To compare one AI search optimization agency with another, score each on the same five questions: what it produces every month, which AI engines that work targets, how it measures citations against pipeline, what governance sits between a draft and your brand in public, and how its price maps to scope. Most vendors in the category sell a tracker, a content service or a mix of both, and they use the same acronyms for all three. Shortlists therefore often compare a dashboard with a managed program as if the two were interchangeable.
This guide defines the terms vendors blur and applies one scoring framework to four options that buyers compare as of October 2026: one managed program and three platforms that agencies and in-house teams operate. It also covers pricing, verification, red flags and realistic timelines. If you are choosing an AI search optimization agency, you should finish with questions you can put to any vendor on a first call.
Key takeaways
- An AI search optimization agency should be judged on what it produces each month, not on the size of its tracking dashboard.
- Trackers such as Profound, AthenaHQ and Semrush show where a brand is missing from AI answers, while a managed program such as Tellr does the work that changes those answers.
- AI visibility data is probabilistic, so a credible vendor shows its prompt set, its collection method and how it handles answer drift.
- Citation share is a leading indicator, and the business case still rests on AI referral traffic, branded search lift, assisted pipeline and what prospects tell sales.
- Small teams usually get more value from a self-serve tracker, while enterprises with $10k+ monthly budgets and brand risk to manage get more from a governed managed program.
What an AI search optimization agency actually does
An AI search optimization agency works to get a brand cited, mentioned or recommended inside AI-generated answers from ChatGPT, Perplexity, Gemini, Claude, Copilot and Google AI Overviews, alongside its rankings in classic search results. Traditional SEO ranks pages. AI search work gets a page selected as a source, and AI answers cite a small set of authoritative domains. That shifts attention from domain-level authority toward page-level signals: clear structure, named sources in the body, specific claims and evidence a model can verify.
The terms vendors use, and how they differ
| Term | What vendors usually mean | What to check |
|---|---|---|
| AI SEO | Umbrella label for SEO adapted to AI answers; sometimes just SEO done with AI writing tools | Whether the work targets AI citations or only uses AI to produce content faster |
| GEO (generative engine optimization) | Shaping content and off-site presence so LLM-based engines quote it | Which engines are in scope and how inclusion is measured |
| AEO (answer engine optimization) | Answer-shaped content for direct answers, featured snippets and AI Overviews | Often overlaps with GEO; ask for examples of cited pages |
| LLMO (LLM optimization) | Influencing how models describe a brand, including training-data presence | Claims about "getting into training data" need evidence |
| AI visibility optimization | Usually tracking-led: mentions, share of voice, sentiment | Whether anyone produces the fix after the report |
| Citation optimization | Earning links from AI answers to your pages or to third-party sources that favor you | Whether Reddit, review sites and publications count, or only your own domain |
Services you should expect to see in scope
- Technical work: crawler access for AI bots, crawl-error fixes, site structure, speed, HTTPS and schema markup.
- Content: comparison pages, reviews and answer-shaped articles with one clear intent per page, original data and expert input.
- Entity and trust signals: consistent brand entities across the site, author credibility and E-E-A-T markers.
- Off-site presence: digital PR, review sites and community threads (Reddit in particular) that AI answers cite.
- Measurement: tracking of mentions and citations across engines, tied to traffic and pipeline reporting.
How optimization differs by engine
Engines retrieve sources differently, so an agency that treats them as one channel will miss gaps.
- Google AI Overviews and AI Mode draw on Google's index, so classic SEO strength carries over, and Reddit and forum discussions often appear among the cited results. Gemini is grounded in Google Search as well.
- Copilot draws on Bing's index, which makes Bing indexing and Bing Webmaster Tools worth checking.
- Perplexity shows its citations openly, which makes it the easiest engine to audit.
- ChatGPT and Claude mix web retrieval with what the model already knows about a brand, so consistent third-party descriptions of your product matter as much as your own pages.
How to compare AI search optimization agencies
Score every vendor against the same criteria and ask for evidence on each one. Case studies each pick a different metric, so reading them side by side tells you little. The framework below turns the five questions from the introduction into criteria. For more on shortlisting, see our guide to picking a generative engine optimization agency.
| Criterion | Question to ask | What a strong answer looks like |
|---|---|---|
| Execution | What do you produce in a normal month, and who produces it? | Named deliverables (pages, replies, creative) with counts and owners, not "recommendations" |
| Engine coverage | Which engines and surfaces do you track or write for, and how do you collect answers? | Engines listed, plus the collection method: API, browser sessions or panel data |
| Measurement | How do you connect citation share to pipeline? | Citation share per query cluster, plus AI referral traffic, branded search and sales feedback |
| Governance | What checks happen before anything goes live under our name? | Brand brief, claim guardrails, approval gate, audit trail of what was placed where |
| Pricing fit | What is the pricing unit, and what does it include? | A clear unit (domain, credits, engagement) and a scope document with deliverables |
Governance deserves more weight than most buyers give it. Regulated and security brands already expect audit-grade controls from AI providers. The Cloud Security Alliance, for example, publishes auditing guidelines for evaluating controls across GenAI service delivery layers. An agency posting in Reddit threads or publishing comparison pages on your behalf should meet a similar standard of traceability.
