Best SEO and AEO agencies for AI startups (2026)

You sell a model, an agent, or an AI-first application. Your buyers ask ChatGPT and Perplexity which vendors to shortlist before they ever open your website. Most agencies selling GEO, AEO and AI search optimization publish no client whose product is the AI itself.

Short answer: for AI startups the shortlist is LoudFace, NoGood, Breaking B2B, Omniscient Digital, DerivateX and Veza Digital, and LoudFace fits teams that want the site, SEO and AI search run as one program. Those five are the other agencies that name an AI-native client on their own pages, and Veza's two are website and documentation projects. generative.qa and First Page Sage target the segment without naming an AI-native client, and the one client First Page Sage names in the segment is an AI-powered identity-verification company. iPullRank, Percepture, Single Grain, Revlift and Search Agency name none.

Every other agency is described from pages it publishes about itself, quoted as its own claim, fetched on 10 September 2026. We audited none of those results.

What do AEO, GEO and AI search optimization actually mean?

Three labels, one discipline. AEO is answer engine optimization. GEO is generative engine optimization. AI search optimization is the plainest of the three. They all describe work that aims to get a company named, cited and recommended inside an AI-generated answer instead of a blue link.

The label matters less than the vocabulary your buyers use. ChatGPT and Perplexity fan a buyer question out into related searches before they answer it, so the words on your pages have to match the words in those searches. Our breakdown of AEO, GEO and SEO draws the line this way: AEO and GEO name two different places an answer shows up, and both describe the same job.

All thirteen name at least two AI engines they work on. None of them sells Google alone any more.

How we ranked these agencies

Five checks, applied to every agency from its own public pages. No agency was scored out of ten, because a public page does not carry enough evidence to defend a number per competitor.

1. Does it name an AI-native client? An AI-native company sells a model, an agent or an AI-first application. A company that uses AI in its marketing does not count. This one check removed more than half the field.
2. Does a published result carry a time window? A percentage with no window is a number you cannot check or plan against.
3. Is a price published? Not every good agency publishes one. An agency that does has made a commitment you can hold it to.
4. How many engines does it name? An agency that names only ChatGPT is reporting on a fraction of your buyers' behaviour.
5. Is there a page for AI companies? A segment page is weak evidence on its own. Paired with a named client it becomes strong.

Every claim here is quoted from the agency's own site. A result stated without a window is marked as such, and so is an agency that publishes no price. None of it is an independent audit of anyone's client results.

The 13 agencies, ranked

1. LoudFace

Best for: an AI-native startup that needs the website, the content and the AI-search work run as one program, measured per engine. Bluefyn, whose product is AI that verifies charges and invoices, moved more than 5x on AI visibility across two 30-day windows less than three months apart.

LoudFace is a full-stack organic growth agency for B2B SaaS and fintech, with AI visibility measured per engine. Three of its clients sell AI products. Bluefyn (bluefyn.ai) describes itself as "the proof layer for money in motion: AI that verifies every charge and every invoice against the contract that governs it". On a fixed set of tracked buyer prompts, comparing the programme's first 30 days against the latest 30 days, its AI visibility rose more than 5x and its share of voice rose more than 5x. ChatGPT visibility rose more than 13x, and average position when named improved to under 2. Share of voice is measured against the full tracked competitor set. Under three months separates the two windows.

Pond (joinpond.ai) runs an AI workforce marketplace, and its numbers come with a caveat stated in the same breath: across the first four weeks, from a near-zero base, AI visibility tripled, share of voice rose 4x, and average position when named improved from about 3 to about 2. Four weeks is a standing start, and a small base flatters a multiplier. Its share of voice is measured against Pond's own tracked competitor set.

Eraser (eraser.io) describes itself as "AI for diagrams that matter", and its own site states, "Create technical diagrams using AI". The Eraser case study covers a website redesign and the maintenance work that followed it, and it publishes no percentage, no multiplier and no window, so there is no AI-search figure to quote.

