Meteoria vs Gumshoe AI (2026): Which AI visibility tracker is worth your money?

Key Takeaways

• Meteoria is a full monitoring platform with unlimited seats, sentiment analysis, and competitor heatmaps starting at €75/month. Gumshoe AI is pay-per-report at $0.10/conversation with 3 free reports.
• LLM coverage differs: Meteoria tracks ChatGPT, Perplexity, Google AI Overview, Gemini, and Grok. Gumshoe AI covers ChatGPT, Gemini, and Perplexity only.
• Gumshoe AI has no ongoing monitoring -- you manually trigger reports when you want a snapshot. Meteoria runs prompts daily and tracks trends over time.
• Meteoria includes sentiment analysis and source tracking out of the box. Gumshoe AI focuses on visibility percentages and competitive rank.
• For one-off checks or tight budgets, Gumshoe AI's pay-as-you-go works. For ongoing brand monitoring and optimization, Meteoria's subscription makes more sense.
• Neither platform offers content gap analysis or AI writing tools -- they're monitoring-only. Tools like Promptwatch fill that gap by showing you what content to create and helping you generate it.

Overview

Meteoria

Meteoria

Track your brand visibility across ChatGPT, Perplexity, and Google AI Overview

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Meteoria is a French GEO (Generative Engine Optimization) platform built for tracking brand visibility across AI models. It runs custom prompts daily across ChatGPT, Perplexity, Google AI Overview, Gemini, and Grok, then quantifies how often your brand appears, where you rank vs competitors, and what sentiment the AI expresses. The platform targets marketing teams and agencies that need ongoing visibility monitoring with unlimited seats and projects. Pricing starts at €75/month for 25 prompts.

The interface is in French but supports multi-language prompt tracking. Meteoria emphasizes "measure, compare, optimize" -- though the optimization piece is mostly about surfacing insights, not generating content.

Gumshoe AI

Gumshoe AI

Track your brand mentions across ChatGPT, Gemini, and Perplexity

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Gumshoe AI is a lightweight AI search monitoring tool with pay-per-report pricing. You define topics, personas, and competitors, then manually trigger "report runs" that query ChatGPT, Gemini, and Perplexity. Each conversation costs $0.10 after your first 3 free reports. The platform shows brand visibility percentages, competitive rank, and which sources AI models cite.

Gumshoe AI is designed for marketers who want occasional snapshots rather than continuous monitoring. There's no daily tracking or trend analysis unless you manually run reports over time. The pricing model makes it accessible for small budgets or one-off audits.

Side-by-Side Comparison

Pricing comparison

Meteoria's pricing is subscription-based with a fixed number of prompts per month. Gumshoe AI charges per conversation -- if you run 100 conversations in a month, that's $10. If you run 1,000, it's $100. The break-even point depends on how many prompts you need.

For example: 100 prompts/month on Gumshoe AI = $10. Meteoria's 100-prompt plan is €175/month (~$190). Gumshoe AI is cheaper at low volumes. But Meteoria includes daily automated runs, sentiment analysis, and trend tracking -- features Gumshoe AI doesn't offer at any price.

LLM coverage and monitoring depth

Meteoria tracks 5 AI models: ChatGPT, Perplexity, Google AI Overview, Gemini, and Grok. Gumshoe AI covers 3: ChatGPT, Gemini, and Perplexity. Neither platform monitors Claude, Meta AI, DeepSeek, Copilot, or Mistral.

Meteoria runs your prompts daily and builds a time-series dataset. You see visibility trends over weeks and months without lifting a finger. Gumshoe AI requires you to manually trigger each report run. If you want weekly data, you have to remember to run reports every week.

This is the core difference. Meteoria is a monitoring platform. Gumshoe AI is a reporting tool.

For brands that need continuous tracking -- say, you're running a PR campaign or launching a product and want to see how AI visibility changes over time -- Meteoria's automated approach is the only option. Gumshoe AI works for one-off audits or quarterly check-ins.

Sentiment analysis and branding insights

Meteoria includes sentiment analysis in all plans. It extracts both implicit and explicit sentiment from AI responses -- how the model "feels" about your brand based on tone and word choice. This matters for brand reputation. If ChatGPT consistently describes your product as "expensive" or "complicated," you know you have a positioning problem.

Gumshoe AI doesn't offer sentiment analysis. You get visibility percentages and competitive rank, but no insight into whether the mentions are positive, neutral, or negative.

For brand managers worried about reputation in AI search, Meteoria's sentiment tracking is a clear advantage. Gumshoe AI is purely quantitative.

Competitor tracking and benchmarking

Both platforms let you track competitors. Meteoria shows competitor heatmaps -- visual grids of which brands appear for which prompts across which LLMs. You can see at a glance where you're winning and where competitors dominate.

Gumshoe AI provides competitive rank -- your position relative to competitors for each topic. It's less visual but covers the same ground.

Neither platform is dramatically better here. The difference is presentation style.

Source analysis and content strategy

Both tools surface which URLs and domains AI models cite when they mention your brand. This is useful for understanding where to publish content -- if Reddit threads or YouTube videos drive most citations, you know where to focus.

Meteoria presents source data alongside visibility scores. Gumshoe AI has a dedicated "Cited Sources" view. Functionally similar.

What's missing from both: neither platform tells you what content is missing or helps you create it. They show you the sources AI models already use, but not the gaps. If you want to know which prompts competitors rank for but you don't, or generate articles optimized for AI search, you need a platform like Promptwatch that combines monitoring with content gap analysis and AI writing tools.

