured data, entity clarity, named frameworks, freshness, and answer readiness.
Sources
Social Thread Coverage
Reddit, Hacker News, LinkedIn, and other social threads where your brand or competitors are discussed — the training signals AI models use.
Baseline
Entity Recognition Score
How consistently AI models correctly identify, describe, and contextualize your brand — measuring mention consistency, context accuracy, and disambiguation across engines.
Competition
Prompt Difficulty
Estimated difficulty of earning a brand mention for each prompt, factoring competitor density, citation authority, answer consistency, and intent competitiveness.
Sources
Citation Readiness
How ready your content is to be cited by AI models across 6 dimensions: fact density, structured data, entity clarity, named frameworks, freshness, and answer readiness.
Baseline
Citation Velocity
Week-over-week citation momentum — whether the brand is gaining or losing AI citation ground. Complements AISoV by measuring trajectory rather than market share at a point in time.
Sources
AEO Content Score
Answer Engine Optimization readiness across 7 factors: E-E-A-T signals, schema markup, direct answer quality, content freshness, structured formats, readability, and fact density.
Competition
Prompt-Space Occupancy
Percentage of monitored prompts where the brand appears. Use it as a directional coverage metric and compare it against repeated scans, competitor pressure, and source quality.
Baseline
Visibility Volatility
How much the brand's visibility fluctuates across scan cycles. Low volatility means AI models reliably include the brand; high volatility means inconsistent citation patterns.
Baseline
Multi-Platform Citation Impact
How widely the brand is cited across different AI platforms. Use it as a directional cross-platform authority signal and validate conversion lift against your own analytics.
A complete operating layer for AI answer visibility.
01Monitor & Scan9 features
AI Search Discovery Reports
Build a report for a configured domain with 25 custom prompts, ranking evidence, crawler signals, and Brand Performance analysis across discovery surfaces.
Prompt Monitor
Track category, competitor, recommendation, local, alternatives, and buying-intent prompts buyers ask AI agents before visiting your site.
Answer Visibility Scan
Extract brand mentions, answer position, sentiment, competitors, citations, model surface, and the source evidence behind each result.
AI Crawler Timeline
See which known AI agents and crawlers read your pages, then connect those visits to later citations and answer evidence.
Historical Trend Tracking
Chart visibility score, brand mention rate, and answer share over time to prove whether content changes and source improvements move AI answers.
Citation Quality Scoring
Score content against the 6 dimensions AI engines tend to reward: fact density, schema clarity, named frameworks, entity clarity, freshness, and answer readiness.
02Analyze & Understand17 features
Media & Citation Analytics
Classify owned, competitor, Reddit, YouTube, review, news, directory, publisher, video, and listicle sources shaping AI recommendations.
Prompt Research
Find prompt gaps from competitor wins, missed mentions, buying intent, source gaps, and recommendation answers.
AI Readiness Checks
5 checks review crawler access, entity clarity, citation quality, prompt coverage, and competitor pressure.
Prompt Gap Analysis
Find prompts where competitors are mentioned but your brand is absent. Turn gaps into prioritized content briefs and comparison page opportunities.
Geo Distribution
See brand mention share by country and region. Understand where AI answers include your brand and where international visibility needs work.
Export Suite
Download brand reports, citation data, GEO audits, Markdown evidence, and JSON payloads for stakeholder review and BI workflows.
Prompt Difficulty Scoring
Estimate how hard it is to earn a mention for each prompt. Factor in competitor density, citation source authority, and answer consistency across AI engines.
Crawler-to-Citation Correlation
Connect which pages AI bots actually crawl to which pages get cited. Identify high-crawl/low-citation pages and recommend optimization priorities.
GEO Tactic Scoring
Score content against directional AEO/GEO patterns: answer-ready blocks, source-backed statistics, visible FAQs, named frameworks, fluent prose, comparison structure, and anti-pattern detection.
03Act & Report14 features
Content Agents
Turn crawl, citation, and prompt evidence into briefs for pages, FAQs, comparisons, schema fixes, source outreach, and answer-ready updates.
Shopping Visibility
Track product recommendations, buying prompts, category winners, missing attributes, and competitor-owned purchase journeys.
GEO Content Scoring
Score any page against the 8 signals AI engines reward when selecting sources: answer blocks, FAQ schema, entity clarity, citation evidence, and freshness.
Narrative Drivers
Identify the top cited domains and prompt patterns driving brand perception across AI answers. Surface sentiment trends and competitor narrative share.
Social Thread Intelligence
Track Reddit, Hacker News, LinkedIn, Twitter/X, GitHub, and Stack Overflow threads that AI models reference. Identify discussions where competitors are cited but your brand is absent.
Content Readiness Scoring
Score any page for AI citation readiness across 6 dimensions: fact density, structure quality, answer readiness, authority signals, freshness, and schema markup.
Prompt-Space Occupancy Score
Measure the percentage of relevant prompts where your brand appears. Use it with competitor pressure and source evidence to judge whether coverage is actually improving.
Visibility Volatility Index
Track how consistently AI models include your brand across scan cycles. High volatility signals unreliable entity signals; low volatility confirms strong brand recognition.
Entity Recognition Scoring
Measure how consistently AI models correctly identify and describe your brand. Tracks mention consistency, context accuracy, and disambiguation success across all monitored engines.
How prompts-gpt.com compares to typical AI visibility tools.
Most AI monitoring platforms provide aggregate scores. prompts-gpt.com provides prompt-level evidence, citation intelligence, and content action workflows across 23 visibility metrics and 12 AI engines.
