AirOps vs Semrush: Content Engine vs SEO Data Suite for AI Search

The AirOps vs Semrush decision is rarely settled by counting features. Both products touch AI search, both produce content in some form, and both publish capability lists that overlap at the edges. The question that decides it is narrower: which bottleneck is holding the program back. A team that knows what to write and cannot get it written is solving a different problem than a team that publishes steadily and cannot tell which topics are worth the effort.

That is the real shape of the seo data suite vs content engine choice. AirOps is a content-operations platform with AI-search measurement attached. Semrush is a broad SEO and marketing-data suite with an AI Visibility product and a separately priced Content Toolkit beside it. Neither description is a criticism. They are different centers of gravity, and a marketing lead who picks the wrong one pays for depth in the place where the constraint is not.

DeepSmith publishes this comparison, so the stance is stated openly. DeepSmith is an AI-search analytics and content-production platform in one, and the case below is that the loop from visibility gap to published article is the part most teams are missing. Where AirOps or Semrush genuinely fits a reader better, that is said plainly.

AirOps vs Semrush at a glance

AirOps: content operations with AI-search measurement attached

AirOps describes itself as an AI content platform for answer engine optimization and SEO, built on three pillars. Insights covers content and AI-search performance. Actions turns those insights into work through Playbooks, Workflows, Grid, and Power Agents. Context supplies Brand Kits and Knowledge Bases so generated material uses company-specific information. An AirOps MCP server makes the platform reachable from Claude, Cursor, or another MCP client.

The measurement layer is genuine rather than decorative. AirOps documents prompt-level answers and answer history, mentions and mention rate, citations and citation rate, page-level attribution, share of voice, competitor presence, sentiment, and visibility trends. It connects to Google Search Console and Google Analytics 4 so AI-search performance can be read next to organic traffic, cited-page referrals, and conversions. Analytics settings support tags, personas, and up to ten competitors.

The collection model drives both cost and cadence. Each tracked prompt run on a platform, region, or persona creates an Answer. A standard Answer consumes one task and a Claude Answer consumes four, and the default is one answer per prompt and platform per day, with more available on request for enterprise accounts.

Playbooks are the surface most teams will spend their time in. A Playbook combines natural-language instructions, Brand Kit context, tools such as SEO Research and Web Research, reusable inputs, and artifacts in Markdown, HTML, JSON, or CSV. It can be triggered by a schedule, a webhook, a monitor, or an AEO insight, and it can include a human review step before publishing. Workflows are the visual automation builder underneath: branching, data processing, model calls, research steps, approvals, and CMS publishing. Grid runs workflows at scale across rows, and Power Agents are pre-built automations for SERP analysis, keyword research, brief creation, and competitive gap analysis.

One architectural limit deserves attention before a team designs around it. The documentation states that Playbooks cannot be used inside Workflows. A Workflow can create a Playbook, but a Playbook cannot be added as a Workflow step. The two are complementary action surfaces rather than one nestable pipeline, so an ambitious automation plan should be drawn against that boundary rather than discovered at build time.

Pricing is where the AirOps evaluation gets harder. Capacity is priced in tasks, and a task covers selected actions such as content generation and data extraction, with consumption varying by step type and data volume. Solo lists 100 tracked prompts and pages, ChatGPT-only Insights, monthly opportunity reports, 20,000 content-production tasks, three Knowledge Bases, and single-user access. Pro lists 250 tracked prompts and pages, multi-engine insights, weekly opportunity reports, 75,000 tasks, five Knowledge Bases, and unlimited seats. Enterprise is custom, and the trial runs 14 days or until tasks are depleted.

The pricing page retrieved for this research displayed those allowances without visibly displaying Solo and Pro dollar prices, and listed an additional-task rate of $0.025 for Solo. Two independent 2026 write-ups report Solo at $200 per month and Pro at $2,000 per month. Those figures are worth carrying into a conversation with AirOps, but should be confirmed at checkout rather than treated as settled list prices.

