AI Search Visibility Platform

See how AI answers describe your brand.

Track when ChatGPT, Claude, Gemini, Perplexity, and Grok mention your brand, cite your sources, recommend competitors, or leave you out entirely.

Free instant check — no signup or credit card required.

12 engines monitored23 visibility metrics
ChatGPTGoogle AIGoogle AI ModePerplexityGoogle GeminiAnthropic Claude

Evidence before score

Many tools show an aggregate score first. Prompts-GPT.com keeps answer excerpts, citations, and source context visible.

Prompt-to-monitor handoff

Prompt discovery, Prompt Studio, public checker, and saved monitors share the same buyer-question workflow.

Agent orchestration for execution

The CLI turns evidence into local agent runs, parallel reviews, pipelines, evals, and worktree diffs.

12

Configured engines

5

Core report surfaces

6

Free tools

23

Visibility metrics

Product proof

Teams need evidence they can explain fast.

The strongest product pattern is consistency: one place to see the answer, the cited sources, the competitor pressure, and the next action without opening five tools.

12

Configured engines

Pulled from the current product configuration instead of testimonials or unverifiable review counts.

5

Core report surfaces

Pulled from the current product configuration instead of testimonials or unverifiable review counts.

6

Free tools

Pulled from the current product configuration instead of testimonials or unverifiable review counts.

Why teams switch

Most AI visibility tools stop at the dashboard.

Buyers now compare platforms across three tiers: monitoring-only tools, optimization layers, and enterprise suites. The wedge for prompts-gpt.com is simple: make the monitoring useful enough to ship fixes, not just report them.

Tier 1: Monitoring-only

Fast visibility snapshots, but limited help turning findings into content or implementation work.

Tier 2: Optimization platforms

Add content recommendations and audits, but often stop before implementation and proof workflows.

Tier 3: Enterprise suites

Broad reporting and large data layers, but usually expensive and harder to operationalize across smaller teams.

Monitor

Monitor with evidence

Track 23 metrics across 12 configured engines with prompt-level answer evidence, citations, and competitor context.

Optimize

Optimize with evidence

Turn misses into source fixes, FAQ updates, comparison pages, schema improvements, and prompt-gap prioritization.

Implement

Implement with evidence

Use content briefs, project workflows, free tools, and agent workflows to move from findings into shipped changes.

Orchestrate

Orchestrate with evidence

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 conversion multiplier.

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 launched MCP integration (33 read + 17 write tools) in April 2026 for all paid plans. Qwairy offers REST API + MCP. 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.

AboutWhat is Prompts-GPT.com?

Prompts-GPT.com is an AI search visibility platform that monitors how brands appear in AI-generated answers across ChatGPT, Claude, Gemini, Perplexity, and Grok. It tracks 23 visibility metrics including brand mention rate, citation share, competitor displacement, sentiment analysis, citation velocity, and prompt-space occupancy. The platform combines monitoring, optimization, implementation, and local agent orchestration so missed mentions can become content briefs, schema fixes, outreach targets, and verified implementation runs.

Category: AI Search visibility platform — monitoring + optimization + implementation

Engines: ChatGPT, Claude, Gemini, Perplexity, Grok + 7 more (12 total, no per-engine surcharges)

Free tools: 6 tools, no signup required

Pricing: Free tier plus Starter $99/mo, Pro $249/mo, Agency $579/mo.

Market context: AEO and GEO tooling is an emerging high-growth category; research quality varies, so the product emphasizes prompt-level evidence instead of unsourced guarantees.

Unique: CLI agent orchestration (parallel, pipeline, eval modes), self-evaluation scoring, cross-OS support

The AI visibility gap

Traditional SEO rankings don't guarantee AI citations.

15–48%

Public trackers show wide variance in Google AI Overview prevalence. Treat query-set and industry ranges as directional, not universal.

12

Configured answer engines are documented in the live product model and should be monitored with plan-specific engine caps.

5

Starter plan coverage begins with five core recurring report surfaces: ChatGPT, Google AI, Gemini, Perplexity, and Grok.

23

Documented visibility metrics are measured from saved answer evidence rather than from a single vanity score.