15
Feature categories
compared head-to-head
12
AI engines
vs. 2–13 competitors
23
Visibility metrics
per scan
6
Free tools
no signup required
| Capability | Prompts-GPT.com | Otterly / Peec AI | Profound / Semrush |
|---|---|---|---|
| Prompt-level answer evidence | Full answer text, citations, sentiment | Aggregate score only | Score + limited evidence |
| AI engines monitored | 12 engines (ChatGPT, Google AI, Google AI Mode, Perplexity, Google Gemini, Anthropic Claude, and 6 more) | 2–6 engines (some as paid add-ons) | 5–10 engines |
| Visibility metrics per scan | 23 metrics | 3–5 metrics | 5–8 metrics |
| Citation source classification | 14 source types: Owned, Competitor, Review, Reddit, YouTube, Hacker News, LinkedIn, Twitter/X, GitHub, Stack Overflow, and more | Basic URL list | Domain-level only |
| Citation quality scoring | 6-dimension scoring (fact density, schema, entity clarity, frameworks, freshness, answer readiness) | Multi-factor GEO audit workflow (Otterly) | Basic content audit |
| Entity recognition scoring | Measures mention consistency, context accuracy, and disambiguation across engines | Not available | Not available |
| Prompt difficulty scoring | Factors: competitor density, citation authority, answer consistency, intent competitiveness | Not available | Not available |
| Content briefs from prompt gaps | Generated from answer gaps with optimization checklists and source context | Not available | Not available |
| Social thread tracking | Reddit, Hacker News, LinkedIn, Twitter/X, GitHub, Stack Overflow | Not available | Reddit only (Semrush Enterprise) |
| Free tools (no signup) | 6 tools | 0–1 tools (Otterly: GEO Landing Page Creator) | 1–2 tools (Ahrefs: free checker) |
| llms.txt support | Generator + monitoring + optimization | Not available | Monitoring only |
| Export suite | PDF, CSV, Markdown, JSON | PDF/CSV only | CSV + API (Enterprise) |
| Multi-platform citation impact | Directional cross-platform scoring for validating authority and referral quality | Not available | Not available |
| Citation velocity tracking | Week-over-week momentum visible in saved evidence and reporting | Not available | Not available |
| Shopping visibility | Product recommendations, buying prompts, category winners | Not available | Writesonic Shopping Tracker |
The 8 content patterns that earn AI citations.
Public GEO research points to repeatable content patterns that can improve citation readiness, but results vary by category, source quality, and model behavior. Our GEO Content Scorer and content briefs treat those patterns as testable signals, not guaranteed citation lift.
Direct answers high on the page
High impactPut concise answer-ready paragraphs near the top of the page so models can extract a factual summary quickly.
Answer capsules
High impactShort, self-contained answer blocks make recommendation, definition, and comparison prompts easier to cite.
Decision tables
Useful for commercial promptsStructured HTML comparison tables help AI systems summarize pricing, features, and tradeoffs without guessing.
Expert attribution
Trust signalNamed quotes, cited research, and explicit attribution strengthen why a page deserves to be referenced.
Action checklists
Useful for how-to promptsScannable steps and clear procedures improve extractability for workflow and implementation questions.
Visible FAQ sections
SupportiveFAQ content can help when it is visible on the page and matches real user questions rather than being schema-only filler.
Statistics with sources
Trust signalSource-backed numbers give AI systems concrete facts to reuse and make claims easier to verify.
Fluent prose
Baseline requirementClear, low-friction prose improves extractability and reduces the chance that a model skips a page.
Fresh canonical details
Important for trustCurrent product facts, current pricing, and stable canonical URLs reduce stale or conflicting summaries.
List and section structure
Useful for summarizationWell-structured lists, subsections, and headings help answer engines fragment and recompose a page accurately.
Listicle extractability
High impactNumbered list items that are self-contained and fact-dense are easier for AI systems to cite than long unstructured marketing pages.
Third-party brand mentions
Trust signalEditorial mentions in podcasts, roundups, and expert quotes can strengthen how answer engines describe a brand beyond owned copy alone.
Keyword stuffing
Over-optimized copy reduces readability and makes the page less trustworthy as an answer source.
Source: Directional AEO/GEO practitioner research and current public AI visibility audits
What makes Prompts-GPT.com different?
Prompts-GPT.com combines monitoring, optimization, and implementation in one full-loop workflow. It monitors 12 AI engines with 23 visibility metrics per scan, classifies 14 public citation source types, and generates content briefs directly from answer gaps. In a market where competitors now cover serious monitoring and recommendations, we differentiate on prompt-level evidence and implementation workflow — not just dashboards.
Engines: ChatGPT, Claude, Gemini, Perplexity, Grok + 7 more — no per-engine surcharges
Metrics: 23 per scan with the full metric glossary documented publicly
Free tools: 6 tools, no signup required
Differentiators: Full-loop workflow, content briefs from gaps, entity scoring, PSOS scoring
See these features in action
Run a free AI visibility check on any domain to experience prompt-level evidence, citation intelligence, and opportunity generation firsthand.
Features competitors charge extra for — or don't offer at all.
The AI visibility market now spans dozens of monitoring, optimization, and enterprise products. Here's what prompts-gpt.com delivers that many alternatives still leave fragmented across separate tools or workflows.
Full-loop workflow
Connect monitoring, scoring, content briefs, and implementation in one workflow instead of splitting the work across multiple tools.
6 free tools, no signup
Visibility checker, market search, GEO scorer, query generator, llms.txt generator, and Codex launcher — all free.
Show 10 more differentiators
Content readiness + briefs from gaps
Score any page for AI citation readiness, then generate prioritized content briefs from prompt gaps.
Visibility Volatility Index
Track scan-to-scan consistency. High volatility means AI models are inconsistent or your source signals are unstable.
Social thread intelligence
Track 6 social platforms (Reddit, HN, LinkedIn, Twitter/X, GitHub, Stack Overflow) that AI models cite.
Crawler-to-citation correlation
Connect which pages AI bots crawl to which pages get cited. Identify high-crawl/low-citation pages to prioritize for optimization.
Self-audit methodology
We run the same workflow on our own product and publish the evidence publicly so buyers can inspect the method as well as the claim.
Export everything
PDF reports, CSV citations, Markdown evidence, and JSON payloads. Your data, your format, no lock-in.
What the research says buyers now expect.
