AthenaHQ vs AirOps: Visibility or Production, 2026

Key Takeaways

• AthenaHQ and AirOps are still sold under those names. One records how answer engines mention and cite you. The other runs content production against a task balance.

• Only AthenaHQ prints a monthly dollar price on its main paid card. AirOps prints task caps and leaves the team tier as a quote.

• Match the tier to the engines you need. The free AirOps entry watches ChatGPT. The free AthenaHQ entry watches a short list, and the paid card watches a longer one.

• Multiply prompts by models by refresh rate before you treat a credit pool or a task pool as large.

• On AirOps, a Claude answer is metered more heavily than a standard answer, and a brand-new free workspace is not the Solo allotment.

• Keep a human review before a page changes. Add a later handoff only when the source tool will not hold that approval itself.

The stuck job decides the tool

AthenaHQ and AirOps are both still offered under those names. The pricing and docs pages opened for this comparison do not describe a rename, a merger, or a shutdown. The choice is which job is stuck on your team this quarter. AI search visibility is the record of whether an answer engine names your brand and which pages it cites when a buyer asks a category question. AthenaHQ is built to collect that record and attach recommendations. AirOps is built to turn research into reviewed drafts and CMS updates, and it meters the work as tasks.

TL;DR: choose AthenaHQ when finance needs a published price and the team needs a multi-model record of mentions and citations. Choose AirOps when the missing work is drafting, reviewing, and publishing, and you can accept a quote once you leave the ChatGPT-only entry. Do not buy both on day one unless one person owns measurement, another owns production, and you have already named the file or API that passes work between them.

A marketing lead at a B2B SaaS company usually feels the gap in one of two meetings. In the first, leadership asks why the brand is absent when a buyer asks an answer engine for a comparison, an integration, or a pricing explanation. In the second, the content calendar is the constraint: pages are thin, stale, or waiting on an editor, so a visibility chart would only confirm a problem nobody can ship a fix for. Those are different purchases. A tracker with a content agent still leaves the CMS write to a person. A production system with a thin engine list still leaves you blind on the models your buyers actually open.

Who this is for

This comparison is for a marketing lead who can shortlist one system this month and who already knows whether the bottleneck is seeing answers or shipping pages. It fits a team that will write down a prompt list in buyer language, name an editor, and check an invoice against a credit or task cap. It is a poor fit if you want a single login to replace a CMS, a search suite, and an analytics stack at the same time.

Choose AthenaHQ when the question in the room is where the brand appears, on which models, against which competitors, and which URLs those answers cite. The public card gives you a number to put in a budget line, a credit definition you can multiply, and a CSV once you are on the paid tier. Choose it when a strategist can act on a recommendation and a writer still owns the page. Across 46 reviews, G2 score: 4.9 out of 5 according to G2 (2026). The March 2026 summary on that page says reviewers value specific recommendations and also report a complicated credit system, no combined view across brands, and gaps around local map results.

Choose AirOps when the question is who will refresh a large set of pages under brand rules, with a review step, into the CMS. The pricing matrix lists playbooks, grids, quality scores, version history, and human review. That is a production system. The team plan does not print a subscription dollar, so procurement has to accept a quote. Solo is the wrong tier if more than one person must log in or if you need any engine besides ChatGPT.

Red flags: you need a public dollar price for multi-engine content production and will not accept a quote; you need SSO, an audit log, and more than one country on a self-serve checkout; you have no editor who will review a draft before it is allowed onto the site.

How we evaluated these tools

The weights below are a buying model for a B2B SaaS marketing lead. They are not a vendor score and not a lab result. Each weight is the share of a 100-point shortlist that criterion represents. The points column repeats the weight so a failed criterion removes that share. A tool can be excellent at a low-weight item and still be the wrong buy if a high-weight item is missing.

Engine coverage matters because a ChatGPT-only watchlist hides the other places buyers ask. A price you can approve without a call matters because a quote stalls a budget meeting even when the product fits. Room to produce or revise pages matters because a chart does not create a citation. A human review point matters because an unreviewed draft on a product site is a brand and legal risk. An export or API matters because the measurement login and the CMS login are rarely the same person. Seats, language, and region matter when more than one marketer, or more than one country, has to see the same brand.

