Profound and AirOps both promise to help teams scale content and win in AI search. But they got to this point from opposite ends, and that difference in design philosophy determines what each tool can reliably deliver.
AirOps started as a content automation platform, but has since added AI visibility features. We conceived Profound from the ground up as an agentic marketing platform for AI search—purpose-built for Answer Engine Optimization (AEO), combining best-in-class AI visibility data with an agentic layer that acts on it.
The comparison has gotten more interesting since AirOps launched Quill, its own background agent, in 2026. Both platforms now run an agent that scans continuously and decides what needs to be done rather than waiting to be triggered. So the real question isn't which platform has an agent anymore—it's what each agent is grounded in, and what happens after it acts.
This article compares the two tools across six dimensions: content automation, LLM and regional coverage, pricing, AI visibility insights, actionable recommendations, and compliance. By the end, you'll have a clear picture of which platform best slots into your team's workflow.
For a quick side-by-side comparison between AirOps and Profound, check out the table below:
Profound vs. AirOps: Content automation and workflows
Both Profound and AirOps let you build AI-powered content workflows, but what sits underneath those workflows, and how much work it takes to get started, is where they diverge considerably.
AirOps: Quill up front, a steep learning curve underneath
At a glance
Pros:
- Quill scans continuously for content gaps and citation opportunities and surfaces them in an inbox—no one has to trigger a workflow to get started
- Visual workflow builder scales across hundreds of URLs via Grid; Power Agents package common jobs into forkable templates
- Workflow governance—technical teams can build complex workflows while non-technical users execute them without seeing the backend.
Cons:
- Steep learning curve—setup requires significant time investment before workflows run smoothly, even with AirOps Academy and embedded Copilot
- Output is rarely publish-ready; brand guidelines can be applied too rigidly, and content refreshes have been known to misplace FAQs or alter heading hierarchy
- Teams without dedicated technical resources report ROI taking too long to materialise
Quill is the front door now. It scans continuously for stale pages, competitor gaps, and prompts you should be cited for but aren't, and surfaces those in an inbox—AirOps' own materials describe it as the platform's "agent captain." Accept an opportunity and it hands off to the execution layer underneath: a visual workflow builder where steps like research, brief generation, and drafting chain into automated pipelines. The Grid feature runs those pipelines across hundreds of URLs at once, while Power Agents package multiple steps into pre-built templates for recurring jobs like content refresh and keyword research.
While the scalability is impressive, and reviewers compliment it, getting AirOps up and running takes time. The builder is hard to learn, and even with AirOps Academy cohorts and an embedded Copilot, user feedback often points to the same issue. This isn't a stale, pre-Quill complaint—G2's 2026 review data still clusters 25+ reviews around learning difficulty, with an average implementation time of roughly a month and an average time-to-ROI of about eight months. As one reviewer put it, "AirOps has a pretty steep learning curve. The initial setup wasn't easy, and getting to the point where workflows are running smoothly took a significant time investment. I felt that for teams without dedicated technical resources, the ROI just took too long."
As for content quality, it's decent, but the output isn't usually publish-ready. AirOps can follow brand guidelines too rigidly, sometimes removing negative framing that’s contextually appropriate, and content refreshes have been known to misplace FAQs or convert H2s to H3s mid-article.
Profound: An agentic layer, not just a workflow builder
At a glance
Pros:
- AIM, the first background agent built for marketers, works the data continuously and scopes the highest-impact visibility gaps into briefs before anyone builds a workflow
- Pre-built Agent templates cover the most common AEO use cases out of the box— AEO Content Refresh, FAQ Generator, Content Optimisation Suggestions—with no configuration required
- Every Agent pulls from Answer Engine Insights: citations, prompt sentiment, and real user prompt data inform generation rather than working in isolation
- Profound tracks which published content gets cited and by which LLMs, feeding that signal back into the generation engine so output improves over time
- Reviewers call it a “major unlock” for streamlining processes and describe the combination of innovation and practical utility as essential for teams managing AI presence
Cons:
- Content output still requires editorial review before publishing
Our Agents are designed for marketers to get started fast, without relying on dev support. The template library covers the most common AEO use cases out of the box, including AEO Content Refresh, FAQ Generator, Content Optimization Suggestions, and more. This means that the same "create a brief" workflow that takes significant ramp-up time in AirOps can be running in Profound in just a few minutes.