Competitors now cover serious monitoring, prompt research, and source analytics. The product work below keeps Prompts-GPT.com focused on the defensible layer: enough prompt depth, visible evidence confidence, and implementation from the same findings.
Prompt and engine coverage
Otterly documents prompt tiers and daily prompt tracking across core AI search surfaces, with Google AI Mode and Gemini as add-ons.
Keep prompt-depth guidance visible in /prompts, the query generator, and monitor creation so users build representative prompt sets before reporting trends.
Evidence sourceSource and citation analytics
Semrush exposes cited pages, topic coverage, prompt research, competitor gaps, and AI-readiness audit checks in the AI Visibility Toolkit.
Expose source confidence, citation quality, crawler evidence, and action ownership directly in reports, sources, free tools, and AI Search results.
Evidence sourceSimple visibility metrics
Peec defines visibility as the percentage of AI responses that mention the brand, which makes the score easy for buyers to understand.
Keep simple mention-rate language, but pair it with answer excerpts, recommendation framing, source confidence, and repeated-scan thresholds.
Evidence sourceMeasurement confidence
2026 research warns that single-run AI visibility metrics can look falsely precise.
Label public checker output as directional and reserve executive confidence for repeated monitors across enough prompts, engines, and scan windows.
Evidence sourceImplementation layer
Generic automation tools now run multiple coding agents with worktree isolation, lint/type/test gates, and evaluation-style comparisons.
Position visibility remediation infrastructure: turn a missed AI mention into research, content, schema, source repair, and evaluated implementation work.
Evidence sourceCrawler and AI-readiness proof
AI visibility buyers now expect crawler access, source accessibility, and technical AI-readiness checks, not only answer screenshots.
Keep llms.txt, robots.txt, crawler access, source freshness, and answer-ready content checks visible in free tools, docs, and reports.
Evidence sourceSuite-vs-operating-workflow clarity
Semrush One packages AI visibility into a broader SEO and content suite, giving existing Semrush customers a convenient bundled path.
Make the narrower value explicit: monitor AI answers, generate action briefs, export evidence, and run local agent orchestration without adopting a heavyweight SEO suite.
Evidence sourceCommon questions about platform features.
What AI engines does prompts-gpt.com monitor?
prompts-gpt.com supports brand mentions, citations, sentiment, and competitor monitoring across ChatGPT, Google AI, Google AI Mode, Perplexity, Google Gemini, Anthropic Claude, Microsoft Copilot, Amazon Rufus, and 4 more configured engines. Paid AI Visibility plans do not require per-engine add-ons, but each plan has a per-monitor engine cap.
How many visibility metrics are tracked per scan?
Each scan captures 23 distinct visibility metrics: ai visibility score, brand mention rate, answer position, ai share of voice, narrative drivers, competitor pressure, sentiment quality, owned citation share, source quality score, crawler citation match, opportunity backlog, prompt volume, geo distribution, citation quality score, social thread coverage, entity recognition score, prompt difficulty, citation readiness, citation velocity, aeo content score, prompt-space occupancy, visibility volatility, multi-platform citation impact. Prompts-GPT documents the full metric list publicly so teams can review what each metric means before relying on it.
Can I monitor competitor brands?
Yes. The platform tracks competitor mentions, recommendation order, cited sources, and share of voice across all monitored prompts. You can see which competitors win specific prompt clusters and why.
Does prompts-gpt.com track Reddit and social threads?
Yes. The platform classifies citations from Reddit, Hacker News, LinkedIn, Twitter/X, GitHub, and Stack Overflow — the social platforms that AI models most frequently cite in training data. This helps identify threads where competitors are discussed but your brand is absent.
What is Citation Quality Scoring?
Citation Quality Scoring measures how ready your content is to be cited by AI models. It evaluates 6 dimensions: fact density, structured data coverage, answer readiness, entity clarity, named frameworks, and freshness. Use it as directional guidance, not as a guaranteed citation-lift promise.
How do content agents work?
Content agents analyze prompt gaps, competitor wins, and citation evidence to generate specific content briefs. Each brief includes the target prompt, competing sources, recommended content structure, and optimization checklist.
What export formats are supported?
The platform supports PDF brand reports, CSV citation exports, GEO audit PDFs, and public Markdown or JSON evidence exports where those surfaces are exposed. Export availability depends on the current plan and the workflow surface.
How does prompts-gpt.com compare to Otterly, Semrush, Profound, or Promptwatch?
Prompts-GPT.com is built around a full-loop workflow: monitoring, optimization, and implementation in one product. As of May 24, 2026, reviewed public pricing shows Otterly from $29/mo, Peec with brand and agency tiers starting at 50 prompts and 3 models, Promptwatch from $99/mo, Profound from $99/mo for a ChatGPT-only starter with broader workflows on higher plans, and Semrush AI Visibility from $99/mo standalone or bundled with Semrush One. Prompts-GPT differentiates on prompt-level evidence, 23 documented metrics, 6 no-signup tools, and content briefs from answer gaps.
Explore more
Dive deeper into pricing, solutions, and optimization resources.
Show the same product truth to crawlers, AI systems, and evaluators.
Competitive AI visibility products expose public discovery files, evidence-led docs, and a transparent self-check path. prompts-gpt.com should do the same so the market sees the current AI visibility platform, not older prompt-library snapshots or a rerun URL without context.
Use the live checker for diagnostics. Use the published markdown or JSON self-audit exports when you need a stable public proof artifact. The JSON export also includes the Prompts-GPT.com project preset and monitor blueprint used for the ongoing internal follow-up path.
Brand facts
Canonical short-form product facts page for AI systems and evaluators.
brand-facts.json
Machine-readable product facts endpoint under /.well-known/.
llms.txt
Machine-readable source map for the current product truth.
robots.txt
Crawler access policy for public and private routes.
sitemap.xml
Canonical public URL inventory for discovery and recrawl.
Self-audit export
Stable markdown proof artifact for the prompts-gpt.com self-evaluation.
Self-audit JSON
Machine-readable self-audit payload with credibility notes and project guidance.