Read the rows as gates, not as a blended score. If you fail the price gate, AirOps Pro is not disqualified as a product. It is disqualified for a team that must finish procurement from a public card. If you fail the production gate, AthenaHQ Starter is not a bad tracker. It is the wrong system for a team whose editors are the bottleneck.

What the cards actually include

Solo tasks: 35,000 per month according to AirOps (2026), where the Solo plan is free to start and includes ChatGPT insights only, 1 user, 1 brand kit, and 3 knowledge bases, the Pro plan lists 100,000 tasks, 7 or more answer engines, 1 brand kit, 5 knowledge bases, and unlimited seats with no dollar price printed, extra Solo tasks cost $0.025, and the questions on that page still describe a 14-day trial of Scale features plus 50,000 testing credits for Scale, Enterprise, and trial accounts. Treat the Pro plan and the Enterprise plan as Quote-based. The three cards are named Solo, Pro, and Enterprise, while those questions still say Scale and Agency. Confirm which names are on the order form before you compare a quote to the public card.

The same split shows up in how the products talk about the work. AthenaHQ's comparison table marks a base content optimization agent, on-page and off-page actions, citation intelligence, CSV export, and Shopify, Webflow, Google Analytics, and Search Console connections on the paid self-serve tier. The advanced optimization agent, the citation engine, SSO, the audit log, persona targeting, and multi-country support sit on the custom tier. AirOps lists CMS and SEO integrations on Solo and a wider CMS, SEO, AEO, social, and project set on Pro, plus human review on the pricing matrix. If your near-term worry is Google AI Overview visibility, check that the tier you are buying names that surface. Essential on AthenaHQ includes AI Overviews in its five-model list. Solo on AirOps does not, because it is ChatGPT insights only.

Use the matrix as a filter, then read the profile that matches your stuck job. A green cell on content work does not mean the draft can go live. A green cell on engines does not mean every country you sell in is included.

Pricing checked against the live cards

Pricing checked October 10, 2026. Starter price: $295 per month according to AthenaHQ (2026), on a card that also lists a free Essential plan with a $25 credit and 300 credits across 5 models, a Starter pool of 3,600 credits at 1 credit per AI response, 11 models, a "$300/month free credit" line, and 17% off when you switch the page to annual billing. The monthly view we opened did not print a second dollar figure for the annual invoice, so confirm that invoice before you sign. API access and extra credits on Starter are paid add-ons with no printed price, so those add-ons are Quote-based. The Enterprise plan is Quote-based, with custom credits, and it is the tier that adds the knowledge base and claim review, discrepancy checks, the citation engine, SAML and OIDC SSO, an audit log, multi-region and multi-language support, persona targeting, and BI connections for Tableau, Power BI, and Looker.

A separate review, last verified on 2 October 2026, still lists that Starter plan at $295 a month with 3,600 credits and 11 models, and it also says annual billing saves 17%, according to AI Visibility Products (2026). That match is useful because older write-ups in the category still quote different model counts. For this article, the live card wins: 11 models on Starter, 5 on Essential, and no invented annual dollar amount.

The "$300/month free credit" line on the Starter card sits beside the 3,600-credit allowance. The page does not show a conversion that turns $300 into a different response count. Budget against 3,600 responses, and ask what the $300 line changes before you model overage. The $25 line on Essential is the same kind of label next to 300 credits. Do not invent a per-credit cash rate from either pair. Extra Solo tasks at $0.025 are the only per-unit cash rate either vendor printed on the pages reviewed. Everything else above the free entry is either $295 a month or Quote-based.