The Genie Teacher case study, in education rather than an AI-native category, records AI share of voice growing from 2.26% to 12.94% between 25 May and 24 August 2026, at an average mention rank of 1.0 to 1.4, against its tracked competitor set. That case study also states the gap in its own data: "Tracking paused 1 Jun – 13 Jul; the line bridges that gap." The stealth fintech case study records AI visibility growing from 0.53% to a 10.46% peak in seven weeks, settling at 8.00% by 24 August 2026, and publishes its own sample-size caveat.

Pricing is public. Engagements start from $5k /mo, scoped to your goals. The published buyer definition is narrower than AI startups in general: B2B SaaS, fintech, and funded companies from Series A to C.

Where it is not the right fit: if you want a paid-media growth partner, NoGood and Single Grain run that as their main business.

2. NoGood

Best for: a funded AI product company that wants brand-scale growth marketing and can carry a premium retainer.

NoGood is the only agency among the thirteen with a frontier-lab name on its own home page: its client list includes Anthropic, AWS, MongoDB and Oura. No Anthropic case study or result is published beside the name, so treat the logo as a logo.

The one full AI-native case study is Inflection AI, whose product Pi is an AI companion. NoGood states it "helped Inflection AI achieve over 1 million daily active users within 3 months". The figures beside that line are paid-acquisition and app-download figures rather than AI-search citation figures, which is worth knowing before you buy AEO from it.

It runs the most explicit AI-company segment page of the thirteen, an "AI marketing agency for category defining startups and scaleups", and claims segment experience without naming the startups. Its price sits in prose: "Our average retainer is above $20,000/month". The dedicated pricing URL returns a 404, so that sentence is the only figure disclosed.

Where it is not the right fit: its published AI-native result is measured on paid acquisition and app downloads rather than on AI-search citations.

3. Breaking B2B

Best for: an early-stage AI company that wants a published rate card and a comparable AI-search result before signing.

Breaking B2B names an AI-native client and defines it as one: Chattermill is "an AI-native B2B SaaS platform that helps consumer brands analyse customer feedback at scale". The result is the closest published analogue to the question an AI startup actually asks. Chattermill "went from a 20% to an 80% AI search mention rate in a few months, and started fielding enterprise RFPs from brands who found them through ChatGPT and Gemini". The timeline underneath that headline names the months: January at "roughly a 20% mention rate across relevant AI searches", May at "Mention rate up to 80%", on a story datelined July 2026.

It publishes the most complete rate card of the thirteen agencies. Growth tiers run from $5,500/month to $20,000+/month, enterprise tiers from $8,500/month to $40,000+/month, with tailored plans from $4,000/month below both. Its startup page targets early-stage B2B and SaaS founders in general, and the phrase AI startup does not appear on it.

Where it is not the right fit: mention rate is Breaking B2B's own metric, defined on its own pages, so it does not compare with a share-of-answer reading from anyone else.

4. Omniscient Digital

Best for: an AI product company with real budget that wants content-led organic growth run by a B2B software specialist.

Omniscient names Jasper, "an artificial intelligence writing tool that helps you write content faster", and its headline pairing is loud: "Jasper grew organic sessions 810% and product signups 400X". No window appears beside those numbers on the home page, and the case study gives only a relative one tied to the engagement.

Its published LLM-visibility pair belongs to Convert, which Omniscient's pages name without describing what it sells: LLM visibility up 81% and AI citations up 140%, again with no stated window. A second AI-named client, Gable AI, carries a descriptive line, "Built category leadership and captured demand with strategic SEO", and no number. Pricing is a single floor repeated on four pages: "Full-service engagements start at $10,000 a month". Positioning is B2B software breadth rather than an AI-startup segment.

Where it is not the right fit: the Jasper figures on its home page carry no window at all, and its published floor is $10,000 a month.

5. DerivateX

Best for: a technical company that wants a named prompt-testing method, a published retainer, and an AI-native name on the roster even though no result is published beside it.