Setup speed aside, the more interesting question used to be who decides the work needs doing. That gap has narrowed: AirOps' Quill now scans on its own and surfaces opportunities without a person triggering a workflow first, much like AIM. AIM works the same way—it scans your AI search data, prompt volumes, and competitive metrics on its own, and when it finds a dropped citation or a rising topic you don't own, it scopes that into a project with a brief attached. The workflow builder is the execution layer beneath an agent that decides what to build. The differentiator now sits one level down, in what each agent is actually looking at.
AirOps has closed some of that gap. Quill, launched in 2026, scans continuously and surfaces opportunities in an inbox rather than waiting for someone to trigger a workflow—genuinely agentic behavior, not just automation. Where the platforms still diverge is the foundation each agent works from and what happens after content goes live. AIM is grounded in AEO-specific real-user-prompt data across 10+ engines; Quill works from AirOps' own visibility layer, which this comparison's own data shows trails on model coverage and regional depth. And Profound's Agent Analytics ties published content back to actual crawler and citation behavior at the CDN level—a harder, more specific feedback signal than an accept/decline click.
Reviewers appreciate the Agents feature, praising both the easy setup and speed gains. One user called it a "major unlock” for the organization to streamline processes and enhance overall output, adding that “the combination of rapid innovation and practical, high-level marketing utility makes Profound an essential asset for any organization looking to master their AI presence.”
Profound vs. AirOps: LLM and regional coverage
The AI search landscape has grown to encapsulate over half a dozen platforms, each with different citation behavior, regional usage patterns, and user demographics. Which LLMs a tool tracks determines how much of that picture you can see.
AirOps: Limited engines, US-only data
At a glance
Pros:
- Covers ChatGPT, Google Gemini, Google AI Mode, and Perplexity on Pro and Enterprise plans
Cons:
- Claude, Meta AI, Grok, DeepSeek, and Microsoft Copilot aren’t covered at any tier
- Regional data is US-only on Solo and Pro; international coverage requires an Enterprise contract
- Prompts run via API rather than front-end browsers, producing a less accurate simulation of what real users see
AirOps’ Solo plan tracks only ChatGPT. Moving up to Pro or Enterprise adds Google Gemini, Google AI Mode, and Perplexity—and that's the ceiling. Claude, Meta AI, Grok, DeepSeek, and Microsoft Copilot aren’t covered, so for brands that need to understand how they’re represented across the full AI ecosystem, that’s a significant blind spot.
Regional coverage is similarly constrained. Insights are US-only unless you’re on an Enterprise contract, which means international brands, or US brands with global audiences, may be working with an incomplete picture. AirOps also runs its prompts through API calls rather than front-end browsers, which produces a less accurate simulation of what real users see when they engage with AI engines.
Profound: 10+ answer engines, global coverage
At a glance
Pros:
- 10+ answer engines tracked out of the box: ChatGPT, Claude, Perplexity, Google AI Overviews, Google Gemini, Google AI Mode, Microsoft Copilot, Grok, Meta AI, and DeepSeek
- New engines added quickly as the market evolves
- 50+ countries and 15+ languages available from the entry-level plan
- Prompts run daily through front-end browsers, reflecting real user experience in local context rather than API approximations
Cons:
- Starter plan tracks 50 prompts on ChatGPT only
Profound tracks all 10 major answer engines out of the box: ChatGPT, Claude, Perplexity, Google AI Overviews, Google Gemini, Google AI Mode, Microsoft Copilot, Grok, Meta AI, and DeepSeek. We add new engines quickly as the market evolves.
Global regional coverage is available starting from the entry-level plan, not locked behind enterprise pricing. Plus, Profound runs every prompt daily through front-end browsers in favor of APIs, so the data reflects what real users see in their local context.