Semrush: an SEO data suite with an AI visibility layer

Framing this as Semrush vs AirOps on content features understates what Semrush is. Its materials separate three relevant surfaces. The SEO Toolkit spans keyword, domain, competitor, technical, position, backlink, local, social, advertising, traffic, market, and project tools across more than twenty reports. AI Visibility measures brand performance and citations in AI answers. The Content Toolkit handles topic discovery, briefs, generation, optimization, brand voice, rewriting, images, repurposing, and publishing.

The SEO depth is the part no other product here matches. Semrush materials state a 26.2-billion-keyword database, and plan-specific limits reach a Site Audit of up to one million pages per month and Position Tracking across up to 40 projects and 5,000 keywords. Keyword Magic Tool, Keyword Gap, Backlink Gap, On Page SEO Checker, and Backlink Audit sit alongside the newer AI-search reporting. For a team whose central job is understanding what the market is doing, that breadth is the product.

AI Visibility is its own set of modules: Visibility Overview with an AI Visibility Score, share of voice, sentiment and narratives; Competitor Research; Prompt Research covering topic volume, difficulty and intent; Brand Performance with location and language analysis; Prompt Tracking; and an AI Search Site Audit. Brand Performance supports more than 68,000 location and language combinations, and Prompt Tracking covers more than 220 countries and territories. That geographic reach is a real advantage for multinational brands, bounded by what the module does not report.

Prompt Tracking documents ChatGPT Search, Google AI Mode, and Gemini, accepts custom prompts by manual entry or TXT and CSV import, and returns AI Visibility, Mentions, Owned Sources, Topic Volume, and Average Position daily. Estimated Traffic and share of voice are not available for either AI search engine inside Prompt Tracking, though Brand Performance and other modules report share of voice separately, and the module is documented as desktop-only. Prompt limits run to 25 on standalone AI Visibility, and 50, 100, or 200 on Semrush One Starter, Pro+, and Advanced. A program tracking hundreds of buyer questions will need a higher plan or a different measurement design.

Pricing is modular in a way that rewards careful reading. The combined SEO and AI Search plans list a free tier, SEO at $139 per month, Starter at $199, Pro+ at $299, Advanced at $549, and custom Enterprise, with additional users at $45 per month. Standalone AI Visibility Base is $99 per month per domain billed annually, covering one domain, 300 daily AI Analysis queries, 25 tracked prompts, AI search checks for up to 100 pages, and 10 CSV exports per day capped at 1,000 rows each. No free trial is documented for the standalone product. The Content Toolkit is a separate $60 per month with a 7-day trial, five SEO-boosted articles per month, an add-on of ten more boosts for $30, up to 50 brand voices, one-click WordPress publishing to as many as 100 sites, and repurposing to seven channels.

One wording discrepancy is worth flagging rather than resolving. The Content Toolkit pricing page displayed 10,000 articles per month while the help documentation describes unlimited standard articles. Those may refer to different units or versions of the product, so the live plan should be checked for the unit that applies.

DeepSmith: one loop from AI visibility to published content

DeepSmith is an AI-search analytics and content-production platform in one, positioned as a production engine rather than a writing assistant. The intended output is a finished, on-brand article, not a first draft that a marketing lead has to rescue. That framing is the reason DeepSmith appears in a comparison it also publishes: the argument is not that it out-features either product above, but that it closes a loop the other two leave to the buyer.

Measurement comes first. The AEO area reports Mention Rate, Citation Rate, Share of Voice, Sentiment, and Visibility Trend, with an overview carrying platform breakdowns, a competitor leaderboard, and the sources AI cites most. Prompts holds the tracked buyer questions with per-prompt mention and citation rates and full answer history, and Discover Prompts generates a starter set from stored product, persona, and buyer-stage context. Pages shows which owned pages AI actually cites and the prompts driving those citations. Competitor Citations names the exact competitor pages winning the prompts a brand cares about.