Self-audit report
Public methodology, export guidance, and current discovery gaps.
Live checker rerun
Fresh diagnostic surface for answer snapshots, citations, and recommendations.
Make each share surface explicit about stability, format, and audience.
The self-test showed that public discovery surfaces are only credible when buyers can tell which link is stable proof, which one is a live rerun, which files are AI-readable discovery aids, and which path requires sign-in for recurring monitoring.
Self-audit markdown export
markdownStable proofStable public proof artifact for external sharing, procurement review, and citations.
Audience: buyer
Open Self-audit markdown export: /reports/prompts-gpt-com-self-audit.mdSelf-audit JSON export
jsonStable proofMachine-readable self-audit payload with credibility notes, export context, and project guidance.
Audience: ai-system
Open Self-audit JSON export: /reports/prompts-gpt-com-self-audit.jsonSelf-audit article
htmlStable proofMethodology, current limits, and product-claim boundaries for public evaluation.
Audience: buyer
Open Self-audit article: /articles/prompts-gpt-com-ai-visibility-self-auditFree checker rerun URL
htmlLive diagnosticFresh answer snapshot, source list, and recommendations for live inspection.
Audience: operator
Open Free checker rerun URL: /free-tools/ai-brand-visibility-checker?site=prompts-gpt.com&submitted=1Official llms.txt
txtAI-readableCanonical AI-readable source map for the current public product story.
Audience: ai-system
Open Official llms.txt: /llms.txtrobots.txt
txtAI-readableCrawler access policy for public versus private routes.
Audience: crawler
Open robots.txt: /robots.txtsitemap.xml
xmlAI-readableCanonical public URL inventory for discovery and recrawl.
Audience: crawler
Open sitemap.xml: /sitemap.xmlPrompts-GPT.com project preset
htmlProject handoffAuthenticated handoff path from one public self-check into recurring monitoring.
Audience: operator
Open Prompts-GPT.com project preset: /free-tools/ai-brand-visibility-checker?auth=sign-up&next=%2Fdashboard%2Fprojects%2Fnew%3Fbrand%3DPrompts-GPT.com%26site%3Dhttps%253A%252F%252Fprompts-gpt.com%26category%3DAI%2Bsearch%2Bvisibility%2Bplatform%26source%3Dfree-checkerMake the public proof boundary explicit for every credibility check.
The self-audit should not force evaluators to infer which parts are inspectable now, which are only directional, which require a saved monitor, and which require sign-in. The matrix below makes that boundary machine-readable and visible on the page.
Answer snapshots
Inspectable nowA credible AI visibility product should show the actual answer snippet instead of summarizing results as a score only.
Inspect by
Run the checker on prompts-gpt.com, read the answer snippet and full-answer evidence, then preserve that run with the checker markdown or JSON download.
Share policy
Use checker-run markdown or JSON when sharing one diagnostic run. Use the self-audit export and article for durable product-level proof.
Citations and source evidence
Inspectable nowBuyers need to see whether owned pages, third-party reviews, or comparison pages are actually supporting the answer.
Inspect by
Inspect detected source URLs, provider-verified flags, top industry sources, and source labels in the live checker result or the checker-run exports.
Share policy
Treat citation lists from one checker run as directional evidence. Use the self-audit export to explain what the product can prove publicly today.
Recommendations
Inspectable nowDiscovery tooling is only useful when the answer evidence turns into concrete next actions instead of a generic score.
Inspect by
Review the checker recommendations below the answer snapshot and compare them with the documented workflow in the public docs.
Share policy
Recommendations from one run are acceptable to share as tactical diagnostics, but not as recurring trend proof.
Opportunity backlog
Inspectable nowOperators need a clear backlog that connects missing mentions or weak citations to pages, briefs, FAQs, or source fixes.
Inspect by
Inspect the opportunity cards and exported opportunity payload from the live checker run for prompts-gpt.com.
Share policy
Use checker-run exports for run-specific opportunities. Use the self-audit export to explain the proof boundary between one run and recurring monitoring.
Scoring and confidence
Directional onlySingle-run scores are easy to overclaim. Public proof should state that a preview score is directional until repeated prompt tracking exists.
Inspect by
Compare the preview score against the benchmark prompt pack and the scoring limitation notes before treating it as a durable benchmark.
Share policy
Do not use a single rerun score as a long-term performance claim. Use repeated monitoring for trend or share-of-voice claims.
Crawler-to-citation logic
Monitor onlyConnecting crawler events to later citations is valuable, but the free checker should not imply that capability without a saved monitor.
Inspect by
Review the public feature and docs pages for the workflow description, then confirm the actual crawler-to-citation evidence only inside a saved monitor.
Share policy
Keep crawler-to-citation claims at the workflow and methodology level in public materials. Do not present them as checker output.
Project guidance and recurring setup
Requires authA public self-check should hand off cleanly into a real recurring project when the platform's own prompt set is worth monitoring.
Inspect by
Use the built-in Prompts-GPT.com project preset and baseline monitor prompts after sign-in, then rerun the benchmark prompt pack as a saved project.
Share policy
Public proof can link to the authenticated handoff path, but project creation and recurring monitor evidence remain account-bound.
A credible self-test needs more than one branded rerun prompt.
The branded checker prompt is useful for a first-pass diagnostic, but recurring self-evaluation should also test category, competitor, recommendation, local, and buying-intent prompts. Those benchmark prompts are exported with the self-audit so the proof path stays reproducible.