Promptwatch

Track and optimize your brand visibility in AI search engines

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Persona-based tracking

Both platforms support persona-based prompts. You can define buyer personas (e.g. "CFO looking for accounting software" vs "small business owner") and see how your brand performs for each.

Meteoria's persona tracking is part of the daily automated runs. Gumshoe AI lets you configure personas when you trigger a report.

No meaningful difference here.

Ease of use and interface

Meteoria's interface is in French, which is fine if you speak French or use browser translation. The dashboard shows visibility scores, competitor heatmaps, and trend charts. It's a full-featured analytics platform with a learning curve.

Gumshoe AI's interface is simpler. You configure a report, run it, and view results. Less to learn, but also less depth. The simplicity is intentional -- it's designed for occasional use, not daily monitoring.

If you want a tool you log into once a week to check dashboards, Meteoria fits. If you want something you fire up once a quarter for a snapshot, Gumshoe AI is easier.

Optimization and actionability

Meteoria promises "measure, compare, optimize" but the optimization piece is light. The platform surfaces insights -- which prompts you're invisible for, which competitors are winning, which sources matter -- but doesn't tell you what to do about it. You still have to figure out the content strategy yourself.

Gumshoe AI mentions "AI-assisted content generation" in its pricing table but doesn't explain what that means. It's unclear if this is a real feature or vaporware.

Neither platform is built for taking action. They're monitoring dashboards. You get data, not solutions.

This is where the gap between monitoring and optimization becomes obvious. Seeing that you're invisible for 80% of prompts is useful. Knowing which specific content to create to fix that is more useful. Promptwatch's Answer Gap Analysis does exactly this -- it shows you the prompts competitors rank for but you don't, then generates content grounded in citation data to close the gap.

Multi-language and geo-targeting

Meteoria supports multi-language prompts and geo-targeting. You can track how AI models respond in French, English, German, etc., and from different regions. This matters for global brands.

Gumshoe AI doesn't mention multi-language support. Unclear if it's available.

If you need non-English tracking, Meteoria is the safer bet.

Reporting and integrations

Meteoria doesn't mention API access or integrations in its public pricing. It's a standalone platform.

Gumshoe AI offers "storage integrations" (unclear what this means) and custom integrations/APIs at the Enterprise tier. If you need to pipe data into your own BI tools, Gumshoe AI's Enterprise plan might support it.

For most users, this won't matter. Both platforms are designed to be used in-app.

Pros and cons

Meteoria pros

• Daily automated monitoring -- set it and forget it
• Sentiment analysis included in all plans
• Tracks 5 LLMs including Google AI Overview and Grok
• Unlimited seats and projects
• Multi-language and geo-targeting support
• Competitor heatmaps for visual benchmarking

Meteoria cons

• Subscription pricing can get expensive at scale (€300+/mo for 200+ prompts)
• Interface in French (though multi-language prompts work)
• No content gap analysis or writing tools
• Optimization recommendations are vague

Gumshoe AI pros

• Pay-per-report pricing is cheap for low volumes ($0.10/conversation)
• 3 free reports to try before you buy
• Simple interface with minimal learning curve
• Good for one-off audits or quarterly check-ins
• Competitive rank and cited sources included

Gumshoe AI cons

• No automated monitoring -- you have to manually run reports
• Only 3 LLMs (ChatGPT, Gemini, Perplexity)
• No sentiment analysis
• No trend tracking unless you run reports repeatedly
• "AI-assisted content generation" feature is unclear/unproven
• Costs add up fast at high volumes (1,000 conversations = $100)

Who should pick which tool

Pick Meteoria if:

• You need continuous, automated monitoring of AI visibility
• Sentiment analysis matters for your brand reputation strategy
• You want to track Google AI Overview and Grok in addition to ChatGPT/Perplexity
• You're running ongoing campaigns and need trend data over time
• You have a team that will use unlimited seats
• You're comfortable with a €75+/month subscription

Pick Gumshoe AI if:

• You only need occasional snapshots (quarterly audits, one-off checks)
• Your budget is tight and you want to pay only when you use it
• You're fine with manually triggering reports instead of automated daily runs
• You don't need sentiment analysis or advanced branding insights
• You're tracking fewer than 100 prompts/month (where pay-per-use is cheaper)
• You want a simple tool with no learning curve

Consider Promptwatch if:

• You want to go beyond monitoring and actually improve your AI visibility
• You need content gap analysis to see which prompts you're missing
• You want AI-generated articles optimized for citation in ChatGPT, Claude, Perplexity, etc.
• You need crawler logs to see how AI models are indexing your site
• You want to track 10+ LLMs including Claude, Meta AI, DeepSeek, Copilot, and Mistral
• You need the full action loop: find gaps, create content, track results

Final verdict

Meteoria and Gumshoe AI solve different problems. Meteoria is a full monitoring platform for teams that need ongoing visibility tracking, sentiment analysis, and trend data. Gumshoe AI is a pay-per-report tool for occasional audits and tight budgets.

If you're serious about AI search visibility and want to track it continuously, Meteoria's subscription model makes sense. The daily automated runs, sentiment analysis, and 5-LLM coverage justify the €75+/month cost.

If you just want a quarterly check-in or a one-off audit, Gumshoe AI's $0.10/conversation pricing is hard to beat. But you're trading cost savings for manual work and missing features.

Neither platform helps you fix the problems they surface. They show you where you're invisible, but not what to do about it. For that, you need a platform that combines monitoring with content optimization -- something that tells you which articles to write and helps you write them.