How the options in this guide were selected
The four options represent the operating models enterprise buyers most often weigh against each other:
- A managed earned-visibility program: Tellr.
- An enterprise visibility platform: Profound.
- A tracker built around action recommendations: AthenaHQ.
- An AI visibility module inside an established SEO suite: Semrush.
Facts come from each vendor's published materials and independent reviews. Ratings are G2 scores as of October 2026, shown only where reviews exist. Three of the four are software that an agency or in-house team operates. They are included because many "agencies" in this category resell or run exactly these tools, and buyers should know which layer they are paying for.
Ask every vendor one question early: "If we cancel, what do we keep?" Published pages, live Reddit replies and creative files stay with you. A dashboard subscription does not.
Tellr, Profound, AthenaHQ and Semrush compared
Tellr is a managed program that produces the content, replies and creative. Profound, AthenaHQ and Semrush are platforms a team operates itself, and they differ in how much content help they give.
| Option | Operating model | Produces the fix | Measurement focus | Pricing unit | Evidence level | G2 rating |
|---|---|---|---|---|---|---|
| Tellr | Managed by a senior team on Tellr's platform | Yes: published content, Reddit replies, ad creative | Weekly citation share on Google and AI Overviews | Per engagement, scoped on a demo | Public method and onboarding process | No G2 rating yet |
| Profound | Self-serve enterprise platform | Content briefs, drafts, page rewrites, outreach materials | Mentions, citations, share of voice, sentiment, position, AI referral traffic | Custom enterprise quote | SOC 2 Type II; large review base | 4.6/5 (1,124 reviews) |
| AthenaHQ | Self-serve platform | Action Center recommendations plus content tooling | Same six metrics, refreshed daily | Credit-based tiers | Small review base | 5.0/5 (48 reviews) |
| Semrush | Self-serve module in an SEO suite | No: insights and opportunities only | Mentions, citations, share of voice, position | Per domain, plus add-ons | Largest review base | 4.5/5 (3,945 reviews) |
Tellr
Tellr is a premium earned-visibility agency for enterprises. A senior team runs one governed program covering four jobs most companies buy from separate vendors: Reddit marketing, content built for AI search, AI and search visibility tracking, and paid-media creative. Each week it tracks the category's queries on Google and records the organic results, the AI Overview and the discussions block. It labels every cited domain as your site, a competitor, Reddit, social, review sites or references. Its comparison pages, reviews and answer-shaped articles are built from the brand's knowledge base and real user reviews. They are written to be quoted by ChatGPT, Perplexity, Gemini, Claude and AI Overviews, and published straight to the client's CMS.
- Produces the pages, Reddit replies and ad creative itself, and uses tracking to decide what to make next.
- Builds in governance with a brand brief, claim guardrails, risk filtering, approval gate, audit trail and takedown support.
- Refuses growth-hack tactics such as upvote buying, aged accounts and fake reviews.
- Reports each Reddit reply placed and whether it is still live, with weekly reporting and a monthly program review.
Tellr needs a few weeks to map the category and agree the brief, so it does not suit a launch that needs results in three weeks.
Profound
Profound is an enterprise AI visibility platform covering ChatGPT, Perplexity, Gemini, Claude, Copilot, AI Overviews and AI Mode. It collects answers through a mix of API, browser sessions and panel data, and its core index updates weekly. It also produces briefs, drafts, rewrites and outreach materials, though your team operates it. Its enterprise controls are the most complete of the platforms here: SSO, roles, approval workflows, audit trail, multi-brand workspaces and SOC 2 Type II. G2 reviewers in October 2026 most often praise prompt tracking, citation and source analysis, and competitor benchmarking.
Pros
- Covers more engines and uses more collection methods than any other option in this comparison.
- Has strong enterprise governance features and a 7-day trial with 50 prompts per day.
Cons
- Reviewers call pricing expensive, and lower tiers restrict coverage, history and API access.
- The volume of data takes time to learn, and some users question how reliable scraped answers are.