Content Map turns the owned site and unlimited competitor sites into one topic and funnel-stage map. Pages are crawled, enriched, and classified onto granular topics and Awareness, Consideration, or Decision stages, with the owned site defining the taxonomy so competitor comparisons are like for like. It surfaces coverage gaps where a competitor publishes more, and untapped topics where a competitor publishes and the brand has nothing. Sitemaps are re-checked every 24 hours and new pages fold in automatically.

Opportunity Agents connect the two halves. Each agent reads the brand's own visibility or Content Map data and returns ideas with the data point that justifies them travelling alongside. Agent families cover getting cited for a tracked prompt, turning mentions into citations, taking a competitor's citations, fixing how AI describes the brand, and closing a stage-specific gap against up to four competitors at once. Runs accept a 30, 90, or 180 day window plus free-text instructions, and each is kept as an immutable record. The practical effect is that a content backlog can be defended rather than explained away.

Production runs from Opportunities to New Ideas to Planned Content to Produced Content. The Writer researches an idea and returns an article with internal and external links, a cover image, and publish-ready metadata. Autowrite takes it further: an article configured at planning time writes itself on its scheduled date and lands in Produced Content with nobody in the app. Publishing goes directly to WordPress, Webflow, Strapi, Sanity, or Contentful, or to custom webhooks. Keyword coverage, heading structure, schema markup, internal linking, and metadata are part of creation rather than a review cycle afterwards, and the pipeline places up to five internal links during generation.

Deep IQ keeps all of this on brand. Company positioning, product profiles, buyer personas, brand voice, visual guidelines, content types, and a trusted-sources list are stored once and reused by every module, which is the honest answer to the fear that AI output drifts into generic copy. It is not a promise that review becomes unnecessary; Produced Content exists precisely so a human can revise body, metadata, and cover image first. Repurpose and the Apps Library then turn each finished article into platform-native versions for LinkedIn, X, Medium, Substack, newsletter email, Reddit, Facebook, Instagram, Slack, WhatsApp, and more.

Pricing is plan-based and legible. Pro is $99 per month, Grow is $199, and Scale is $399, or $80, $160, and $299 when billed annually, with custom Enterprise above that. Those tiers carry 20, 40, and 90 articles per month, 50, 100, and 200 tracked prompts, and 5, 7, and 10 seats. A 7-day free trial runs on real data and real drafts, with no long-term contracts and no cancellation fees.

The engine coverage rule is the boundary worth stating clearly. DeepSmith names ten engines: ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews, Google AI Mode, Grok, Meta AI, Microsoft Copilot, and DeepSeek. Pro tracks ChatGPT only. Grow adds Perplexity, Scale adds Gemini, and all ten require Enterprise or Custom. A reader who needs every engine at the entry price should not be told otherwise. The mitigating fact is that ChatGPT is where most buyer research begins, so a program starting at Pro is measuring the engine that matters most while the article allowance is already producing against what it finds.

AI-search measurement compared

All three products measure AI search, and the differences are in scope rather than presence. Semrush offers the widest analytical surface: a visibility score, sentiment and narratives, prompt research with topic volume and intent, geographic breadth across tens of thousands of location and language combinations, and an AI-search site audit. That is the strongest option for a team that wants AI visibility analyzed next to organic rankings, backlinks, and market data in one place. The bound on that strength is unit fragmentation. Different modules expose different engines and metrics, standalone AI Visibility tracks 25 prompts against Semrush One's 50 to 200, and the reports carry their own export caps.

AirOps measures in service of action. Its visibility data feeds the AEO Insight trigger, so a prompt losing ground can start a Playbook rather than a meeting. The bound is that collection consumes tasks from the same pool that generates content, so tracking cadence and production capacity draw on one budget.

DeepSmith's distinction is that measurement is designed as an input to production rather than as a destination. Citations attribute to specific pages, competitor citations name the exact winning pages, and Opportunity Agents read that data directly to produce the next set of ideas.