DerivateX names fifteen clients and describes each by category. One of them sells an AI product: Prophet Security, filed under "cybersecurity", whose own home page sells "AI SOC Agents Built to Outwork Modern Attackers" and names an "AI SOC Analyst" as the product. DerivateX publishes no result attributed to it. The others include Gumlet in video infrastructure, REsimpli in real estate CRM, Verito in cloud hosting and Kroto in sales enablement. It publishes an AI and ML industry playbook with no client attached, and its framing is unusually blunt about where an AI buyer looks: "ML engineers ask Claude before they ask you". Its method is stated as a number: "We test 20 prompts your buyers ask across ChatGPT, Claude, Gemini and Perplexity."

The published results carry windows, and both belong to clients that are not AI products. Within 90 days, REsimpli "went from absent in AI answers to being the #1 cited CRM for investors across dozens of high-intent prompts", under a heading that names ChatGPT and Perplexity. DerivateX attributes a share of Gumlet's inbound revenue to AI discovery: "20% of Gumlet's inbound revenue now comes from users who first discovered the brand through ChatGPT and other AI tools". DerivateX dates that engagement at eight months on the case study and at twelve months on its home page, so ask which it is. Its entry retainer is "$5,000 per month", and it publishes a standalone $3,500 diagnostic for buyers who want the audit, query map and content strategy before a retainer.

Where it is not the right fit: the one AI-native name on its roster, Prophet Security, has no published result beside it.

6. generative.qa

Best for: an AI startup that wants a fixed-fee $3,500 diagnostic before committing to a retainer. DerivateX publishes a standalone $3,500 diagnostic too, so that price is not unique to generative.qa.

generative.qa is the only firm here whose whole identity is your segment. It calls itself "The GEO Firm Built for AI Startups" and spells out the buyer motion: GEO for SaaS companies and AI startups, to "appear in AI-generated comparisons, recommendation lists, and category overviews that drive enterprise purchasing decisions".

Across seven pages fetched there is no named client, no case study and no client-attributed result. The operational numbers it publishes are delivery durations and allocation targets rather than outcomes, and none is attached to a client.

Prices are public and anchored against software: it notes that "Enterprise GEO platforms charge $8,000-$15,000/year", its dashboard "starts at $79/month", and its own consulting entry point is "USD 3,500 for a 3-day audit". Its retainer price appears once, on the content-strategy page: "Content creation is included in the GEO retainer at the $8,000/month tier". Two fixed-fee sprints are priced above the audit: "USD 7,500 for a 5-day sprint" on that same content-strategy page, and "USD 12,500 for a 7-day sprint" on the SEO-integration page. Buy the audit and ask for a reference before you go monthly.

Where it is not the right fit: nothing published gives you a reference to call, so the $3,500 audit is the only way to test the work before a retainer.

7. First Page Sage

Best for: a large AI company happy with anonymised proof and a two-year horizon.

First Page Sage runs a segment page that combines AI with software development rather than addressing AI startups alone. Its AI sub-segment is described as "Category and use case campaigns for products whose buyers ask AI itself what to shortlist", which is the right sentence.

Its AI-native client is real and anonymous: "an AI writing and communication assistant used by tens of millions of people daily". That page publishes a windowed result, with qualified business leads growing "from 214 per month to 1,480 per month over two years".

Its second GEO case study is written as anonymous yet names Microblink once in the body, and Microblink is an AI-powered identity-verification company rather than a generative-AI product company. That same page publishes two different end-state figures for one engagement: it reports 61% recommendation share under Year 1, described in prose as growth "from 8% at kickoff to 61% by the end of Year 2", while under Year 2 it says the client "was recommended in 23% of tracked high-intent AI-platform queries, up from 8% at kickoff". Ask which is right before you rely on either. No retainer price is published on any page fetched, though it does publish a GEO cost breakdown built from a survey of other firms.

Where it is not the right fit: it publishes no price, and its second GEO case study reports two different end-state figures for one engagement.

8. iPullRank

Best for: an enterprise-scale AI company that wants technical depth and does not need a named reference.

iPullRank anonymises every case study by industry: a financial services study, a telecom study, an ecommerce marketplace study. Across five pages fetched, the only client company named at all is American Express, and only as a testimonial byline.