AthenaHQ
AthenaHQ was founded by engineers from Google Search and DeepMind. It tracks the same seven surfaces, mainly through API integrations, and refreshes data daily. Its Action Center turns gaps into prioritized tasks, and G2 reviewers say this is why they act on the data instead of only reading it. Reviewers also note regional segmentation that helps multi-market retail brands. The vendor lists SSO, roles, approval workflows, audit trail and SOC 2 among its enterprise features. Its 5.0 G2 score comes from only 48 reviews, so treat it as an early signal.
Pros
- Recommendations point to specific content gaps, and reviewers describe support as same-day.
- A permanent free tier includes 300 credits across 5 AI surfaces.
Cons
- The prompt library has no industry templates, so tracked prompts are built from scratch.
- Credit pricing is hard to budget, and generated content can need heavy editing.
Semrush
Semrush's AI Visibility Toolkit adds AI tracking to the SEO suite many teams already pay for. It covers the same seven surfaces, mainly via API, with daily prompt rankings and weekly brand and share-of-voice data. It integrates with GA4, Search Console and WordPress, and offers an API and an MCP server. G2 reviewers increasingly call its AI Overview and AEO tracking valuable. It surfaces opportunities but does not write briefs, publish pages or run outreach.
Pros
- Teams already on Semrush can start with the least setup.
- Semrush One adds multi-brand and multi-region reporting.
Cons
- Reviewers cite limited regional, language and engine depth for global use.
- Costs climb with extra domains, prompts and users, and the toolkit has no free trial.
Pricing models and what each budget buys
AI search optimization is priced in three ways: per domain or credit for self-serve trackers, custom quotes for enterprise platforms, and per engagement for managed programs. The pricing unit tells you who does the work.
| Model | Example from this guide | What you get | Who does the monthly work |
|---|---|---|---|
| Per domain plus add-ons | Semrush: about $99/month per domain billed annually; $45/month per extra user; $60/month per 50 prompts | Tracking and opportunity lists | Your SEO and content team |
| Credit-based tiers | AthenaHQ: free Essential tier, then credit tiers and a custom enterprise quote | Tracking, recommendations, content tooling | Your team, guided by the platform |
| Custom enterprise platform | Profound: custom quote after the trial | Tracking, briefs, drafts, governance controls | Your team or an agency running it |
| Managed engagement | Tellr: scoped on a demo for teams spending $10k+ a month, at companies worth $500M+ or with 200+ employees | Published content, Reddit replies, creative, weekly tracking | The vendor's senior team, with your approval |
A tracker subscription is not the full cost. Someone still has to write the comparison pages, get subject-matter experts to review claims and earn third-party mentions. Price that labor before you compare a software line item with a managed fee. Our breakdown of what belongs in the statement of work lists the deliverables to pin down. For the build-versus-buy question, see how enterprises choose between an agency or in-house team.
Hire, buy or build? Buy a tracker if you have writers and SEO capacity and only lack data. Hire a consultant if you need a strategy and prompt set your team can run. Choose a managed program if the bottleneck is output across Reddit, content and creative, and brand risk requires approvals and an audit trail.
Is an AI search optimization agency legit? How to verify claims and spot red flags
A legitimate AI search optimization agency can show its prompt set, its collection method, examples of content that AI engines actually cite and a link from that work to pipeline. Vague claims of "AI visibility growth" are not enough.
What to ask for before signing
- The prompt or query set they would track for your category, grouped into clusters such as comparisons, alternatives and "best for" queries.
- Screenshots or exports of tracking for a current client, showing cited domains and week-over-week movement.
- Three live pages they produced that are cited in AI Overviews or Perplexity today, which you can check yourself.
- Before-and-after topic coverage: which queries had no owned citation, and which do now.
- Content samples showing SME input, such as interview notes turned into claims, product differentiation backed by evidence and sourced figures.
- Evidence of business impact: AI referral sessions, assisted opportunities or SQLs, and named or referenceable clients.
Red flags
- llms.txt presented as the main strategy rather than a minor technical item.
- No prompt methodology, or a prompt set that changes between reports without notice.
- AI-written articles with no subject-matter expert review.
- Reddit "growth" through upvote buying, aged accounts or fake reviews.
- Reports that count mentions or impressions as outcomes, with no line to traffic or pipeline.
- Hidden fees, or a scope described only as "optimization".
Measuring beyond mentions
Citation frequency per query cluster and share of model visibility against named competitors are leading indicators. A CFO will care more about the lagging ones:
- AI referral traffic in GA4, segmented by sessions from chatgpt.com, perplexity.ai, gemini.google.com and copilot.microsoft.com.