6

No-signup free tools give teams a public baseline before they commit to recurring monitoring.

25+

Funded and bootstrapped AI visibility vendors now compete across monitoring, optimization, and enterprise-suite categories.

The questions that matter

Know what AI says about your brand — before anyone else does.

Every day, people ask AI assistants about your category, your competitors, and your products. The answers they get shape perception and decisions before anyone visits your website.

Is AI recommending your brand?

Find out when ChatGPT, Claude, or Perplexity mention, rank, cite, or skip your brand across the prompts that define your category.

Which sources does AI trust?

Discover the pages, reviews, directories, and competitor URLs that shape how AI engines answer questions about your category.

What prompts matter for your market?

Map the comparison, alternatives, recommendation, and high-intent questions where AI visibility determines who gets mentioned.

What should you fix first?

Get a prioritized action queue — missing mentions become comparison pages, schema fixes, outreach targets, and content briefs.

What gets tracked

Every signal behind AI-driven brand discovery.

Go beyond vanity scores. Track the prompt asked, the answer generated, the competitors mentioned, the sources cited, and the specific actions that will improve your next AI 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

Connect AI citations to site visits and conversions. Treat AI referral lift as a measured analytics workflow because conversion benchmarks vary by study, industry, and attribution method.

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.

Beyond monitoring

Most tools show the problem. We help you fix it.

Most AI visibility tools hit a monitoring ceiling — they show accurate data but leave teams without clear next steps.

Monitoring-only tools

Show you're invisible in AI answers — then leave you with a dashboard and no action plan. Teams hit a ceiling where data is accurate but next steps are unclear.

Prompts-GPT.com

Turns every missed mention into a specific content brief, schema fix, comparison page, or outreach target. Monitoring + optimization + implementation in one workflow.

Step 1

Monitor

Track brand mentions, citations, and competitors across AI answers — the table stakes every tool offers.

Step 2

Optimize

Score content for citation readiness, identify prompt gaps, and prioritize fixes based on competitive evidence.

Step 3

Implement

Generate content briefs, FAQ structures, schema recommendations, and outreach targets directly from answer gaps.

How it works

From blind spots to action items in three steps.

A visibility score alone doesn't help your team. You need to know exactly which prompts matter, what evidence exists, and what to fix next.

01

Map your prompt landscape

Identify the category, comparison, alternative, and intent-driven prompts that matter most for your brand's AI visibility.

02

Collect answer evidence

Run recurring checks across AI engines and capture exact mentions, rankings, citations, and competitor context from every answer.

03

Prioritize and fix

Turn gaps into a prioritized action queue — comparison pages, schema fixes, llms.txt updates, media outreach, and content briefs.

AI Visibility metrics

Metrics built for AI search, not traditional SEO.

Track what's actually in the AI answer — mentions, citations, competitors, sentiment, and source quality across every engine.

AI Visibility Score

Baseline

A rollup score for whether the brand is mentioned, cited, recommended, and framed well across monitored prompts.

Brand Mention Rate

Presence

How often the brand appears in AI visibility answers across the tracked prompt set.

Answer Position

Presence

Average placement when the answer lists vendors, products, agencies, or recommended sources.

AI Share of Voice

Competition

The brand's share of answer mentions compared with named competitors in the same prompt cluster, weighted by prompt intent and audience reach.

Narrative Drivers

Message

Top cited domains and specific prompts shaping the brand's story, revealing influential publishers for outreach and the exact queries driving conversation.

Source intelligence

Understand why AI cites a competitor instead of you.

AI answers don't just pick brands randomly. They're shaped by owned pages, third-party reviews, community discussions, and competitor content. Understanding these sources is the key to improving your AI visibility.

Your pages

Product, docs, pricing, support, and comparison URLs you control.

Third-party proof

Reviews, directories, news, podcasts, and partner pages that validate your brand.

Community sources

Forums, social discussions, videos, and practitioner guides where your audience engages.

Competitor pages

Alternative, feature, pricing, and category pages that shape how AI contrasts your brand.

Example action queue

Prioritized fixes from real evidence

Content gapCreate competitor comparison page targeting missing prompts
Schema fixAdd FAQ schema to product category pages for richer AI answers
Discovery filePublish llms.txt with canonical source list for AI crawlers
OutreachPitch top review directory that competitors are cited from

Unique to Prompts-GPT

Agent orchestration via CLI.