Research breadth and the path to a production queue

On research depth, Semrush wins clearly and the concession should not be hedged. No product here approaches its keyword, backlink, technical, local, market, and API coverage, and an agency reporting across many clients will feel the difference daily. The adjacent limit is that breadth does not assemble itself: research, content generation, AI visibility, approvals, publishing, and distribution are separate surfaces with separate allowances, and the team supplies the connective process.

AirOps sits closer to the work. Power Agents cover SERP analysis, keyword research, brief creation, and competitive gaps, and its integrations pull in Moz, DataForSEO, Search Console, and analytics sources. Research is an input to a workflow rather than a library to browse. The limit is that the architecture still has to be designed, and the Playbook and Workflow boundary shapes what can be composed.

The transition that decides most programs is the one from a known gap to a scheduled article. Semrush finds the gap. AirOps can trigger an action from it. DeepSmith carries the evidence into the queue: the data point that justifies an idea travels with it into New Ideas, a date moves it into Planned Content, and Autowrite produces it on that date. For a marketing lead whose real complaint is that good ideas stall between the dashboard and the calendar, that is the axis that matters.

Brand context and distribution

Each product stores context, and the scope differs. AirOps uses Brand Kits and Knowledge Bases to ground outputs in company information. Semrush Content Toolkit documents up to 50 brand voices with tone optimization, alongside the SEO Writing Assistant's checks on SEO, readability, originality, and tone inside Google Docs, WordPress, and Word. Deep IQ stores company, product, persona, voice, visual, content-type, and trusted-source records that every DeepSmith module reads, so the same context shapes research, writing, linking, imagery, and metadata without a per-article briefing.

Distribution is a genuine Semrush strength and deserves crediting. Content Toolkit repurposes to seven channels and publishes through Social Poster, Mailchimp, WordPress, and Canva connections. The bound is that it is a separate product surface at a separate price, so the research, visibility, content, and distribution steps still need stitching together. DeepSmith's Repurpose and Apps Library cover a wider named channel list and arrive attached to the finished article, which keeps distribution from becoming the step that falls off after publication.

Pricing shapes that do not compare directly

A useful semrush alternative comparison has to resist the urge to line up the numbers. AirOps tasks, Semrush reports and prompts, Content Toolkit SEO boosts, and DeepSmith articles are not the same unit, and converting between them produces confident nonsense.

AirOps prices flexible capacity in tasks, which suits an organization willing to model consumption and confirm plan pricing directly. Semrush prices modular breadth, so a full workflow may mean paying separately for SEO, AI Visibility, Content Toolkit, extra users, and API units. DeepSmith prices predictable output, with an article count, a tracked-prompt count, a seat count, and an engine tier visible on every plan. For a lead who has to defend a line item, a visible article allowance is easier to budget than a task pool.

Which should you choose

The seo data suite vs content engine framing resolves once the constraint is named honestly, so the recommendations below are organized by situation rather than by score.

Choose AirOps when execution is the constraint and the team wants to build its own operations rather than adopt someone else's. Playbooks, Workflows, Grid, Power Agents, human review, MCP access, and direct CMS publishing suit an organization that already has a process worth automating. It fits best where someone is prepared to model task consumption before committing.

Choose Semrush when SEO and marketing intelligence is the constraint. Keyword and competitor research, technical audits, backlinks, rank tracking, local and market analysis, and API access across many sites or clients are the jobs it was built for, and AI Visibility can then be read alongside them. It suits a team comfortable managing a modular suite and assembling its own path from research to publication.

Choose DeepSmith when the problem is both halves at once: no clear picture of where the brand is losing in AI answers, and no capacity to respond when the picture arrives. Teams asking whether AirOps or Semrush should be the primary tool often find the answer is neither, because the gap is the loop between them. DeepSmith measures visibility, attaches evidence to each idea, produces publish-ready articles in stored brand context, schedules them, publishes to the CMS, and generates the distribution assets, on one plan with one set of allowances.

The 7-day trial runs on real data and real drafts, so the workflow can be tested before payment. Start a free DeepSmith trial and see which prompts the brand is already losing.