Profound vs. AirOps: AI visibility insights
For AEO to work, you need data that tells you how answer engines see your brand, what’s driving that perception, and what your content gaps are.
AirOps: Better on sentiment and citations, still no real prompt data
At a glance
Pros:
- Sentiment breaks down by theme (e.g. "customer support," "pricing flexibility," "product reliability"), not just brand-level positive/negative—closed a real gap here
- Citation tracking now shows a Top 10 Cited URLs view with per-page citation share, not just an aggregate citation count
Cons:
- No prompt-level attribution—can see a page gets cited often, but not which specific prompts are driving those citations
- Prompt popularity score is still an estimation model, not derived from real user conversations
- No infrastructure-level monitoring—can't show which AI crawlers are visiting your site or what they retrieve
AirOps provides share of voice, overall AI visibility, sentiment, and citation data. It's a meaningfully deeper dashboard than it was when this comparison was first written—sentiment and citations have both moved past brand-level summaries. What still caps a serious optimization strategy is the layer underneath all of it: the demand data.
Sentiment used to be brand-level only, but that's changed: AirOps now breaks sentiment down by theme, using short auto-extracted descriptors like "customer support," "pricing flexibility," or "product reliability," visualized as a treemap and filterable by platform, region, and persona. That's genuinely comparable to what Profound offers. Citation tracking has also gotten more specific—AirOps now shows a "Top 10 Cited URLs" view with citation count and share per page, not just an aggregate citation share. What's still missing is prompt-level attribution: AirOps can tell you a page gets cited often, but not which specific prompts are driving those citations, so you can't connect a citation back to the exact question that triggered it.
Prompt visibility is limited in a more fundamental way. AirOps doesn’t have access to real prompt volume data; the platform surfaces a “popularity” score, but it’s an estimation model rather than a metric derived from user conversations.
Profound: The deepest AI visibility data in the market
At a glance
Pros:
- Full AI visibility metrics suite: share of voice, visibility score, citation share, ranking position, and sentiment, broken down by specific themes and product attributes
- Prompt Volumes powered by 1.9B+ real user conversations, filterable by demographics including age, income, and region
- Agent Analytics adds CDN-level crawler monitoring via integrations with Cloudflare, Akamai, AWS CloudFront, Fastly, and others—shows which AI crawlers visit, how often, and what they retrieve
- Query Fanouts Analysis reveals how answer engines decompose a single user prompt into multiple underlying queries, enabling deeper optimisation
Cons:
- The dashboard can feel overwhelming at first due to the sheer amount of data points it tracks
Profound is overwhelmingly praised by users for its comprehensive data foundation. Answer Engine Insights tracks visibility score, share of voice, citation share, sentiment, and positioning across all major answer engines, with daily data refreshes and full historical records.
Sentiment analysis doesn't cap at positive/negative. Our platform surfaces the specific themes and product attributes driving each sentiment signal, so you can see what AI is saying about your brand’s pricing, performance, or feature set.
Citation tracking is just as detailed. You can pinpoint your most-cited pages, track citations for individual URLs on your site, and identify which pages are appearing in citations for specific prompts. Prompt Volumes, powered by 1.9B+ real user conversations, lets you filter by demographics including age, income, and region, see related prompts, and understand the intent behind what people are asking AI engines.
Agent Analytics goes a layer deeper still, with infrastructure-level monitoring via CDN integrations that shows which AI crawlers are visiting your site, how often, and which content they’re retrieving. Plus, Query Fanouts Analysis reveals how answer engines transform a single user prompt into multiple underlying search queries before generating a response, so you can optimize for what AI systems are searching.
Profound vs. AirOps: Actionable recommendations
Spotting a problem and knowing what to do about it are two different things. How much each platform helps you span that distance is one of the more practical distinctions between AirOps and Profound.