Analyze AI visibility for prompts-gpt.com. Is the brand understood, mentioned, cited, and positioned accurately in AI answers?
diagnosticUseful as a first-pass branded diagnostic, but still biased because the prompt names the brand directly.
best AI search visibility platforms for marketing teams
categoryExpands self-evaluation beyond the branded diagnostic into category-level AI visibility prompts.
tools for monitoring brand visibility in ChatGPT and Perplexity
categoryExpands self-evaluation beyond the branded diagnostic into category-level AI visibility prompts.
prompts-gpt.com alternatives for AI visibility monitoring
competitorChecks whether prompts-gpt.com is explainable in comparison and alternative workflows instead of only branded prompts.
prompts-gpt.com vs PromptWatch for answer engine optimization
competitorChecks whether prompts-gpt.com is explainable in comparison and alternative workflows instead of only branded prompts.
which AI visibility tools should an SEO agency compare
recommendationTests whether the platform appears in shortlist and buyer-guidance prompts where evaluators expect independent recommendations.
recommend software for tracking AI answer citations and brand mentions
recommendationTests whether the platform appears in shortlist and buyer-guidance prompts where evaluators expect independent recommendations.
AI search visibility tools for teams in the United States
localVerifies whether region-specific discovery claims hold outside the core branded story.
AI visibility software pricing and features for a growing brand
buying_intentChecks whether pricing and feature pages support commercial AI answers with enough proof.
which AI brand monitoring platform should I buy
buying_intentChecks whether pricing and feature pages support commercial AI answers with enough proof.
Public AI visibility products are judged on proof, not only feature copy.
Competitor research consistently raises the same bar: exportable evidence, shareable reporting, public methodology, and a clean handoff into recurring monitoring. This kit exists so prompts-gpt.com reads like an AI Search visibility platform rather than a generic dashboard with AI-themed marketing.
Stable public proof export
supported publiclyBuyers need a shareable artifact that does not mutate when answer providers change.
Machine-readable evidence export
supported publiclyAI systems, evaluators, and internal tools need a structured payload instead of screenshot-only proof.
Live diagnostic rerun
supported with limitsOperators need a fresh answer snapshot to inspect citations, entities, and recommendations on demand.
Public methodology and claim boundaries
supported publiclyTrust depends on explaining what scoring, citations, and crawler context can prove versus what requires saved monitoring.
Recurring reporting handoff
monitor onlyA credible platform must convert a public diagnostic into a saved project when visibility work becomes ongoing.
PDF and CSV export with citation detail
supported with limitsStakeholders expect downloadable brand reports and citation spreadsheets with full and summary modes.
Scheduled report delivery
supported with limitsRecurring automated email reports eliminate manual export steps for teams that report AI visibility to leadership.
Shareable online dashboards
monitor onlyAgencies and teams need live dashboard links that stakeholders can access without account setup.
BI connector (Looker Studio)
monitor onlyData teams need live structured feeds into existing dashboards and reporting pipelines.
Content briefs from AI insights
supported with limitsVisibility data should produce concrete content recommendations, not just metrics.
Prompt gap and competitor gap analysis
supported with limitsBuyers need to identify exactly which prompts competitors own and where the brand is absent.
Geo distribution tracking
supported with limitsGlobal brands need to understand which countries and regions provide their highest AI visibility.
Public proof expectations were checked against live category examples.
This self-audit did not invent a reporting standard. The research pass checked how adjacent AI visibility products explain citations, documentation, and exports in public before setting the proof policy for prompts-gpt.com.
Semrush AI Visibility Toolkit
Recurring reporting, prompt research, Reddit analysis, negative sentiment detection, and shareable AI visibility dashboardsReviewed 2026-05-17Semrush publicly documents prompt research, visibility overview, brand performance reporting, PDF exports, CSV exports, shareable online dashboards, Reddit thread analysis for AI citation gaps, and automated negative sentiment detection with domain-level source attribution inside the AI Visibility Toolkit.
Why it matters: Semrush launched Reddit analysis and negative sentiment detection in May 2026 — buyers now expect AI visibility tools to surface social threads influencing AI answers and flag negative brand framing automatically.
Semrush KB - Getting Started with the AI Visibility ToolkitPeec AI
AI search analytics, source influence metrics, BI-friendly reporting, and $29M total funding ($21M Series A)Reviewed 2026-05-17Peec's public materials and funding coverage document a $21M Series A in November 2025 on top of earlier seed funding, plus daily AI-search monitoring across major answer surfaces. As of May 2026, its public pricing emphasizes brand and agency packaging with model and credit allocation details rather than one stable universal entry tier.
Why it matters: Peec is a serious mid-market competitor with public documentation for AI-search metrics, packaging, and MCP-style access. Its packaging complexity is relevant when buyers compare simple all-in plan messaging against model- or credit-shaped pricing.
Peec AI Docs and TechCrunch Series A CoverageProfound
Enterprise GEO platform with $96M raised (Series C at $1B valuation), 10+ engine coverage, agent analytics, and content agentsReviewed 2026-05-17Profound's public materials document enterprise AI-visibility coverage across major answer surfaces, agent analytics, and prompt or conversation drill-down workflows. Separate funding coverage reports a $96M Series C in February 2026.
Why it matters: Profound is positioned as a high-end enterprise reference point in the category. The relevant buyer signal is less the exact list price and more the combination of broad engine coverage, enterprise workflow depth, and sales-led expansion.
Profound - Enterprise GEO Platform and PricingScrunch
Citation drill-down and source-level influence reviewReviewed 2026-05-16Scrunch publicly documents citation grouping by domain or URL, platform filtering, and citation-level influence analysis in its help center.
Why it matters: Answer evidence without source drill-down is weak; buyers want to inspect which domains influence mentions and citations.
Scrunch Help Center - Understanding the Citations Tab in ScrunchOtterlyAI
GEO Landing Page Creator, export-oriented reporting, and Google AI Mode/Gemini add-onsReviewed 2026-05-17Otterly's public help and pricing materials describe three plans (Lite, Standard, Premium), prompt allowances, daily tracking, exports, a GEO audit workflow, and Google AI Mode or Gemini as paid add-ons.
Why it matters: Otterly's public materials make clear that AI Mode and Gemini require add-ons, which matters when buyers compare all-engine packaging across tools.
