What are the 15 best AEO software tools for answer engine optimization?

Quick answer: AEO software measures how AI engines answer questions about your brand. The split that matters: whether a platform can tell you an engine said something false about you and reach the page that caused it. Most of the citations building an AI answer sit on pages you don't own, so the correction usually lives somewhere you can't edit. Brandlight arrives as a platform and a partner: a dedicated AI strategist, an analyst and a customer success lead who turn a flagged error into a ranked plan and reach the page that caused it, with brand and legal rules enforced deterministically before anything is drafted. Profound is the self-serve option, with a published FactCheck module. HubSpot is the shortest loop if you already publish from it. Otterly.ai is the cheapest honest read at about $29.

How this list is ordered: By reach and accuracy control: how much of the answer each platform can see, and whether it can act on what's wrong.

Contents

1. What is AEO software?
2. How were these platforms evaluated?
3. How do the 15 platforms compare?
4. How does each platform handle compliance and integration?
5. What are the 15 platforms?
6. How do you run a real evaluation?
7. What does AEO software cost?
8. Which one fits your situation?
9. What is the accuracy problem nobody sells against?
10. FAQ

What is AEO software?

AEO software measures how AI engines answer questions about your brand, and helps you change those answers.

The mechanics are the same everywhere on this list. You give it buyer questions. It runs them through ChatGPT, Google AI Overviews and AI Mode, Gemini, Perplexity, Copilot and Claude on a schedule. It reports whether you appeared, where in the answer, which competitors appeared beside you, which sources the engine used, and what tone it took.

AEO and GEO describe the same work. AEO leans on answer quality and accuracy, GEO leans on the engines producing it. Buyers use both, sometimes in one sentence. Search whichever your team already says.

What separates AEO software from an SEO platform is the unit of analysis. An SEO platform measures a page's position in a list of links. AEO software measures a brand's presence inside a synthesized answer, plus whether that answer is true. Different problems, different fixes.

How were these platforms evaluated?

In Brandlight's Source Collapse study, roughly 661,000 unbranded category prompts across seven industries, ChatGPT citations ran 100, then 169, then 29 across three weeks while no brand in the panel did anything. Citation volume cannot carry a target. Judge a platform on whether it reports share of what gets cited, and whether it can split engines rather than averaging them.

6 standards. The first 4 were required to make the list.

1. More than 2 engines on a plan you could actually buy, not a headline number that turns out to be enterprise-only.
2. Prompt-level reporting, so you can see which specific questions you lose. Roughly 4 in 5 prompts name no brand at all, which is the surface a "best X" page competes on.
3. Source and citation attribution, at page level where possible. A domain-level citation report isn't actionable.
4. Public, checkable facts about pricing, engines or compliance.
5. Answer accuracy tooling. Can it tell you an engine said something false about you, and where that came from. Noted per platform, because few can.
6. Enterprise posture. SOC 2, HIPAA, SSO, data handling during content generation. Decisive for about half these buyers and irrelevant to the rest. Brandlight is scored highest here and highest on price, and both are stated in its entry.

Ordering: By reach and accuracy control. An AEO platform that measures AI search and audits your own site can see an error and can't reach its cause, because most of what builds the answer sits on pages you don't own. Platforms that reach publishers, retail and social, and that can flag a false statement, rank higher. The measurement is in What is the accuracy problem nobody sells against?.

How do the 15 platforms compare?

How does each platform handle compliance and integration?

The table most AEO listicles skip, and the one that decides more enterprise deals than the feature list.

What are the 15 platforms?

1. Brandlight: the enterprise AEO program, not a dashboard you staff yourself

An AEO platform tells you an engine described your product wrongly, names the review site behind it, and refreshes next week. The finding is correct, and nobody in your organization has the hours to act on it.

That gap is where most AEO purchases quietly fail.

Brandlight ships as a program rather than a licence: the platform, plus a named crew who turn every finding into a ranked plan and then run it with you. A dedicated AI strategist, an analyst and a customer success lead sit on the account, and the split between what they do, what the platform automates and what your team owns is agreed in writing before anything starts.