AirOps: Limited context, limited actionability
At a glance
Pros:
- Content refresh opportunities auto-populate a relevant Grid workflow, providing a useful shortcut from insight to action
Cons:
- Outreach opportunities surface the issue but leave the workflow empty, with no guidance on which publication to target, who to contact, or what to write
- Single tag level for segmentation; teams with multiple product lines, regions, or business units cannot meaningfully slice insights with the precision required
AirOps organizes opportunities into subcategories—prompt gaps, declining citations, weak content, and others. For some recommendation types, like AEO content refreshes, selecting an opportunity auto-populates a Grid with a relevant workflow, which is a nifty shortcut.
For other recommendations, the experience falls short. “Mention gap” opportunities, which require outreach to third-party publications, surface the issue but leave the Grid empty. There’s no guidance on why a particular publication is worth reaching out to, who to contact, what to write, or when to act. Teams are expected to fill in the strategy themselves.
Segmentation is also constrained in AirOps. The platform only supports one tag level for filtering and analyzing data which, for businesses with multiple product lines, brands, or business units, isn't enough to meaningfully slice insights and act on them with precision.
Profound: Context-rich, action-ready insights
At a glance
Pros:
- Every recommendation includes the rationale: competitive landscape around the prompt, expected visibility impact, and where you currently stand relative to cited pages
- Outreach opportunities come with drafted sample emails, suggested targeting criteria, and prioritisation logic for which publications or authors to approach
- Multi-level segmentation by product line, region, business unit, or any custom dimension
- Recommendations sharpen over time: the self-learning loop feeds post-publication citation data back into the recommendation engine
Cons:
- Recommendation quality improves over time, but early on the feedback loop needs content volume to kick in—teams starting fresh don't get the full benefit of the self-learning engine until they've published and tracked enough content.
Profound’s recommendations come with the rationale built in. Each opportunity surfaces what to do, yes, but also why: the competitive landscape around the prompt, the expected visibility impact, and where you currently stand relative to the pages being cited. Users frequently highlight how instrumental these insights are, with one reviewer noting that “AEO felt like shooting in the dark before Profound, and now we have actionable insights that are driving real uplift.”
For outreach opportunities in particular, Profound drafts sample outreach emails, suggests targeting criteria, and explains the logic behind prioritizing specific publications or authors.
Multi-level segmentation with tags, topics, and custom filters lets you slice data by product line, region, business unit, or any dimension that is relevant to you. And the self-learning feedback loop we mentioned earlier means recommendations improve over time. As content gets created and published, our platform tracks what gets cited and what doesn’t, feeding that signal back into the recommendation engine so future suggestions are sharper.
Profound vs. AirOps: Compliance and security certifications
At a glance
AirOps:
- AirOps is SOC 2 Type II certified
- There's no evidence of HIPAA assessment on AirOps’ side—for teams in regulated industries, that ambiguity alone can disqualify a vendor in procurement
Profound:
- Profound has a SOC 2 Type II certification \+ an independent HIPAA compliance assessment conducted by Sensiba LLP
- Profound's enterprise grade safeguards include AES-256 encryption at rest, TLS 1.2+ in transit, MFA, RBAC, comprehensive audit logging, automated disaster recovery
- Profound supports SSO via SAML and OIDC and integrations with enterprise infrastructure including GA4, Cloudflare, Akamai, AWS CloudFront, Fastly, Netlify, and Vercel
For enterprise organizations, especially those in healthcare, pharma, finance, or other regulated industries, compliance is a gate.
Profound holds SOC 2 Type II certification and has completed an independent HIPAA compliance assessment conducted by Sensiba LLP. That assessment validated enterprise-grade safeguards across the full security stack: AES-256 encryption at rest, TLS 1.2+ encryption in transit, multi-factor authentication, role-based access controls, comprehensive audit logging, and automated disaster recovery.
Profound also supports SSO via SAML and OIDC, granular permission roles, and integrations with enterprise infrastructure including GA4, Cloudflare, Akamai, AWS CloudFront, Fastly, Netlify, and Vercel.
AirOps’ compliance posture is considerably less transparent. While it claims to be SOC 2 Type II compliant, there’s no evidence of a HIPAA assessment and its associated safeguards. For teams in regulated industries running procurement reviews, that ambiguity alone can disqualify a vendor.
