AthenaHQ plans compared on what 3,600 credits a month buys, and the cost per recorded answer across eight vendors

AthenaHQ is worth it for the buyer who wants to start metering assistant answers this week without a sales call, and the reason is one published sentence rather than a feature. Read on 31 October 2026, its plans page states that one credit is one AI response, gives the Starter plan 3,600 credits a month at 295 dollars, and offers a free tier carrying 300 credits and 25 dollars of free credit. A defined unit and a published count is all you need to price the work per answer, which is the only way two quotes in this market can be compared at all.

The three plans as published

Published row	Free	Starter	Enterprise
Price	free, with 25 dollars of credit	295 dollars a month, annual toggle shows 17 per cent off	custom
Credits	300 included	3,600 a month	custom allocation
Engines	5, named as ChatGPT, Perplexity, AI Overviews, Gemini, Copilot	11, adding AI Mode, Claude, Grok, DeepSeek, Meta AI and Mistral	11 plus more on request
Topics, prompts, competitors	prompt and response analysis	unlimited topics, prompts and competitors	unlimited
Countries	single	country level support, single	multi region and multi language
Seats	unlimited	unlimited, with role based access control	unlimited, with audit logs
API access	no	paid add-on billed on top, price not stated	included
Single sign on	Google and Microsoft OAuth	Google and Microsoft OAuth	SAML and OIDC, 2 hour SLA

Two lines deserve the attention. Unlimited seats on every tier, including the free one, is unusual in this category and it is a genuine advantage for a team that wants the whole marketing department looking at the same dashboard. And API access is an add-on with no published price, which the page says plainly: API access and extra credits are billed on top of the Starter subscription rather than included in it, and you have to ask what they cost. Saying so on the page is better behaviour than leaving it to the first invoice, and it is still a figure you cannot plan around today.

What 3,600 credits a month actually covers

Because the unit is one AI response, the sizing arithmetic is yours to do in a minute. Spread across the eleven models Starter carries, 3,600 credits is about 327 responses per model a month, or around ten a day. Put the other way round: a question set of 100 prompts read once a week on all eleven models consumes about 4,400 credits a month and is already over the quota, while the same 100 prompts on four models weekly consumes about 1,600 and fits comfortably. So the Starter plan is a good fit for a focused prompt set on many models, or a wide set on few models, and the decision is which of those two shapes your market needs.

At 295 dollars for 3,600 responses, the computed cost is about 8.2 cents a recorded answer. That number is what lets you compare AthenaHQ with anybody, and it is the table below.

Cost per recorded answer, computed from published figures on 31 October 2026

Vendor and plan	Published price	Published count	Computed cost an answer
Evertune Pro	800 dollars a month, billed annually	100,000 prompt credits a month	about 0.8 cents
Ahrefs prompt package, Scale	250 dollars a month	25,000 checks a month, overage 1.0 cent	about 1.0 cent
Evertune Starter	60 dollars a month	5,000 prompt credits a month	about 1.2 cents
Goodie Core	295 dollars a month	110 prompts on 5 models, collected daily	about 1.8 cents, computed from a daily cadence
Scrunch Core	250 dollars a month	5,000 responses a month	about 5.0 cents
Ahrefs Brand Radar index	199 dollars a month	2,500 checks a month	about 8.0 cents
AthenaHQ Starter	295 dollars a month	3,600 credits a month	about 8.2 cents
AI Knows Us Scale, ours	599 dollars a month	4,667 credits a month	about 12.8 cents
AI Knows Us Growth, ours	299 dollars a month	1,600 credits a month	about 18.7 cents
Profound, Conductor, Brandwatch, Brandlight	no figure published	Conductor publishes 2,500 AI search credits a year	not computable from the page

We are the most expensive company in that table on cost per recorded answer, by a wide margin, and that is the honest reading of it. Our plans are not metering subscriptions: Growth publishes 20 pages written and published to your site a month, Scale publishes 40, with pitches to the sites assistants cite and help asking customers for reviews. A buyer who wants only the readings should buy readings, and five of the vendors above sell them more cheaply per answer than we do. A buyer who wants somebody to act on the readings is comparing different things, and the per answer column is the wrong column for that decision.

Where AthenaHQ beats us, said plainly

Four lines. Eleven engines against our five apps. Unlimited seats on every plan against one login with full access on all of ours, and we publish no SAML single sign on at any tier where AthenaHQ publishes it on Enterprise. A published annual discount of 17 per cent in the served page, where our annual figure sits behind a button. And a genuinely free tier with 300 credits, where our free offering is a scan rather than a standing credit balance.

Two lines go the other way. Our pricing page prints every plan in six currencies in the served HTML, which matters if you are buying from outside the United States, and our unit sentence includes the exception that costs money: a Claude check is 3 credits rather than 1. AthenaHQ defines a credit as one AI response and does not publish a per engine weighting, so a Claude heavy prompt set is a question to put on the call.

Questions buyers ask about AthenaHQ plans

Is the free tier usable or a demo?

It is 300 credits, which is 300 recorded AI responses, across five named engines with unlimited users. That is enough to read a real answer set once and decide whether the paid plan is worth 295 dollars, which is more than most free tiers in this category allow.

Is 295 dollars a month good value?

On cost per recorded answer it sits in the middle of the eight vendors above, at about 8.2 cents. It buys eleven engines and unlimited seats at that price, which is where the value sits rather than in the credit count.

What does the API add-on cost?

Not published. The page states twice that API access and extra credits are add-ons billed on top of the Starter subscription, and says to contact them for add-on pricing. If an API is part of your requirement, get that figure before you compare Starter with anybody.

How should I size the credits?

Multiply prompts by engines by readings a month. One hundred prompts across eleven engines once a week is about 4,400 credits and exceeds Starter, so either narrow the engine list or buy the extra credits knowingly.

Who should look at Enterprise instead?

Anybody who needs SAML or OIDC single sign on, audit logs, more than one region or language, or a 2 hour support SLA. Those four lines are the published difference, and three of them are procurement requirements rather than preferences.

Why a defined unit is the thing to shop for

Half this market quotes a monthly figure without saying what one reading is, and the other half quotes a reading count without a price. AthenaHQ publishes both and tells you the one thing that is excluded, which is why it can be compared with eight rivals in a table rather than discussed in a meeting. Run that table with your own prompt count in it before any demo, including the row for us, and accept what it says: if the job is only to meter the answers, several vendors are cheaper per answer than we are. We are worth the difference when somebody also has to write the pages that change the answer, and that is a separate decision from the one this page is about. The startup cut of the same roster runs it for a buyer with no budget approval at all.

How we know this

We read the assistants rather than guessing what they do. In our own audit of 1,260 saved answers from ChatGPT and Gemini across the United States, the United Kingdom and India, 82.0% of every citation landed on a site the business itself owned, and review directories took 0.7%. Counted as one domain per reading, 16,516 of 20,143.

That is the whole asymmetry: the pages you own are the pages an assistant quotes back to a buyer. See the dated readings and the method on our proof page.

Find out whether assistants name your business, on your own domain and your own buying questions.

By Aditya Goel, Founder, AI Knows Us. Reviewed 1 November 2026.