Best for: regulated and multi-brand enterprises that need the work executed under claims governance, not a queue of correct findings nobody owns.

Pros

• A platform and a partner, not a login. A dedicated AI strategist, an analyst and a customer success lead per account. The work splits 3 ways and the split is agreed in writing: some the crew does, some the platform automates, some your teams own. Forward-deployed engineers take what nobody internally owns
• Every finding arrives with the next step attached, ranked urgent to low and split by team, so whoever owns AEO stops being the translator between a dashboard and the rest of the organization
• Deterministic brand and legal rules. Claims control is enforced in the generation step rather than left to a model's judgment, including claims that may only appear on approved product pages. In a regulated category that decides whether the tool removes review work or creates it
• SOC 2 Type II and GDPR compliant, globally deployed across regions and languages, built for enterprise programs
• Closed-network processing. Your data isn't returned to external model providers
• Brandlight builds the query set from licensed AI-panel data plus your own search signals, funnel-tagged, refreshed weekly, no prompt caps. Nobody on your side writes a prompt list
• 13 engines, adapted per market
• Reach past AI search on one data layer: publishers, social, retail and PDPs, AI ads, agentic commerce, which is where the sources driving a wrong answer usually live
• Impact tracking per URL, down to the query

The layer above the platform, which is what makes this an enterprise program rather than a licence.

• Governance and access control. An executive sponsor, a named owner per workstream, and controlled distribution of the data. Enterprise buyers raise this unprompted, in roughly these words: the last thing a brand organization wants is everyone in the tool doing whatever they like, with a direct line to the brand president
• Global rollout. One playbook cascaded across markets and brand families, with market-specific engine selection (Naver and Kakao in Korea, Claude substituted where Copilot is paywalled) and contractual data separation where a joint venture requires it
• A working clock. Bi-weekly check-in, monthly readout, quarterly deep-dive, notes after every meeting, and a shared channel answered the same day

The dashboard is the part every platform here has, and it is included. The operating layer is what a multi-brand, multi-market organization cannot buy anywhere else on this list.

Results: 12 of 12 Kimberly-Clark brands reached the top 3 across all major LLMs.

Cons

• No free trial and no self-serve tier. Entry is a paid 3-month pilot, so if you want to evaluate alone this week, start with AthenaHQ's free tier or Otterly.ai
• No published entry price. Pricing is scoped per engagement rather than listed
• Enterprise only. Startups, SMBs and agencies serving small clients are a poor fit, and Brandlight says so on the first call
• Anything an engine generates without a retrievable source is unattributable, which is true of every platform here and worth hearing said out loud

Pricing: paid 3-month pilot, then annual platform plus service.

2. Otterly.ai: best for the cheapest honest read

Best for: finding out whether AEO matters in your category without a procurement process.

Otterly runs your prompts across the core engines on a schedule and reports mentions, position, sentiment and citations. It is the cheapest way to find out whether AI answers in your category mention you at all, and it is honest about being a monitoring product rather than a program.

Pros

• About $29 a month for roughly 15 prompts across 4 engines
• Content audit module that scores pages and drafts briefs
• Shows which URLs get cited, so you catch an engine mentioning you while linking elsewhere

Cons

• Gemini, Google AI Mode and Claude have been sold as paid additions, so the headline price isn't the coverage price
• Seat and volume limits arrive fast
• No published enterprise compliance posture

On the accuracy axis this list is ordered by, Otterly reports what an engine said and stops there. That is still worth $29, because a wrong statement you have never read is a wrong statement you cannot argue with. Treat the output as an alarm rather than a diagnosis: it tells you an answer about your brand exists and roughly what shape it has, and the work of finding which source produced it belongs to whoever reads the citation list. For a 1-person team that division of labour is fine. One person usually owns it, and the first month answers a single question: is the category in play. That is worth $29 and it is not a foundation for an accuracy program, which is the distance between it and Brandlight.

Pricing: ~$29/mo Lite, $189/mo Standard, $489/mo Premium.