Total cost is the subscription plus the units you will actually burn, plus reviewer time, plus any add-on you were told was included. On AthenaHQ, a wide daily sweep can exhaust 3,600 credits while the $295 line looks modest. On AirOps, a ChatGPT-only Solo plan can look cheap because it is free to start, then fail the buying brief because the second user and the second engine are not on that card. Pro's missing dollar is the larger unknown. Put "quote" in the spreadsheet until the order form replaces it. A useful companion on the production side of the budget is a SaaS workflow pricing guide, so task math and seat math are not treated as the same kind of cost.

AthenaHQ when the record is the product

Best fit is a SaaS team that will maintain a prompt list in buyer language and report mentions, citations, and competitors to leadership. Starter is the tier that matches that job on a public price: 11 models, unlimited topics on the comparison table, competitor tracking, sentiment, a base content agent, and CSV export. Essential is a sensible first month if you only need the five named models and can live inside 300 credits. It is the wrong month if you already know you need Claude, Grok, DeepSeek, Meta AI, Mistral, or AI Mode, because those names appear on the Starter list, not on Essential.

The limits are printed, and they are easy to skip. Starter is single-region and single-language on the comparison table. SSO, the audit log, persona targeting, the advanced optimization agent, and the citation engine are Enterprise, which is Quote-based. API access is not inside the $295. G2's summary on the page cited above also flags the lack of one view for several brands, so a company with many products should ask how workspaces are separated before it assumes one login covers the portfolio. The credit system is the other limit reviewers mention, and the math in the next section shows why. None of that makes the tracker a poor buy. It means the $295 card is a measurement product with a base agent, not an enterprise governance suite.

Implementation starts with the prompt list, not with the agent. Write prompts the way a buyer asks: category, competitor comparison, integration, pricing, and implementation. Run a small set on Essential, then move the same prompts to Starter if the five-model list is too narrow. Export CSV for anyone who will not get a seat in the weekly review. If a second system must read the rows, budget the API add-on as Quote-based and do not assume the CSV will be replaced for free. Pair the citation view with a short list of AI citation tools only to see which extra check you still need. AthenaHQ's own card already includes citation intelligence, so a second tracker is optional, not a default.

AirOps when the pages are the product

Best fit is a content operations lead who already knows which URLs should change and needs a system that can research, draft, score, and wait for a person. Pro is the first tier that matches a team: unlimited seats, 100,000 tasks, and insights across 7 or more answer engines. The price is Quote-based. Solo fits a single operator proving a workflow on ChatGPT, with 35,000 tasks, basic CMS and SEO integrations, and community plus live chat support. It does not fit a squad, and it does not fit a brief that names Perplexity, Gemini, or AI Overviews.

The limits are mostly about the meter and the names on the page. A new free-tier workspace is not Solo. Schedules stop if you fall back to a free workspace, and you have to turn them on again if you upgrade later. The pricing questions still talk about Scale and Agency, so a quote that uses those words needs a line-by-line map to Solo, Pro, or Enterprise. Across 133 reviews, AirOps G2 score: 4.7 out of 5 according to G2 (2026). The May 2026 summary on that page cites a steep learning curve, workflow errors, and weak spots in GEO tracking and CRM connections. Read that as a staffing warning. Someone has to own the workflows after the kickoff. If your team wanted a tracker and hoped production would come along for free, this is the heavier product. Writers comparing draft quality across tools can also look at AI writing tools for SaaS without treating any of them as a substitute for the review step.

Implementation means estimating answers before you estimate articles. The billing docs define monthly answers as platforms times regions times (1 plus named personas) times 30 days, show 3 platforms times 2 regions times 3 persona slots times 30 days equal to 540 answers, price Claude at 4 units against 1 unit for ChatGPT, Gemini, Perplexity, Google AI Mode, and Google AI Overview, say Google AI Overview runs once per region per day and ignores personas, grant a new free-tier workspace 1 task, cap a code step at 1 task per run, and charge 0 tasks for an output step, according to AirOps (2026). Set a hard task limit so a runaway grid cannot keep spending. Keep the human review the pricing matrix already lists, and do not treat a quality score as approval. Failed steps are not charged, but a nested workflow that succeeds is charged, so a red parent run can still cost money. Ask the account team whether your workspace is on combined task billing or on legacy answer credits, because those two models do not draw from the same balance.

