AirPulse vs Evertune: measurement at scale, or fixes you can verify?
Evertune runs the biggest prompt samples in the category, a statistician's approach to AI brand perception. AirPulse is an operator's approach. The right pick depends on which question you're asking.
Pick Evertune when…
Pick AirPulse when…
AirPulse and Evertune, feature by feature
| Evertune | AirPulse | |
|---|---|---|
| Engines monitored | 9 incl. Meta AI and DeepSeek: ChatGPT, AI Mode, AI Overviews, Claude, Gemini, Perplexity, Copilot | ChatGPT, Claude, Perplexity, Gemini, Copilot |
| Monitoring depth | AI Brand Index at 1M+ prompts/brand/month; SOV, sentiment, unlimited competitors; EverPanel real-user prompt panel | Daily prompt runs: citation sightings, source mix, sentiment, category rank |
| Crawler / agent analytics | No crawler-log/agent analytics beyond a GEO site audit | Agent Pulse: crawler & agent log analytics, tied to remediation |
| Content execution | Content activation, plus Strength & Opportunity URLs | Content Pulse: schema-aware authoring |
| Done-with-you remediation | No done-for-you implementation | Yes: done with you, verified by live re-audits on production |
| GSC / analytics integration | No revenue attribution | GSC integration; control-brand analysis on your own analytics |
| Evidence standard | Scale itself: largest prompt samples in category; Athenahealth, Roku, Virgin Voyages, Canada Goose, Miro | Published methodology: control groups, consistent windows, live-verified audits |
| Pricing transparency | Undisclosed/demo-gated; reported ~$3,000/mo on annual terms (third-party, as of June 2026) | Engagement-based, scoped with you up front |
| Best fit | Enterprise brands + agency holdcos (WPP) | Mid-market B2B that wants fixes shipped |
The differences that survive a demo call
The statistician and the operator
Evertune's bet is that sample size beats everything: at a million-plus prompts per brand per month, its AI Brand Index has confidence intervals nobody polling a few hundred prompts can match, and EverPanel adds real-user behavior most vendors only simulate. If you're a CMO defending brand health to a board, that rigor is the product. AirPulse polls far fewer prompts, deliberately, because our unit of work isn't the index, it's the individual answer: which engine, which source, what it said, and which fix changes it.
Aggregates don't ship fixes
Evertune's gaps are the operator's checklist: no crawler-log or agent analytics beyond a site audit, no revenue attribution, no done-for-you implementation, and an orientation toward aggregate scores over prompt-level detail. AirPulse's whole loop lives in that gap: Agent Pulse reads crawler behavior, Content Pulse drafts the schema-aware fix, our team ships it with yours, and a live re-audit confirms it landed. Newton School's Google AI mention rate went from 51.4% to 93.3% on full-run windows because five specific fixes shipped on five specific dates, that causality chain is what small-sample, high-touch measurement buys.
Numbers with dates on them
Want the answer-level detail an index can't give you?
A walkthrough on your own brand's prompts, run by the team that builds the product.