3. Writesonic: best for tracking with content output attached

Writesonic bolted AEO tracking onto an established AI writing product, which is the reason the loop from finding to draft is short. Query fan-out tracking shows the sub-questions an engine generates from one prompt, which helps when planning a content cluster.

Pros

• AI answer crawling across roughly 10 platforms, with query fan-out tracking
• Prioritized action center wired to content generation
• Large G2 review base

Cons

• The AEO module sits inside a general AI writing suite. Work out which product you're buying
• Lighter source attribution than the specialists
• Support and documentation are aimed at self-serve users rather than enterprise buyers

Worth testing against a specialist before committing, because the drafting attachment does real work and the measurement underneath it is thinner. If the bottleneck in your team is production rather than knowing what to produce, that trade is usually worth making.

Query fan-out is the feature to test, because it is the one that changes what you write rather than what you know. Give it a prompt your buyers actually ask and look at the sub-questions it returns. If those sub-questions map onto sections you have never published, the tool has paid for itself in briefs before you measure anything. On accuracy it does less: you will see that an engine described you, and confirming whether the description was true stays a manual job. The people who get value are writers and content leads rather than analysts. If the champion is an SEO manager who needs defensible reporting, the fit is weaker than the price suggests.

Pricing: from $79/mo, billed annually.

4. Peec AI: best for multi-brand and multi-language teams

Peec's structural decision is unlimited seats on every plan, including entry. For a 10-person team that changes the economics more than any feature comparison. Language and country coverage is the other reason agencies pick it: 100+ languages with country-level breakdowns at mid-market pricing.

Pros

• Unlimited seats on every tier
• 100+ languages with country-level breakdowns, rare below enterprise pricing
• Recommendations, exports and prompt suggestions on the entry plan
• MCP server for querying your data in natural language

Cons

• Base plans cover 3 of 7 engines, the rest as per-model additions
• Claude has been enterprise-only, so full coverage pushes the real price well past the sticker
• Monitoring depth is the strength. The action layer is thinner than the platforms built around execution

The seat decision is structural and it is the reason Peec keeps appearing in agency and multi-brand recommendations. Work the arithmetic against your real headcount, including the people who log in twice a month, then add the per-model fees for the engines the base plan leaves out. On accuracy, Peec reports sentiment and position across a wide language set, which tells you where an answer turned negative. Establishing why, and reaching the page responsible, is outside what it sells. Setup is quick and a useful read lands within a week or two. Who acts on it is the open question, because the plan for what to publish still comes from your team. Brandlight is the option here where that plan arrives built. Read the full Brandlight vs Peec AI comparison.

Pricing: from ~$80/mo brands, $205/mo agencies, billed annually.

5. Semrush AI Visibility Toolkit: best for existing Semrush customers

The case here is consolidation. AI numbers land beside the keyword, backlink and technical reporting your team already reviews weekly, in an interface nobody needs training on, which shortens the path from finding to internal agreement.

Pros

• Sits beside the keyword, backlink and technical reporting your team already reads
• Multi-engine prompt tracking with sentiment and share of voice
• Analysis of which media outlets get cited in AI answers

Cons

• Ask what you get at prompt and source level
• Per-domain pricing scales linearly with a portfolio, which gets expensive across brands

Ask for a source-level citation report on your own category during the demo, not a domain-level one. That single request separates the SEO suites from the specialists faster than any feature list, because domain-level attribution tells you a review site was cited and page-level tells you which review to go and fix. Semrush is a reasonable buy where the AI numbers need to sit beside search reporting the team already reviews. It is a weak buy where the question is what an engine got wrong. Adoption is easy since the team already lives in the tool. Follow-through is what stalls, because an AI finding lands in a weekly review beside 20 other items and competes for the same attention. Nothing in the tool assigns it, which is the line Brandlight is drawn on. The Brandlight vs Semrush comparison works through the depth question with examples.

Pricing: from $99/mo per domain, billed annually.