- Branded search lift in Search Console.
- Assisted conversions in your CRM.
- A "how did you hear about us" field that sales reps fill in when prospects mention ChatGPT or Perplexity.
Where tracking falls short
AI answers are probabilistic. The same prompt can return different sources minutes apart. Answers vary with location, login state and conversation history, and model updates can shift citation patterns overnight. Prompt sets drift too, as teams add queries and break week-over-week comparisons. Treat any single reading as a sample and judge trends across clusters. NIST's work on frameworks for evaluating AI systems makes the same point: measuring model behavior needs repeated, structured testing rather than one-off checks.
What to expect at 30, 90 and 180 days
| Window | Realistic progress |
|---|---|
| First 30 days | Category map, agreed brief and guardrails, baseline citation share, first pages and replies live |
| By 90 days | New pages indexed and ranking; first owned citations in AI Overviews and Perplexity; Reddit replies holding in high-intent threads |
| By 180 days | Citation share moving across clusters, measurable AI referral traffic, and early pipeline signal in CRM and sales notes |
How Tellr fits an enterprise AI search program
Tellr runs alongside an existing SEO and paid team. Your team owns strategy and approvals, and Tellr's senior team produces and places the work on a fixed weekly rhythm. Week one delivers a category map of the threads, queries and AI answers that matter, and week two agrees the brief and claim guardrails. After that, drafts arrive weekly for approval, results are reported weekly, and a monthly review sets the next priorities. Each brand has its own workspace, which suits multi-brand portfolios.
- Your SEO lead uses the weekly citation-share data to see which domains Google and AI Overviews cite.
- Content and product marketing approve pages built from your knowledge base and real user reviews.
- Brand and legal review every Reddit reply against the guardrails before it goes live.
- Paid media receives category ad intelligence and ready-to-run creative.
- Leadership gets a record of what was placed where.
Which option fits which company
No single vendor is best for everyone. The right option depends on company size, risk profile and whether the bottleneck is data or output.
| Company type | Best-fit model | Why |
|---|---|---|
| Enterprise B2B (cloud security, AI software) | Managed program such as Tellr | High-stakes comparison queries, Reddit scrutiny and a need for approvals and an audit trail |
| Regulated industries | Managed program, or Profound run in-house | Claim guardrails, approval workflows and audit trails are required |
| Consumer and ecommerce brands across markets | AthenaHQ or Profound, plus content capacity | Regional segmentation and broad engine coverage |
| Early-stage SaaS | Semrush toolkit or AthenaHQ free tier | Low cost; founders and small teams can do the writing themselves |
| Local and founder-led services firms | Self-serve tracker or a freelance consultant | A managed enterprise program is more than a business this size needs |
Find your row, then run the five framework questions on every vendor left on the shortlist, and ask each one what you keep if you cancel. A team that can staff the writing and SME review needs data. A team that cannot needs output with guardrails. Whichever route you take, judge an AI search optimization agency on the pages, replies and pipeline it can show you, not on the dashboard it demos.
FAQ
How should you compare AI search optimization agencies?
Score every vendor against the same five criteria: execution, engine coverage, measurement, governance and pricing fit. The article argues that buyers should compare what a vendor actually produces each month, which AI engines it targets, how it connects citation share to pipeline, what approval controls exist before anything goes live, and how pricing maps to scope.
What is the difference between a tracker and a managed AI search program?
A tracker shows where your brand is missing from AI answers, while a managed program does the work that can change those answers. In this guide, Profound, AthenaHQ and Semrush are platforms that teams operate themselves, whereas Tellr is the managed option that produces pages, Reddit replies and creative on the client’s behalf.
How can you verify whether an AI search optimization agency is legit?
Ask to see the prompt set they would track, their collection method, screenshots or exports showing cited domains over time, and live examples of pages they produced that are cited in AI Overviews or Perplexity today. The article also recommends asking for evidence that connects citation gains to AI referral traffic, assisted opportunities or pipeline impact.
What red flags should buyers watch for?
Warning signs include treating llms.txt as the main strategy, hiding the prompt methodology, publishing AI-written articles without subject-matter expert review, using Reddit manipulation tactics such as upvote buying or fake reviews, and reporting mentions or impressions without any link to traffic or pipeline. A vague scope described only as “optimization” is another red flag.
How long does AI search optimization usually take to show results?
The guide suggests realistic milestones at 30, 90 and 180 days. In the first 30 days, teams should expect a category map, guardrails, a baseline and the first pages or replies live. By 90 days, new pages may be indexed and earning first citations. By 180 days, citation share should be moving across clusters, with measurable AI referral traffic and early pipeline signals.