The mechanism it publishes is the most technically specific of the thirteen: it engineers visibility "in ChatGPT, AI Overviews, and AI Mode by understanding how GEO actually works: query fan-out, passage retrieval, embeddings, and synthesis". That sentence is a better signal than most case studies a buyer will read in this category.

Its anonymised finance study reports "Over 121% Cumulative increase in Sign-ups (6 Months)" beside a 52% organic traffic increase carrying no window of its own. Its ecommerce study states its window as year over year, reporting more organic search sessions, a 43.5% improvement in the number of transactions and a 175% increase in revenue. No price is published. The dollar figures on its cost page are third-party survey benchmarks rather than its own rates, plus three worked examples of its own, including "(75 people-hours x $150 per hr.) + ($5,360) + (30% agency markup) = $21,593".

Where it is not the right fit: across five pages fetched it names no client company except a testimonial byline, so you get no reference to call.

9. Percepture

Best for: a company that wants a published tier ladder and a monthly report on AI mentions, sentiment and referral traffic, from the one agency here that names Grok among its engines.

Nine of the thirteen agencies here publish a price of some kind, and Percepture's is a named tier ladder: "Starts at $3500/mo", with named tiers at $3,500, $6,000, $8,500 and $10k+ per month. It names five engines, and states the stakes plainly: "ChatGPT, Google AI Overviews, Gemini, Grok and Perplexity are now where people start their research, and if your brand isn't showing up in those answers, you're invisible."

No AI-native client is named on any page fetched. Two named clients carry windowed results, and neither result is an AI-search reading: its headline testimonial from Chayora puts traffic up 485% in 4 months, and a staffing firm, Broadstaff, reached "90% page-one keyword visibility and 3x qualified lead growth within 12 months". Its strongest AI-search numbers are anonymised, including "a 3000% increase in AI mentions in 3 months" for an unnamed tech client.

Where it is not the right fit: no AI-native client is named on any page fetched, and its strongest AI-search figure is anonymised.

10. Veza Digital

Best for: an AI startup that mainly needs a website and documentation experience built well.

Veza runs a page addressed to AI companies as a segment, and it names two clients it describes as AI products on its case-study index. Crossing Minds is the clearest: "Documentation experience developed in Webflow for Crossing Minds' AI recommendation API." Tesorai is the second. Both entries are website design and development work rather than AI-search work, which is the honest read of what you would be buying.

Its largest published AI-search numbers belong to Concordium, a blockchain protocol, and they are the LLM figures: "+363%" LLM sessions, "+366%" engaged LLM sessions and "+500%" LLM key events, all from GA4, with no time window stated on that page. The organic pair on the same page, "Organic sessions increased by 144% and engaged sessions by 134%", covers the whole search ecosystem rather than the AI channels alone, and Veza says so in the sentence it appears in. Its Grata study does carry a window, "within just six months", and Grata is a deal-sourcing platform. Its own case-study tagging is unreliable, so read the text rather than the tag. No price is published. Every project is scoped individually.

Where it is not the right fit: both entries it describes as AI products are website and documentation builds rather than AI-search work.

11. Single Grain

Best for: a company that wants AI-search work bundled with broad performance marketing.

Single Grain names five engines and has real AI-search proof from companies that are not AI products. Its Smart Rent study, on a smart-home platform, reports "100+ new citations across all major AI platforms" inside one month. Its Winedeals study is ecommerce and not an AI-search result at all: a programmatic SEO programme that published 200 high-intent pages and lifted click-through rate 325%, from 0.8% to 3.4%, in three months.

Among its published clients, the AI-product affiliation is a testimonial byline from Kim Cooper, Director of Marketing at Amazon Alexa. No AI-native company appears among the published case studies, and it publishes no price of its own.

Where it is not the right fit: no AI-native company appears among its published case studies, and it publishes no price of its own.

12. Revlift

Best for: a founder who values plain dealing and a published price ladder more than a client roster.

Revlift names zero clients, and it explains why in its own words: "These are first-party results on products we operate, not client case studies. We won't fabricate those." That is more honest than most anonymised case studies a buyer will be shown.