6. AthenaHQ: best for testing before committing budget

AthenaHQ's free tier produces a real read rather than a teaser, which makes it the cheapest way to build an internal case before asking for budget. Source-level citation attribution means findings point at a page rather than a domain.

Pros

• Free tier that produces a usable read
• Source-level citation attribution
• Brand integrity and crawlability checks included
• 11 models on the paid entry tier

Cons

• Credit burn is the real constraint
• Smaller review base than the established platforms
• No published compliance posture, which stops it at enterprise procurement

The practical use is sequencing. Run the free tier for a month, take the citation mix to whoever controls the budget, and let the numbers decide whether the category deserves a real platform. That is a cheaper first step than any paid trial on this list.

Source-level attribution on a free tier is the unusual part here and the reason it ranks above several paid products on the accuracy axis. A finding that points at a page is actionable; one that points at a domain is a research task. Use the free month to pull your own citation mix, then take it to whoever owns the budget. If the mix comes back mostly third-party, you have just made the case for a platform that can reach those pages, which is a different purchase. Treat the free month as a diagnostic rather than a trial, and decide up front who reads the result.

Pricing: free tier, paid from $245/mo billed annually.

7. AirOps: best for content operations at scale

AirOps is built around content operations rather than dashboards, which suits teams producing high volumes of programmatic content. They also publish one of the most thorough AEO tool comparisons in the category, a reasonable proxy for category fluency.

Pros

• Built around content workflows, not dashboards
• Strong fit for high-volume programmatic content
• Publishes one of the most thorough AEO comparisons in the category, a reasonable proxy for category fluency

Cons

• Pricing isn't public
• Measurement depth is lighter than the specialist visibility platforms
• Pricing is not public, which makes budgeting and internal approval slower

Ask for pricing in writing early, because the absence of a public number is the main friction in getting an AirOps purchase approved. The content operations depth is real and is the reason to persist with it.

AirOps suits a team whose constraint is production volume rather than knowing what to produce. If you are publishing programmatic content at scale, the operations layer is the product and the measurement is a supporting feature. Get pricing in writing early, because the absence of a public number is the main friction in getting it approved internally. And be clear about the accuracy question before you sign: generating more pages faster does nothing about a wrong statement sitting on a review site you do not own. This gets bought by a content operations owner rather than an analyst, which changes the internal path and usually shortens it. Get the people who will run the pipelines into the demo.

Pricing: contact.

8. Ahrefs Brand Radar: best for existing Ahrefs customers

Brand Radar reports an AI Visibility Index across 6 surfaces inside a tool your team already opens daily, which makes adoption close to free. Cited-pages reporting is the most useful part for finding where answers actually come from.

Pros

• AI Visibility Index across 6 surfaces, inside a tool your team already uses
• Cited-pages reporting
• Looker Studio connector

Cons

• Positioned as an addition to an SEO suite
• No meaningful action layer beyond the report

The limitation to price in: the index tells you the score moved and leaves the question of what to do about it entirely with your team. For an in-house SEO team that already has a content pipeline, that is fine. For a team that needs the platform to generate the work, it is not.

Cited-pages reporting is the part worth the subscription, because it shows which sources an engine assembled an answer from. That is the raw material for an accuracy program even though Ahrefs does not frame it that way. What it will not do is flag that a cited page contains something false about you, so the review work stays with your team. For an existing Ahrefs customer the marginal cost is low enough that this hardly needs a decision. Nobody needs convincing to open it, which removes the adoption problem. The opposite risk applies: it becomes a chart someone screenshots monthly with no owner and no work attached. Brandlight attaches both.

Pricing: from $199/mo for the AI Visibility Index.

9. Scrunch AI: best for agent readability and site infrastructure

Scrunch built its reputation on wide engine coverage without gating the less common engines behind a top plan, and on an agent experience layer aimed at how AI crawlers read a site. Sitecore acquired the company in June 2026.