Otterly AI Pricing and FeaturesAhrefs Brand Radar
Search-backed prompt database with free AI visibility checker and cited domain analysisReviewed 2026-05-16Ahrefs publicly provides a free no-signup AI visibility checker with mentions by platform, top 5 topics, top 5 cited domains, and top 5 cited pages. Brand Radar tracks 400M+ monthly search-backed prompts derived from real search behavior across ChatGPT, Gemini, Perplexity, Copilot, AI Overviews, AI Mode, and Grok.
Why it matters: A free checker with no signup creates a strong top-of-funnel acquisition loop. Search-backed prompts from real user behavior are more trustworthy than synthetic question sets. Cited domain and cited page analysis gives actionable source intelligence.
Ahrefs - Free AI Visibility Checker and Brand RadarHubSpot AI Search Grader
Free AEO audit plus paid monitoring with a 5-dimension scoring modelReviewed 2026-05-17HubSpot provides a free one-time AEO Grader and a paid AI Search monitoring tool. The scoring model uses five weighted dimensions: sentiment (40 pts), presence quality (20 pts), brand recognition (20 pts), share of voice (10 pts), and market position (10 pts). The paid tier adds continuous monitoring across ChatGPT, Perplexity, and Gemini with week-over-week trend tracking and competitor comparison.
Why it matters: A structured scoring model with explicit dimension weights gives buyers a concrete evaluation framework. Free-to-paid funnel with HubSpot brand trust creates high-volume acquisition that category-specific tools must compete with.
HubSpot - AEO Grader and AI Search ToolPromptEye
Multi-LLM brand visibility tracking with snapshot reporting and industry reportsReviewed 2026-05-17PromptEye tracks brand visibility, ranking position, and source reliance across GPT, Perplexity, Gemini, and DeepSeek. Claude and Grok are available through paid industry reports. The tool provides baseline audits, ongoing change tracking, and client-ready snapshot reports for agencies.
Why it matters: A clear free trial tier with prompt-limited tracking and separate paid industry reports shows that the market expects both self-serve monitoring and one-time audit products.
PromptEye - Track Your Brand Visibility in AI ModelsRank Prompt
AI visibility scoring with prompt discovery, citation tracking, and agent modeReviewed 2026-05-17Rank Prompt monitors visibility across ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini, and Grok with 0-100% visibility scores. The platform includes competitor mention tracking, citation source analysis, AI Content Studio for content generation, scheduled reporting with email alerts, and a natural-language Agent Mode for querying visibility trends.
Why it matters: Agent Mode for natural-language visibility queries and integrated content generation show the market shifting from dashboards to conversational AI workflows that close the measurement-to-action loop.
Rank Prompt - AI Visibility Monitoring PlatformSurfaced
13-model AI visibility monitoring with AEO Score and content recommendationsReviewed 2026-05-17Surfaced monitors 13 AI models including ChatGPT, Perplexity, Gemini, Claude, Grok, Meta AI, and DeepSeek with daily automated scans. The platform provides a proprietary AEO Score (0-100) benchmarking visibility, accuracy, sentiment, and competitive position. It includes competitor intelligence, AI-generated content blueprints, citation analytics, and weekly executive reports.
Why it matters: Tracking 13 AI models with a standardized AEO Score and content blueprints shows the bar rising for breadth of coverage and actionability in the AI visibility category.
Surfaced - AI Answer Engine Optimization PlatformPromptwatch
GEO platform with citation-optimized content generation and AI traffic attributionReviewed 2026-05-22Promptwatch tracks brand mentions across 10+ AI engines with daily refreshes, offers answer gap analysis showing competitor-owned prompts, and includes a built-in writing agent that creates citation-optimized articles based on 880M+ analyzed citations. The platform connects AI visibility signals to actual site traffic attribution.
Why it matters: Bundling citation-optimized content generation with visibility monitoring closes the measurement-to-action gap. AI traffic attribution connects visibility changes to business outcomes beyond vanity scores.
Promptwatch - GEO Platform for AI Search VisibilityQwairy
Complete GEO platform with 6 integrated modules, AI crawler analytics, and ROI attributionReviewed 2026-05-17Qwairy offers Cockpit (dashboard), Monitor, Act, Analyze, Optimize, and Measure modules covering 10+ AI engines with no per-provider surcharges. Includes AI crawler analytics, referrer tracking, ROI attribution, multi-locale monitoring, and REST API plus MCP integration. 40+ features across all modules.
Why it matters: Qwairy's six-module structure with ROI attribution and crawler analytics shows the market expects full-stack platforms that connect monitoring to measurable business outcomes.
Qwairy Features - Complete GEO PlatformAthenaHQ
Enterprise AI visibility with dynamic crawler management, citation engine, prompt volume estimation, and credit-based pricingReviewed 2026-05-17AthenaHQ monitors 8+ AI platforms with real-time sentiment intelligence, prompt volume estimation, and dynamic crawler-management positioning. Public materials describe self-serve and enterprise packaging built around credits and analytics integrations.
Why it matters: AthenaHQ's credit-based packaging makes actual cost less obvious from a single headline price. Its crawler-management and analytics-integration positioning shows the market moving toward platforms that connect AI visibility with traditional analytics.
AthenaHQ - Action on AI SearchWritesonic
Full-stack GEO+SEO platform with ChatGPT Shopping visibility and AI traffic analyticsReviewed 2026-05-17Writesonic combines AI search tracking across major answer surfaces with traditional SEO tooling, citation-source identification, shopping visibility, sentiment analysis, and an integrated SEO content agent.
Why it matters: Writesonic's bundling of GEO monitoring with full SEO content generation at $249/month sets a price-value benchmark for platforms offering both monitoring and content creation.
Writesonic GEO PlatformSemrush AI Visibility Toolkit
Enterprise AI Optimization with Reddit analysis, negative sentiment detection, 261M+ prompt database, and multi-model visibilityReviewed 2026-05-17Semrush launched Enterprise AI Optimization (AIO) automations in May 2026 adding Reddit Analysis (identify threads where competitors are cited but your brand is absent) and Negative Sentiment Analysis (surface domains contributing to negative brand perception). The core toolkit tracks visibility across ChatGPT, Gemini, Google AI Mode, AI Overviews, and Perplexity with AI Visibility Scores, brand performance, competitor research, and prompt research from a 261M+ prompt database across 15 regional databases. Their 248K Reddit post study confirmed Reddit is the #1 cited domain on Perplexity (4% share) and #3 on Google AI Mode (9% share).
