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Mentionable vs AirOps (2026): Which GEO tool fits your budget?

A detailed comparison of Mentionable and AirOps covering pricing, AI visibility tracking, content workflows, integrations, and real user complaints, to help you pick the right GEO tool for 2026.

Key takeaways

  • Mentionable is a tracking-first tool: daily scans across 7-8 LLMs, transparent credit pricing, and a simple dashboard. AirOps is a content-production platform with AI visibility bolted on as one feature among many.
  • Price gap is massive. Mentionable tops out at €299/mo for unlimited agency use. AirOps' real-world paid entry point is closer to $200/mo, and the next tier jumps to roughly $2,000/mo with, as more than one reviewer puts it, "no viable middle ground."
  • AirOps can publish directly into your CMS (Webflow, WordPress, HubSpot CMS, Contentful, Ghost). Mentionable writes the missing page for you but you have to paste it in yourself.
  • Mentionable's Claude scans cost 15 credits versus 1 credit for every other engine, a hidden cost that can eat your monthly allotment fast if you track Claude heavily.
  • AirOps holds a strong 4.7/5 on G2, but the same review base flags a steep learning curve, confusing credit accounting, and an average 8-month time-to-ROI. Mentionable has no G2 presence yet since it's newer and smaller.
  • If you need enterprise-scale content workflows and can budget $2k+/mo, AirOps wins. If you want affordable, transparent daily GEO tracking without a workflow-builder learning curve, Mentionable wins.

Overview

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Mentionable

Credit-free daily GEO tracking across eight LLMs
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Mentionable tracks whether ChatGPT, Claude, Perplexity, Gemini, Copilot, Google AI Mode, and Google AI Overviews cite your brand, on a daily cadence, without the usual credit-hoarding pricing model most competitors use. It shows mention rate, citation rate, which competitors are winning the prompts you're losing, and which sources those engines trust instead of you. Its standout move is generating the actual page you're missing for a given prompt, then re-scanning to check whether engines start citing it. It's built by a small team and priced like a tool built for solo consultants and small agencies, not enterprise procurement.

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AirOps

AI workflow automation for GEO
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AirOps started as a no-code AI workflow builder and has repositioned itself around "winning AI discovery." Its core mechanics are Workflows, a drag-and-drop automation builder for content pipelines, and Grids, a spreadsheet-style interface for running the same operation across hundreds of URLs at once, tied to an execution agent it calls Quill. AI visibility tracking exists inside AirOps, but multiple independent reviewers, including Profound, describe it as a secondary feature layered on top of a content-automation core rather than the product's reason for existing.

Side-by-side comparison

FeatureMentionableAirOps
Primary focusAI visibility tracking + page generationContent workflow automation + AI visibility
LLMs tracked7-8 (ChatGPT, Claude, Perplexity, Gemini, Copilot, Google AI Mode, AI Overview)"7+ Answer Engines" on Pro; ChatGPT only on Solo
Scan frequencyDaily (configurable, e.g. 3x/week)Not the product's core loop; visibility data is secondary
Free tierNo permanent free plan; 4-7 day trial, no cardFree-to-start Solo tier with ChatGPT-only insights
Entry price€79/mo~$200/mo functional entry (despite "free-to-start" marketing)
Content generationGenerates the missing page (150 credits)Full workflow-driven drafting, refreshing, internal linking, schema, FAQ generation via Grids
CMS publishingNone, manual copy-pasteNative: Webflow, WordPress, HubSpot CMS, Contentful, Ghost, Strapi
Competitor benchmarkingYes, per-engine mention counts vs named competitorsLimited/basic per third-party review
White-label / agency featuresYes, on Agency plan (€299/mo)No dedicated white-label tier found
MCP / dev integrationsYes, public MCP server (Claude Desktop, Cursor, n8n) on Pro/Agency46 listed integrations on G2 including Asana, ClickUp, Airtable
Learning curveLow, dashboard-drivenSteep, per G2 reviewers on the Workflow builder
Third-party review presenceNone on G2/Capterra yet; 4.2/5 on Salesdorado4.7/5 on G2 (134 reviews), though 21+ flag pricing as too steep for ROI

Pricing and credit structure

Head-to-head verdict

Mentionable's pricing is transparent and linear: three plans, clear prompt and credit caps, a per-scan overage rate you can watch in real time. AirOps' pricing looks cheap on the surface ("free-to-start") but the functional jump from Solo to Pro is roughly 10x, and that jump is where AI visibility tracking, brand voice training, and multi-engine coverage actually unlock. If your budget caps out around $200-300/mo, Mentionable gives you more usable functionality at that price than AirOps does.

PlanMentionableAirOps
Free / entryNo permanent free plan (4-7 day trial)"Free-to-start" Solo tier, ChatGPT-only, 35,000 tasks
Starter/Growth€79/mo (1 project, ≤115 prompts, 1,500 credits)~$200/mo (real-world Solo price per third-party trackers)
Mid tier€149/mo (3 projects, ≤231 prompts, 3,000 credits, MCP)No published middle tier
Top tier€299/mo (unlimited client projects, ≤385 prompts, 5,000 credits, white-label)~$1,999-2,000/mo Pro (7+ engines, 100,000 tasks, unlimited seats)
EnterpriseNot offeredCustom pricing, dedicated account manager
Overage€0.02/scan, user-set spend cap$6-9 per 1,000 tasks depending on plan

One quirk worth flagging on Mentionable: every engine costs 1 credit per scan except Claude, which costs 15. If Claude visibility matters to your brand, budget accordingly, because it will burn through your monthly allotment far faster than the other six engines combined.

Head-to-head feature deep-dive

AI visibility tracking depth

Mentionable's dashboard shows mention rate, citation rate, and a per-engine breakdown (which of the 7-8 LLMs mentioned you, in what share) alongside a ranked list of competitor brands and the specific sources those engines trust more than yours (G2, Capterra, Reddit, and your own domain, ranked by citation count). AirOps' visibility layer, per Profound's hands-on review, is comparatively shallow, with limited LLM and regional coverage that

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