Profound vs. AirOps: Final verdict
AirOps is no longer just a content generation tool—Quill, its background agent, now scans continuously for stale pages, competitor gaps, and citation opportunities, and learns from what a team accepts or declines. But the critical piece of AEO is still data: on what people are actually asking answer engines, on how LLMs decide what to cite, and on which content earns those citations over time. An agent is only as sharp as the signal it's watching.
Previously, teams serious about AEO needed two platforms—Profound for data and something like AirOps for content orchestration. That's no longer the case. Profound is an agentic marketing platform, and the whole loop lives in one place: the industry's deepest AI visibility data, AIM finding and scoping the highest-impact gaps on its own, Agents turning those briefs into publish-ready drafts, and Agent Analytics measuring which pages the engines rewarded so the next round is sharper.
Profound has raised a $96M Series C led by Lightspeed Venture Partners, holds the #1 ranking on G2 for AEO, and is trusted by the likes of Ramp, Figma, MongoDB, U.S. Bank, and Chime, among many others.
If your team needs comprehensive AI visibility data, agentic content creation, and a closed measurement loop in a single platform, Profound is the obvious choice.
Get your AEO program to new heights. Book a demo with our team.
Profound vs. AirOps FAQs
Is AirOps or Profound better for AI visibility tracking?
Profound is the stronger choice by a large margin, though the gap has narrowed on two specific metrics. AirOps now offers theme-level sentiment and per-URL citation tracking, which used to be brand-level-only. What AirOps still lacks is real prompt volume data (its "popularity" score is an estimation model, not real conversations), prompt-level citation attribution (it can't connect a specific citation to the prompt that triggered it), and infrastructure-level crawler analytics. Profound's Answer Engine Insights, Prompt Volumes, and Agent Analytics give you a comprehensive, daily-updated picture of how answer engines see your brand, grounded in 1.9B+ real user conversations.
Can Profound replace AirOps for content creation?
Yes. Profound Agents cover the same content creation and refresh use cases as AirOps, including brief generation, FAQ creation, and content optimization, but with the added advantage of being powered by AI citation and prompt data. Profound runs AIM, an always-on background agent that originates the brief by spotting the visibility gap on its own; AirOps' Quill does something similar now, but works from AirOps' own visibility data, which trails AIM's on model coverage and real-user grounding (see the data foundation comparison above). And because Profound tracks what gets cited after publication at the CDN level, the content engine improves over time against a harder signal than accept/decline feedback.
How does pricing compare between Profound and AirOps?
AirOps and Profound serve different scopes, and the pricing reflects that. AirOps is primarily a content automation tool with basic AI visibility monitoring added on top. Its paid plans top out at four to five answer engines with US-only regional data unless you're on an Enterprise contract.
Profound is a full AEO platform. Enterprise plans include 10+ answer engines tracked daily, real prompt volume data from 1.9B+ user conversations, infrastructure-level crawler analytics, citation tracking at the page and text-chunk level, global coverage across 50+ countries, and HIPAA compliance. Visibility plans are fixed by tier with no task-based billing on the analytics side.
For teams evaluating both, the question isn't which is cheaper. It's which platform covers what your AEO program actually needs.
Which tool covers more AI platforms, Profound or AirOps?
Profound covers 10+ answer engines out of the box: ChatGPT, Claude, Perplexity, Google AI Overviews, Google Gemini, Google AI Mode, Microsoft Copilot, Grok, Meta AI, and DeepSeek. AirOps' paid plans top out at five engines and don't include Claude, Meta AI, Grok, DeepSeek, or Microsoft Copilot. Profound also covers 50+ countries and 15+ languages, while AirOps' regional coverage is US-only unless you're on Enterprise.
Is Profound HIPAA compliant?
Yes. Profound has completed an independent HIPAA compliance assessment conducted by Sensiba LLP, validating enterprise-grade safeguards including AES-256 encryption at rest, TLS 1.2+ in transit, multi-factor authentication, role-based access controls, and automated disaster recovery. Profound is also SOC 2 Type II certified and supports SSO via SAML and OIDC.