Why it matters: Semrush's 261M+ prompt database, Reddit analysis, and negative sentiment detection set the enterprise bar. Their 248K-post Reddit study is the strongest public evidence linking social discussion to AI citation outcomes. Available standalone or with Semrush One subscription.
Semrush - Enterprise AI Optimization New FeaturesFoglift
Daily-to-hourly AI brand monitoring with position tracking, sentiment analysis, webhook alerts, and planned AI content writerReviewed 2026-05-17Foglift monitors 5 AI engines (ChatGPT, Perplexity, Google AI Overview, Gemini, Claude) with daily to hourly frequency depending on tier. Features include visibility score percentage, citation URL tracking, position tracking (1st/2nd/3rd in responses), sentiment analysis, prompt-level breakdown, weekly digest emails, webhook alerts, and competitor comparison. 2026 roadmap includes browser-based GEO queries (Q1), citation tracking expansion (Q2), multi-language monitoring (Q2), and AI content writer (Q2). Pricing: Launch $49/mo (daily), Growth $129/mo (twice-daily), Enterprise $299/mo (hourly).
Why it matters: Foglift's hourly monitoring cadence is the fastest in the market — no other competitor offers sub-daily refresh. Their planned multi-language support and AI content writer show the market converging on full-stack GEO workflows.
Foglift - GEO Monitor and RoadmapPeec AI
AI search analytics with multi-country monitoring, citation source analysis, sentiment scoring, Actions module, and $29M total fundingReviewed 2026-05-17Peec AI tracks brand visibility across 6+ AI engines (ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude, DeepSeek — with Grok as add-on) with daily automated tracking. Features include mention monitoring with position and sentiment scoring, citation source analysis, competitive benchmarking, multi-country monitoring, and an Actions module. $21M Series A (Nov 2025, led by Singular) + seed = $29.1M total. 1,300+ brands, $4M+ ARR, 300+ new customers/month. Valuation above $100M. As of May 2026, public pricing emphasizes brand or agency packaging plus credits and add-ons rather than one stable universal starter tier. NYC sales office planned Q2 2026.
Why it matters: Peec's $29M funding and 1,300+ customer base make it the second-most funded mid-market AI visibility tool. Extra fees for Claude/Gemini and credit-model packaging create cost uncertainty that full-access platforms can exploit. NYC expansion signals aggressive US market push.
Peec AI - AI Search Analytics and TechCrunch Series AProfound
Enterprise GEO platform with $96M total funding at $1B valuation, AI-powered content agents, crawler analytics, and Fortune 500 logosReviewed 2026-05-17Profound raised $96M total through Series C at a $1B valuation (Feb 2026). Tracks 10+ AI engines with prompt volumes from opted-in user panels, answer engine insights, citation share analysis, and AI-powered content agents generating briefs and article drafts. Enterprise tier includes Agent Analytics for crawler tracking, SOC 2 Type II compliance, SSO, and API access. Ranked #34 on G2's Top 50 AI Products of 2026. Serves ~10% of Fortune 500.
Why it matters: Profound's $96M raise at a $1B valuation makes it the highest-valued pure-play AI visibility company. Their 10% Fortune 500 penetration and G2 #34 ranking set the enterprise credibility bar.
Profound - Enterprise GEO PlatformSurva.ai
AI visibility tracking with auto-generated content, direct CMS publishing, and tiered prompt/article plansReviewed 2026-05-17Surva.ai monitors ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews with daily scans. Features include one-click AI-optimized article generation, direct CMS publishing (WordPress, Webflow), competitor gap analysis, citation tracking, GEO content optimization, AI crawler logs, and Slack/Teams integrations. Pricing materials reviewed in May 2026 list Starter, Growth, and Business tiers with prompt/article capacity and API access on higher tiers.
Why it matters: Surva.ai's direct CMS publishing to WordPress and Webflow raises the implementation bar for monitoring tools. Their bundled article generation per plan creates a clear content creation value proposition.
Surva.ai - AI Visibility Tracking PlatformSEOmonitor
Unified SEO + AI search tracking from existing keyword lists with 50K+ prompt variations per keywordReviewed 2026-05-17SEOmonitor uses existing keyword lists (not separate prompts) to automatically generate 50,000+ prompt variations per keyword across ChatGPT, Gemini, and Perplexity. Tracks AI Search Presence (% of search volume mentioned), AI Search Cited (% cited as source), Citation Rank, Context Analysis, and Sentiment. March 2026 update added LLM Switcher for real-time model comparison. Builds independent historical data per model.
Why it matters: SEOmonitor's keyword-to-prompt approach eliminates the prompt setup barrier — existing SEO workflows extend directly to AI visibility. 50K+ prompt variations per keyword creates comprehensive coverage from minimal user input.
SEOmonitor - AI Search Tracking SoftwareSona
LLM-native competitor analysis with 17-check AI visibility audit and structured benchmarking frameworkReviewed 2026-05-17Sona provides AI visibility tracking across ChatGPT, Perplexity, Claude, and Google AI Overviews with competitor Share of Voice calculation. Recommends 50-100 query test suites organized by buyer journey stage. Free AI Visibility audit covers 17 technical checks (crawlability, schema, structure, freshness) in under 30 seconds. Competitive benchmark of 20%+ Share of Voice. Research finding: brands mentioned in first two sentences are 5x more likely to enter consideration.
Why it matters: Sona's structured benchmarking framework (50-100 queries by journey stage, 20% SoV target) and 17-check audit create a repeatable methodology that buyers find credible.