Race agents in parallel, chain pipelines, or run eval scoring from your terminal. Competitive research found strong monitoring and recommendation features across Otterly, Peec, Profound, Semrush, Ahrefs, and Searchable, but not a visibility-focused CLI that turns answer gaps into local parallel, pipeline, and eval runs.

Quick start

npx prompts-gpt orchestrate --mode parallel
parallel

Parallel execution

Race multiple AI agents simultaneously, score results, and pick the best output. Ideal for A/B testing visibility fixes across different models.

npx prompts-gpt orchestrate --mode parallel
pipeline

Pipeline chaining

Chain agents sequentially with context passing. Each phase builds on the previous output — audit, then optimize, then verify.

npx prompts-gpt orchestrate --mode pipeline
eval

Eval scoring

Run and evaluate with configurable criteria. Score agent outputs against visibility benchmarks, citation readiness, and content quality.

npx prompts-gpt orchestrate --mode eval

The attribution gap

AI traffic is invisible in your analytics.

AI referrals are still hard to measure because platforms, browsers, and analytics tools do not preserve attribution consistently. Treat visibility monitoring as upstream evidence: what answers appeared, which sources were cited, and which prompts deserve conversion analysis.

Prompt evidence

before traffic evidence

Know which buyer questions mention you before trying to explain downstream attribution.

Source evidence

before conversion claims

Separate owned, competitor, review, community, and media sources so teams know what shaped the answer.

Repeat checks

before trend claims

Run the same prompt set over time so movement is not confused with one-off model variance.

UTM hygiene

for known campaigns

Pair AI visibility monitoring with clean landing pages, UTMs, and assisted-conversion reporting where possible.

Dark traffic review

for analytics teams

Review direct and referral traffic spikes against visibility scans instead of assuming attribution is complete.

Revenue context

for executives

Use AI visibility as an influence signal that should be connected to CRM and analytics data, not as a standalone ROI promise.

Why AI visibility still matters

AI referral traffic is growing, but exact conversion multipliers are not stable enough for homepage promises.

Current 2026 tracker coverage points in the same direction: AI referrals are rising and often arrive with stronger intent than broad organic traffic, but platform-by-platform conversion rates vary materially by source, attribution setup, and industry.

Rising

Signal

Independent referral trackers and vendor benchmark coverage both show AI-driven visits increasing in 2026.

Directional

Signal

Use your own analytics stack to validate conversion impact by engine, landing page, and prompt group.

Measured

Signal

Treat visibility scans as upstream evidence and connect them to UTMs, CRM data, and assisted-conversion reporting before making ROI claims.

Sources reviewed May 20, 2026: Google Search Central guidance, Statcounter referral reporting, BrightEdge Q1 2026 referral coverage, and Searchless cross-platform conversion analysis.

Platform features

Built for teams that need more than a dashboard.

Most AI monitoring tools stop at showing you a score. We give you the operating layer — prompt evidence, citation intelligence, trend history, exports, and free tools for the whole team.

Prompt coverage mapping

Map every category, comparison, alternative, and high-intent prompt across the AI engines that matter for your brand.

Presence scoring

Measure brand mentions, answer rank, share of answer, sentiment, and competitive pressure from actual AI-generated answers.

Citation intelligence

See exactly which pages, reviews, forums, and directories AI engines cite — and which ones they trust for your competitors.

Crawler evidence

Connect AI crawler visits with answer mentions and citation patterns to understand what influences your discoverability.

Action briefs

Turn every gap into a specific action — comparison pages, FAQ updates, schema fixes, source outreach, and editorial briefs.

Competitor tracking

See which competitors get mentioned alongside you, which prompts they dominate, and where you can close the gap.

Get started in 3 steps

1. Free check

Run an instant AI visibility check for any domain — no signup required, with six public free tools available today.

2. Create a project

Set up your brand, competitors, and target prompts to start tracking. Auto-detect industry and generate relevant prompts in under 60 seconds.