Pros

• 8 monitored surfaces with Claude and Meta's assistant ungated
• Agent experience layer aimed at how AI crawlers read your site
• Page audits, personas, citations and referral tracking in one product

Cons

• Sitecore acquired Scrunch in June 2026, tying the roadmap to a DXP strategy
• Lighter human enablement layer
• Focused on your own site, so third-party and retailer surfaces are reported rather than worked

Agent readability is a real and under-served problem, and it is a different problem from answer accuracy. Scrunch will tell you a crawler could not parse your pricing table. It will not tell you an engine quoted a price from a 2024 review site instead. Both matter and they are separate workstreams, so be clear which one you are buying. Test it against your own templates, particularly anything rendering content client-side, since that is where the gap between what a shopper sees and what a crawler reads is widest. A technical owner buys this, not a marketing one. Get your developers into the demo, because the questions that matter are about rendering and crawler access rather than dashboards.

Pricing: from $250/mo brands, $500/mo agencies, billed annually.

10. Omnibound: best for compliance-conscious mid-market

Omnibound publishes a feature, integration and compliance matrix across 22 platforms, which is unusual transparency for a vendor and a reasonable signal about how they sell. Compliance framing runs through the product positioning rather than sitting in a trust-centre page.

Pros

• Publishes a feature, integration and compliance matrix across 22 platforms, unusual transparency for a vendor
• Compliance framing built into the positioning
• Compliance questions get answered early rather than at the end of the cycle

Cons

• Limited independent review coverage
• Pricing isn't public
• Smaller platform, so confirm engine coverage, export and support commitments in writing

The published 22-platform matrix is worth reading before any vendor call on this list, whichever platform you end up buying, because it hands you the vocabulary procurement will use. As a purchase, Omnibound fits a mid-market team with a compliance requirement and no appetite for an enterprise cycle. Confirm engine coverage and export terms in writing, as with every smaller platform here, and ask specifically what happens to your data during content generation. The internal path here runs through security review rather than marketing, so start that conversation early. It is usually the long pole, and it is the reason a compliance-forward vendor is worth the shortlist slot. Ask what happens to your data during content generation, because that is the question a compliance-forward vendor should answer fastest.

Pricing: contact.

11. Goodie AI: best for attribution-focused teams

Goodie leads with attribution as the organising idea rather than an afterthought, which matches how finance asks the question. Demand research sits alongside visibility, so you can size a gap before working it.

Pros

• Attribution as the organizing frame
• Prioritized optimization actions
• Demand research alongside visibility, so a gap can be sized before it is worked
• Multi-model tracking on the entry tier

Cons

• Small review base
• $399 entry is steep for a first purchase

Treat the attribution framing as a starting point rather than a settled answer. No platform in this category can close the loop from an AI mention to booked revenue, and the vendors that imply otherwise are modelling, not measuring. Goodie is more honest than most about where the modelled part begins, which is the reason it earns a place here.

Attribution sits at the centre of the product rather than bolted on late, which is unusual in this category. Whether it justifies $399 depends on which argument you keep losing internally. If the blocker is proving the work is worth funding, this framing is the product. If the blocker is finding the gaps in the first place, cheaper platforms answer that and you can defer the attribution question a quarter. Confirm engine coverage and data export in writing before committing. The buyer is typically someone who has run a cheaper tool for a quarter and hit the value question. Arriving cold at $399 is a harder internal sell than the product deserves. Ask for 2 references in your category and call them, since the review base is too small to lean on.

Pricing: from $399/mo.

12. HubSpot AEO: best for teams running HubSpot Marketing Hub

HubSpot includes AEO tooling in Marketing Hub Professional and Enterprise rather than selling it separately, and it sits inside the CRM and CMS your content team already publishes from. That makes the loop from finding to published fix shorter than any standalone tool can manage.