Sona - LLM Competitor AnalysisTargetlytics
AI brand ranking tracker with daily monitoring across ChatGPT, Perplexity, and Google AI OverviewsReviewed 2026-05-17Targetlytics tracks AI brand visibility with daily monitoring across ChatGPT, Perplexity, and Google AI Overviews. Features include brand mention tracking, competitor comparison, citation source analysis, and weekly email digests. Pricing starts at $49/mo for 50 prompts.
Why it matters: Targetlytics' affordable entry point ($49/mo) and daily monitoring cadence appeal to SMBs. Their focus on three core platforms keeps the product simple but limits multi-engine coverage.
Targetlytics - AI Brand Ranking TrackerSE Ranking AI Visibility Tracker
Hybrid SEO + AI visibility tracking with SERP-integrated monitoring and content optimizationReviewed 2026-05-17SE Ranking added AI Visibility Tracker alongside its established SEO toolkit. Monitors brand mentions and citations across ChatGPT, Perplexity, and Google AI Overviews. Integrates AI visibility data with traditional SERP tracking for a unified SEO + AI view. Pricing starts at $129/mo with a 14-day free trial.
Why it matters: SE Ranking's hybrid approach bundling traditional SERP tracking with AI visibility appeals to teams already using SEO tools. The 14-day trial removes adoption friction.
SE Ranking - AI Visibility TrackerTrakkr AI
SMB-focused AI visibility monitoring with competitive benchmarking and weekly reportsReviewed 2026-05-17Trakkr AI offers AI brand visibility monitoring targeted at SMBs. Tracks brand mentions across ChatGPT, Gemini, Perplexity, and AI Overviews with automated weekly reports, competitor benchmarking, and citation source analysis. 14-day free trial. Rated 4.7/5 by DemandSage.
Why it matters: At $79/mo, Trakkr fills the affordable SMB gap between free checkers and enterprise platforms. Their 4.7/5 rating suggests strong user satisfaction for the price point.
Trakkr AI - SMB AI Brand MonitoringAlertmouse
Real-time AI visibility alerts with free tier and lightweight monitoringReviewed 2026-05-17Alertmouse provides real-time monitoring alerts for AI search visibility changes. Offers a free plan with basic monitoring and paid tiers at $120/year. Focuses on alert-first workflows rather than comprehensive dashboards.
Why it matters: Alertmouse's free tier and alert-first approach appeals to teams wanting lightweight monitoring without dashboard overhead. At $120/year, it's the most affordable paid option in the market.
Alertmouse - Real-time AI Visibility AlertsGetMentions AI
AI visibility monitoring + managed brand placement execution across 192K+ partner websitesReviewed 2026-05-19GetMentions AI launched in April 2026 as an AI visibility platform combining analytics with execution. Tracks brand appearance across ChatGPT, Gemini, Google AI Mode, and Perplexity. Offers managed execution with page-level insertions and domain-level placements across 192,000+ partner websites. Pricing: Starter $85/mo (50 prompts), Growth $155/mo (100 prompts), Pro $289/mo (200 prompts), Scale $479/mo (350 prompts). Weekly refresh at lower tiers; daily at higher tiers.
Why it matters: GetMentions is the first platform to combine monitoring with managed execution, but execution means paid placements — not organic citability improvement. This is a fundamentally different value proposition from organic visibility optimization.
GetMentions AI pricing and launch announcementMeltwater GenAI Lens
Enterprise AI brand monitoring with AI-powered recommendations, LLM-generated reporting, and journalist source attributionReviewed 2026-05-19Meltwater GenAI Lens monitors brand presence across ChatGPT, Google AI Overviews, Gemini, Claude, Perplexity, Grok, and DeepSeek with 48-hour data refresh. Mid-year 2026 release added AI-powered recommendations and LLM-generated branded reporting. Source attribution identifies high-authority websites and journalists that AI models cite. Trusted by PR, communications, and marketing teams across 27,000+ organizations.
Why it matters: Meltwater's 27,000+ organization distribution is massive but serves PR/comms teams, not SEO or content marketing. 48-hour refresh is slower than daily monitoring competitors. Enterprise-only pricing excludes SMBs and agencies.
Meltwater GenAI Lens product page and mid-year 2026 releaseBrandlight
Enterprise AI visibility command center with technical crawler analysis, publisher intelligence, and cross-brand ROI planningReviewed 2026-05-21Brandlight publicly positions its platform around AI visibility, attribution, competitive intelligence, content optimization, publisher performance, technical crawl analysis, and enterprise command-center reporting. Public product copy highlights visibility across AI engines, query intent and citation analysis, crawl frequency and coverage monitoring, server-log analysis, multi-region deployment, and SOC 2 Type II compliance.
Why it matters: Brandlight expands the enterprise competitive set beyond SEO-native AI visibility vendors. Its technical crawler module and publisher intelligence reinforce that buyers expect AI visibility platforms to connect answer monitoring, crawlability, partnerships, and executive reporting.
Brandlight - AI Visibility Platform for Enterprise BrandsPublic proof should include what is still weak.
A credible AI visibility platform should publish risks discovered during self-testing, not only positive feature claims. These risks are mirrored in the self-audit markdown and JSON exports for external review.
Legacy prompt-library snippets still outrank AI visibility positioning for some queries
highEvidence: Public search results still surface the /prompts listing with a legacy 'Best AI Prompts Library' snippet while the homepage describes prompts-gpt.com as an AI visibility platform.
Impact: Evaluators can misclassify prompts-gpt.com as a generic prompt library instead of an AI Search Visibility platform.
Action: Keep /, /features, /pricing, /resources, /docs, /articles, and self-audit exports internally consistent; keep canonical AI visibility positioning in llms.txt and avoid reintroducing prompt-library-first metadata.
Live rerun links are easy to treat as permanent proof
mediumEvidence: The free checker URL is public and shareable, but the output can change as providers, citations, and model behavior shift.
Impact: External stakeholders may treat mutable diagnostics as stable evidence and misread score changes as regressions.
Action: Use markdown/JSON exports and the self-audit article as the default proof artifacts in public sharing and documentation.