Run the month on paper first

The table below applies the Starter rule already cited: 1 credit equals 1 AI response, and the pool is 3,600 credits at $295. The rows are arithmetic, not observed customer usage. A pass is one check of every prompt on every model in that row.

Essential's 300 credits do not survive the tight row. Twenty prompts on the 5 Essential models, checked twice in the month, use 200 credits and fit. The same list checked weekly uses 400 and does not. That is why a free month can look healthy and a weekly habit on 11 models can crowd the paid pool. The twice-weekly row leaves 80 credits, which is not enough for a second ad hoc pass if someone asks a new question on Friday.

Take a SaaS marketing lead who wants 40 comparison prompts checked on the 11 models named for the Starter plan. One full pass is 40 times 11, or 440 responses. Four weekly passes use 1,760 responses. The Starter pool cited above is 3,600 credits at 1 credit per response and the card price is $295, so this pattern leaves 1,840 credits. Reading the rows back through the responses endpoint, each row includes a prompt_id, and the docs set page_size to a default of 40 and a maximum of 100, which means 440 rows are 11 pages at that default, according to AthenaHQ (2026). Those figures are arithmetic on the published credit rule and the published page size. They are not a measured customer result.

AirOps math uses a different unit, and the official example is the right anchor. One prompt on 3 one-unit engines, in 2 regions, with the default persona plus 2 named personas, is 540 answers and 540 tasks if none of those engines is Claude. Solo cannot host that example, because Solo is ChatGPT only, even though 35,000 tasks would otherwise hold it many times. On ChatGPT alone, the same 2 regions and persona factor of 3 are 180 tasks per prompt. One hundred ninety-four of those prompts use 34,920 tasks, which still fits in 35,000, and the one hundred ninety-fifth does not, because 195 times 180 is 35,100. Pro's 100,000-task pool would hold the 540-task pattern for 185 prompts with tasks left over, since 185 times 540 is 99,900, and the dollar price of that pool remains Quote-based.

Apply the Google AI Overview exception before you copy the formula into a spreadsheet. That surface ignores personas and runs once per region per day, so adding named personas does not multiply it. Claude does multiply, by 4. A plan that "includes Claude" can consume the pool much faster than a plan that includes another engine at the same prompt count. Write the engine list into the estimate. Do not estimate from the task cap alone.

The handoff after the tool

A proposed workflow from US Tech Automations is for the gap after the measurement tool has already stored the answers. The trigger is a scheduled CSV, or a successful responses export that includes website_id once the API add-on is turned on. The action groups rows where the brand was mentioned and not cited, and it opens one review item per prompt cluster. The output is a brief with the prompt text, the engines that skipped the brand, and the page someone thinks should change. A person has to approve that brief before anyone requests a CMS edit. Prerequisites are the export or the paid API add-on, a place to store the run, and a named reviewer. This is a design you can configure. It is not a statement about a current customer or a measured lift.

Where the source system is AirOps, US Tech Automations can take a finished workflow run that stayed inside the task balance and produced a draft. The action writes the draft, the task count, and the source URL into a review queue, and it stops when the run reports an error, because a failed step should not look like a published page even if a nested step succeeded and was billed. The output is an approval record. The human review point sits before any CMS write, including when a grid has already scored the draft. Prerequisites are a plan that includes the integration you will call, access limited to the reviewer, and a duplicate check so a second run does not open a second page for the same URL.

The realistic alternative is to connect the export yourself in Zapier, Make, or n8n, or to script it in-house. Those products can keep run histories, retries, error branches, and an audit trail when you configure them. You then design and own observability, idempotency, escalation, access controls, and the maintenance when a field name changes. A proposed US Tech Automations design puts the review gate, the stop-on-error rule, and the duplicate check into the flow up front, with the same prerequisites: a CSV or an API key, a named reviewer, and a stored decision before a publish step runs. If the only goal is a cheaper view of automation prices, stay with the workflow pricing guide linked above and skip the extra system.