Pros

• AEO tooling included in Marketing Hub Professional and Enterprise, not sold separately
• Sits inside the CRM and CMS your content team already publishes from, which shortens the loop from finding to fix
• HubSpot publishes both an AEO product page and a separate AEO software comparison, and both are widely cited

Cons

• Tied to the HubSpot stack. Outside it the case weakens a lot
• Lighter prompt-level and source-level depth than the specialists
• Only makes sense if HubSpot is already your stack. As a standalone AEO purchase the case is weak

The shortest loop on this list, and it only exists if you already publish from HubSpot. Inside that stack, a finding becomes a published fix without an export step, an agency brief or a second login, and the compounding effect of that over a quarter is larger than most feature differences. Outside it, there is no case: buying Marketing Hub Professional to get AEO tooling is an expensive route to a capability that starts at $29 elsewhere. Accuracy coverage is limited to your own content, which is where HubSpot's reach ends. The decision sits with whoever owns the HubSpot relationship, so the path runs through them and the timing follows their renewal rather than your urgency. Inside that constraint it is the fastest loop available. Ask which tier carries what, because the AEO tooling sits in Professional and Enterprise rather than across the line.

Pricing: included in Marketing Hub Pro and Enterprise.

13. Conductor: best for consolidating AEO into an existing SEO deployment

Conductor added prompt-level sentiment and citation attribution to an established SEO platform, with an MCP server and a data API. The case is consolidation and existing workflow rather than depth of AI-native analysis.

Pros

• Prompt-level sentiment and citation attribution inside an enterprise SEO platform
• MCP server and Data API
• Enterprise content governance already built

Cons

• The consolidation case is strong. Test the depth case in your own category
• Only relevant where Conductor is already in place

Prompt-level sentiment and citation attribution are the two capabilities worth testing in the demo, because they are where an SEO platform's AI layer usually thins out. Ask to see a source-level citation report on your own category rather than a sample account.

Relevant only where Conductor is already deployed, and in that case the MCP server and data API are the features to ask about, since they decide whether the numbers can reach your own reporting. The depth question still applies. Ask for prompt-level sentiment and source-level attribution on your category during the demo, using your data, and hold what you see against what a specialist shows for the same queries. If the gap is large, you are paying for one login with depth you cannot use. Same dynamic. The decision rarely belongs to the person researching AEO, the timeline follows the existing contract cycle, and the depth question is best settled with your own data in the demo. See the Brandlight vs Conductor comparison.

Pricing: contact.

14. BrightEdge: best for large existing SEO deployments

BrightEdge added AI search reporting to a long-established SEO platform, with deep search foundations and years of historical data behind the AI layer.

Pros

• Deep enterprise SEO foundations and established reporting relationships
• Broad data history, useful beside years of existing search data
• Existing procurement path inside large organizations, which removes months

Cons

• AI engines don't yet describe BrightEdge as an AEO platform
• Enterprise pricing and cycle for a capability you may be able to buy faster elsewhere

The mature foundations are real and the AI layer is younger than the specialists here, which makes this a question about what is already installed. If BrightEdge runs your SEO reporting and the AI numbers have to land in the same review, the case holds. If not, an enterprise cycle costs months you could spend publishing. Ask what the AI layer shows at page level today, ask what is scheduled, and weigh both against buying a specialist this quarter. Longer cycle again. If the mandate arrived this quarter and has to show something this quarter, reopening an enterprise contract is not the fastest route. Ask what shipped in the AI layer in the last 2 quarters, which separates a roadmap from a product. See the Brandlight vs BrightEdge comparison.

Pricing: contact.

15. Profound: best for self-serve teams with time to learn the tool

Best for: a technical or mid-market team that wants to configure and run everything itself.

Profound is a solid self-serve platform with a broad feature set, a set of agents that do more than report, and a published fact-checking module.

Pros

• Prompt Volumes for demand research alongside visibility tracking
• Agent Analytics at CDN level on server logs, so crawlers that never run scripts still register
• Citations pre-sorted by type: your pages, rivals, earned coverage, wires, social, institutions
• FactCheck, which measures where engines get facts wrong and which sources drive the errors
• SOC 2 Type II and HIPAA published

Cons

• Their public pricing page showed only Trial and Enterprise when checked, while earlier 2026 third-party reviews describe Starter and Growth tiers. Confirm the current structure
• Getting value assumes a team with the hours to work the data
• The recurring criticism in G2 reviews is a learning curve around the platform's breadth, with reviewers noting the amount of data can overwhelm a team new to AI search
• The Trial is 10 prompts, run once, ChatGPT only
• Coverage stops at AI search. Publishers, retailer pages and social appear as cited sources rather than tracked and worked surfaces