3. Monitor & improve

Get recurring reports, action briefs, and alerts with evidence-based priorities. Unlike monitoring-only tools, every gap becomes a specific fix.

6 free tools, no signup required

Most competitors offer 0–1 free tools. Prompts-GPT.com keeps 6 entry tools available without signup: visibility checks, market research, GEO scoring, prompt generation, llms.txt drafting, and Codex launching.

Try Free Tools

Market context

How the AI visibility market is evolving in 2026

AI search is now a serious discovery channel, but exact adoption, conversion, funding, and prompt-database claims vary by source. The practical buyer question is simpler: which answers mention you, which sources are cited, and what implementation work can improve the next run?

AI Mode

Search

Google AI Mode and AI Overviews make generated answers part of mainstream search behavior.

Prompt tracking

Monitoring

Semrush, Peec, Otterly, Ahrefs, Profound, and Searchable all show that prompt-level visibility is now table stakes.

Sources

Evidence

The cited-domain layer matters because answers are shaped by owned pages, reviews, communities, media, and competitor content.

Actions

Execution

The durable gap is moving from findings into briefs, schema, comparison pages, source outreach, and validation.

Agents

Orchestration

Multi-agent coding tools are expanding quickly; visibility workflows should use them to implement and evaluate fixes.

Attribution

Measurement

AI referral conversion research is promising but variable, so visibility reporting should connect to analytics instead of replacing it.

GEO research (2026)

The signals that earn AI citations.

Research across thousands of AI citation events identified the content patterns and technical signals that determine whether AI engines cite your content. Our GEO Content Scorer and content briefs are built on this evidence.

High

Entity clarity

Recurring AEO and GEO guidance pattern

High

Answer-ready structure

GEO research and practitioner audits

High

Fresh citations

AI citation and source-quality studies

High

Third-party proof

Answer engine source analysis

Medium

Schema and metadata

Technical SEO and AEO guidance

Medium

Owned canonical pages

Brand source hygiene audits

Medium

Community source coverage

Reddit and forum citation discussions

Emerging

llms.txt and source maps

AI-readable discovery file guidance

Your competitors are already in the answer. Are you?

Run a free AI visibility check and see exactly how AI engines describe your brand today.

Platform presence across AI engines

ChatGPT

Mention rank

Track recommendations, alternative comparisons, and category mentions.

Claude

Positioning

Monitor research-style evaluations and reasoning-led positioning.

Gemini

Source fit

See Google-connected summaries, entity clarity, and source-backed discovery.

Perplexity

Citations

Analyze citation-led answers, source visibility, and competitor mentions.

Grok

Recency

Track real-time web synthesis, trending awareness, and news-driven recommendations.

FAQ

Everything you need to know about AI visibility.

What is AI visibility?

AI visibility is how your brand appears in AI-generated answers. When someone asks ChatGPT, Claude, or Perplexity about your category, AI visibility determines whether you get mentioned, recommended, or left out entirely.

Why does AI visibility matter for my brand?

More people are using AI assistants to research products, compare options, and make decisions. If AI doesn't mention your brand in category and comparison prompts, you're invisible to a growing share of your audience.

Which AI platforms should I monitor?

Focus on the AI engines your audience uses most. ChatGPT, Claude, Gemini, Perplexity, and Grok each generate different answers from different sources — tracking all of them reveals the full picture.

How is AI visibility different from SEO?

SEO tracks search rankings and organic traffic. AI visibility tracks the generated answer itself — whether you're mentioned, what competitors appear alongside you, which sources get cited, and how sentiment shapes recommendations.

Can I improve my AI visibility?

Yes. AI answers are shaped by the sources they cite — your website, reviews, directories, forums, and media coverage. By strengthening these sources and filling content gaps, you can influence how AI describes and recommends your brand.

How do I get started?

Run a free visibility check with your domain — no signup required. You'll see a live snapshot of how AI engines currently describe your brand, which sources they cite, and where the biggest opportunities are.

Research-backed positioning

What the competitive audit changed.

The category is no longer just dashboards. Current leaders cover prompt tracking, share of voice, sentiment, sources, exports, and recommendations. Prompts-GPT.com should win by proving the next layer: implementation and orchestration from the same evidence.