Glossary

• Answer engine: a product that replies in prose, such as ChatGPT or Perplexity, rather than only listing links.

• AI search visibility: whether those replies name your brand and which pages they cite.

• GEO and AEO: two labels for shaping that record. The practical test is still a mention, a citation, and a page you changed.

• Credit: AthenaHQ's meter. The pricing card sets 1 credit equal to 1 AI response.

• Task: AirOps' meter for billable actions such as generating content or extracting data. Not every step is a task.

• Answer: on AirOps, one captured run of a prompt on a platform, region, and persona setup. Daily runs are why one prompt is not one answer.

• Citation: a source the answer points to. A mention names you. A citation links a page. Teams that care about the markup on that page often compare structured data tools for AI search as a separate checklist.

• Brand kit and knowledge base: AirOps containers for brand context. The card counts differ by tier and are listed in the pricing section above.

Mistakes that show up on the invoice

The most expensive mistake is comparing Solo to Starter as if they were the same shelf. Solo is one user and ChatGPT insights. Starter is a multi-model pool at a printed monthly price. A second mistake is reading the Pro button that invites you to start as if 100,000 tasks and 7 or more engines were a published free team plan. They are not. The dollar is Quote-based. A third is ignoring the Scale and Agency wording still sitting in the pricing questions. If the quote uses those names, map every limit back to a current card before legal reviews it.

On AthenaHQ, the matching mistake is assuming Enterprise features ride along at $295. SSO, multi-country tracking, the audit log, and the citation engine do not. Another is turning on a daily 11-model sweep because the pool "looks large." The twice-weekly row above leaves 80 credits from 3,600. A daily habit at that width will not fit, and the page does not print a price for the extra credits. On AirOps, forgetting the Claude multiplier has the same shape. Thirty answers become 120 tasks when the provider is Claude, in the one-region default example. Google AI Overview will not scale with personas, so a formula copied without that exception overstates that surface and understates Claude.

The last mistake is skipping the editor because an agent drafted the page. AthenaHQ's card does not describe an approval inbox comparable to the human-review line on AirOps' pricing matrix. AirOps lists the review and still leaves you responsible for using it. A quality score is not a signature. If nobody is named to reject a draft, do not automate the CMS write.

Questions before you sign

Are AthenaHQ and AirOps the same type of tool?

No. AthenaHQ is organized around tracking AI answers, competitors, and recommended actions, while AirOps is organized around producing and reviewing content against a monthly task balance.

Which tool has a public monthly price?

The Starter plan on AthenaHQ costs $295 per month on the card cited above, the Essential plan is free, and the Pro plan on AirOps is Quote-based.

Is a new free AirOps workspace the same thing as Solo?

No. The billing docs grant a new free-tier workspace 1 included task, while the Solo card lists 35,000 tasks a month, ChatGPT insights, and a single user.

Which plan covers more than ChatGPT?

The Essential plan on AthenaHQ names 5 models, the Starter plan names 11, the Solo plan on AirOps is ChatGPT only, and the Pro plan on AirOps says 7 or more answer engines.

What should you treat as Quote-based?

Treat the Enterprise plan on AthenaHQ, the Pro plan on AirOps, the Enterprise plan on AirOps, and the Starter add-ons for API access and extra credits as Quote-based, because those pages do not print a dollar amount for them.

When NOT to use US Tech Automations?

Skip the extra handoff when a CSV export or the vendor's own approval step already finishes the job, when you will not maintain a second system, or when one form-to-document automation is the whole workflow and nobody needs a stored approval.

How do you trial this without burning the cap?

Start with a short prompt list, multiply by the engines on that exact plan, and compare the product to the monthly allowance before you turn on a daily run. On Essential, two passes of 20 prompts across 5 models use 200 of 300 credits. A weekly pass of that same list uses 400 and does not fit.

The choice on the search is AthenaHQ when you need a published price and an answer record across many models, and AirOps when you need the production system and can accept a quote. Either way, do the credit or task math, keep an editor in the loop, and see how US Tech Automations configures this only if the handoff itself is the piece still missing.