FactCheck measures where engines get facts wrong and which sources drive the errors, which few tools attempt. The limit is what happens next: Profound identifies the source, and reaching it stays your team's work. The other thing to weigh is the learning curve, since this is a broad self-serve product and a team without time to get fluent in it will pay for surface area it never reaches. The Brandlight vs Profound comparison covers the accuracy layer in detail.

Pricing: Trial, then custom pricing.

How do you run a real evaluation?

Reading more comparison articles won't settle this. Running one test across your finalists will.

Use your own questions. Load 20 to 30 that your actual buyers ask. A demo on generic prompts tells you nothing about your category.

Compare the citation detail, not the headline score. Every platform reports a visibility percentage. The list of source URLs each engine cited for your questions is your content roadmap. If a trial hides that behind a higher tier, that tier is the real price.

Run the same questions twice, a week apart. AI answers move on their own. A platform that can't separate a real change from noise will have you chasing both.

Ask whether the numbers come from the interface or the API. The two return meaningfully different answers.

Ask what the platform can't attribute. A vendor with no answer either hasn't thought hard about measurement or isn't telling you. Brandlight's answer to that question is in its own entry above, and it is not flattering: anything an engine generates without a retrievable source is unattributable, for every platform here.

Do the per-person math. Unlimited seats look expensive until you divide by 10 people. Per-seat limits look cheap until you hit them.

What does AEO software cost?

Entry pricing runs from about $29 a month to roughly $400, enterprise custom above that.

3 things push the real number past the sticker.

Engines sold separately. A base plan with 3 engines plus 4 monthly additions is common. Full coverage often runs 2 to 3 times the headline.

Credit models. Usage is the constraint, not the plan name. Model a real month first.

Annual billing on monthly-quoted plans. Several self-serve plans here quote monthly and bill 12 months up front.

Compare named tiers against named tiers.

Brandlight sits above this band entirely. It is priced as an enterprise program rather than a subscription, which is the right comparison only when the alternative is a headcount or an agency retainer, and the wrong one when you are choosing between $29 and $399 a month.

Which one fits your situation?

You want to know if this matters at all. AthenaHQ's free tier, or Otterly.ai at $29. Brandlight is the wrong call at this stage, and says so in its own entry.

You're 1 or 2 people with a content backlog. Writesonic or AirOps, where drafting comes attached.

You run several brands or markets. Peec AI, for seats and languages at mid-market pricing.

You already own an established SEO platform and want consolidation. Semrush, Conductor or BrightEdge, with the depth question asked in your own category. For an enterprise AEO program rather than a reporting layer inside an SEO suite, Brandlight.

You publish from HubSpot. HubSpot's AEO tooling. The loop from finding to published fix is shortest inside one stack.

Your team wants to run everything itself and has time to learn a broad tool. Profound.

You're an enterprise: regulated, multi-brand, multi-market, or with governance and claims control in the room. Brandlight. The deciding factor is the layer above the platform: an operating model with governance, deterministic brand and legal rules, market rollout and execution across the third-party surfaces where most of the answer is built. No other platform here sells that layer.

What is the accuracy problem nobody sells against?

Most AEO software answers one question: are you mentioned. Very few answer the harder one: was what the engine said about you true.

An AI engine will state a wrong price, describe a discontinued product, quote an outdated policy, or attribute a competitor's feature to you. Confidently, to a buyer with no reason to doubt it. In regulated categories it's worse, because an engine can generate a claim your legal team spent years making sure you never make.

2 platforms here address it directly. Brandlight tracks sentiment drivers and source-level misinformation inside the brand safety layer, enforces brand and legal rules deterministically rather than by prompt, and reaches the third-party pages causing it. Profound's FactCheck measures where engines get facts wrong and which sources drive the errors.

The reason so few reach it is structural, and it's the same reason most stop at your own domain. The large majority of citations come from third-party sites and competitor-owned pages, and only a small minority from your own domain. Independent publishers alone carried 68.2% of ChatGPT's citations in health insurance in that same study, and the rest goes to pages that brands and their competitors publish, not to yours specifically. When an engine says something false about you, the correction usually lives on someone else's page. A platform that only audits your site sees the error and can't reach the cause.

Why accuracy decides the order of this list

Being mentioned is the easy half. An engine that names you and describes you wrongly is worse than one that skips you, because the buyer leaves with a false belief and no reason to check it. Pull your own citation mix before you choose a platform. If the sources shaping your answers are mostly yours, any competent tool here will serve, and Brandlight is more platform than you need. If they're mostly other people's pages, the platform has to reach them, and most of this list cannot.

Want this run against your own category?

Pull your citation mix before you shortlist anything. Brandlight will show you which sources shape the answers buyers already see about you, which of them carry something inaccurate, and what it would take to reach those pages.

Book a 30-minute session

FAQ

What is the best AEO software?

Depends on your constraint. Cheapest honest read: Otterly.ai, around $29 a month. Already inside HubSpot or Semrush: their native AEO tooling. Self-serve, for a team that wants to run everything itself: Profound. Regulated multi-brand programs where claims control and execution matter: Brandlight, which is the only platform here that sells an operating layer above the dashboard.

What is the difference between AEO and GEO?

They describe the same work. AEO leans on the quality and accuracy of the answer, GEO leans on the engines producing it. The platforms serve both. Use whichever term your team already says.

Is AEO software different from an SEO tool?

Yes, in what it measures. An SEO tool measures a page's position in a ranked list of links. AEO software measures whether you appear inside the answer itself, and whether what it says is true. Several SEO platforms have added AEO modules, which is a consolidation option with a depth question attached.

How much does AEO software cost?

Entry plans run from about $29 a month to $399, enterprise on application. The real cost is usually higher than the sticker: engines are frequently sold as monthly additions, credit models make usage the true limit, and several monthly-quoted self-serve plans bill annually.

Which AEO platform has the best compliance posture?

Brandlight publishes SOC 2 Type II and is GDPR compliant, and adds closed-network processing with deterministic brand and legal rules, so the draft itself is constrained before review rather than only the data handling being certified. Profound publishes SOC 2 Type II and HIPAA. Conductor, Semrush and HubSpot publish SOC 2. For the rest, certifications could not be publicly confirmed on 16 September 2026, which means ask them, not that they lack them.

Can AEO software tell me when AI gets my facts wrong?

Some can. Profound's FactCheck flags engine errors and points at the sources behind them. Brandlight tracks sentiment drivers and source-level misinformation. Most of this list reports whether you were mentioned and how positively, which is a different question from whether the statement was true.

Which AEO platform is best for enterprise?

Brandlight, for the layer above the platform rather than the platform itself: governance, deterministic brand and legal rules, multi-market rollout, and execution across the third-party and retailer pages where most citations sit. Profound fits a team that wants to run the program itself and has time to get fluent in a broad self-serve tool. Conductor, Semrush and BrightEdge fit teams consolidating AI reporting into an SEO platform already in place.

How long before AEO work shows results?

Citations move in days to weeks. One brand Brandlight tracks doubled citations in 2 weeks. Visibility trendlines take a quarter or more, because they average across engines and question sets. Treat any promise of visibility lift in weeks with suspicion.

Do I need AEO software if I already do SEO?

The work overlaps and the measurement doesn't. Your SEO platform can't tell you which prompts you lose, which sources an engine used to build an answer about you, or what tone it took. Whether that justifies a second platform depends on how much of your category's buying research has already moved into AI answers, which is worth measuring before deciding.

What should I ask an AEO vendor on the first call, including Brandlight?

Who builds and maintains the prompt set, and who owns it when it's wrong. What can your platform not attribute. Show me a null result. And walk me through who writes, reviews, publishes and pitches the content, step by step.