Its published citation figures therefore belong to Revlift's own properties over a trailing three-month period, sourced to Bing Webmaster Tools. That is evidence the team can do the work on a site. It is no evidence of a client result, and none at all of an AI-startup result. It publishes a full price ladder from "$1,500/mo" up, including its two top tiers, which the page badges "Coming soon", and addresses founders generically rather than any AI-company vertical.

Where it is not the right fit: every published figure comes from Revlift's own properties, so there is no client result and no AI-startup result.

13. Search Agency

Best for: a company selling into Indonesia and South-East Asia that wants AI-search work with local pricing.

Search Agency has genuine windowed AI-search results, all on consumer brands. Its headline is 450% AI search audience growth for DiscoverASR, a hospitality brand, "in a single quarter", alongside 3.7x AI search footprint growth for Prenagen over twelve months. A third windowed figure, 2M+ new users for Kompas.ID in six months, it files under organic growth rather than AI search.

Its named verticals are travel and hospitality, and FMCG and consumer, with an explicit catch-all: "Banking, e-commerce, healthcare, property, whatever your category, the method is the same." That is a reasonable claim for a consumer brand and a weak one for a company selling a model to engineers. Pricing is tiered, quoted in rupiah with dollar equivalents.

Where it is not the right fit: every windowed result it publishes is on a consumer brand, which is weak evidence for a company selling a model to engineers.

How do ChatGPT and Perplexity decide what to cite?

Ranking on Google and getting cited by an AI engine are largely separate events. Ahrefs measured the overlap across 15,000 long-tail queries and found that "only 12% of links cited by ChatGPT, Gemini, and Copilot appear in Google's top 10 results" for the same prompt. An agency that reports only Google positions is missing most of your problem.

The mechanism that decides most B2B shortlists is third-party lists. Peec analysed nearly 200,000 AI responses across eight engines and concluded that "being present in the right third-party listicles is the most critical hurdle". Rank inside the list then decides how much of that hurdle you clear: in B2B SaaS, rank 1 carries a 16.5 percentage point lift. Getting into other people's lists, in a good position, is real work with a measurable payoff.

Access comes before any of it. OpenAI runs three separate agents for three separate jobs. "OAI-SearchBot is used to surface websites in search results in ChatGPT's search features", so that agent decides your search eligibility, while GPTBot exists to train foundation models and ChatGPT-User fetches a page when a user's question calls for it. Perplexity draws the same line, with PerplexityBot for search and Perplexity-User for user-triggered fetches. Blocking the training crawler does not block the search crawler, and plenty of AI startups have blocked both by accident.

Google publishes no separate entry ticket. It states that "there are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary", and describes its AI features as issuing "multiple related searches across subtopics and data sources". That second sentence is the practical instruction. One long page does not answer a fan-out. A set of pages that each resolve one buyer question does.

Google retired the FAQ rich result from Search in May 2026, though the FAQPage vocabulary itself is alive and still machine-readable. And the click economics have shifted: in an April 2025 study across 300,000 keywords, Ahrefs found that "the presence of an AI Overview in the search results correlated with a 34.5% lower average clickthrough rate". Judge an agency on answers won. Sessions gained is no longer the number that matters most.

What changes when the product is the AI

An AI-native sale runs through people who never appear in a marketing funnel. A security reviewer with a questionnaire. An engineer with a free trial. A legal owner asking what you indemnify. Each one stops at a different page, and each page either answers them or loses the deal quietly.

The artifacts they read are documentation. The model card travels with the product, described in the original paper as a short document "accompanying trained machine learning models that provide benchmarked evaluation in a variety of conditions". On Hugging Face it is a file in the repository, and its metadata "supports discovery and easier use of your model". The repository is a discovery surface too: GitHub states that "a README is often the first item a visitor will see when visiting your repository", and topics exist so buyers can explore a subject area.

Governance arrives early. Buyers name the NIST AI Risk Management Framework, which NIST describes as a framework to manage risks "to individuals, organizations, and society associated with artificial intelligence". Procurement asks for a SOC 2 report. If your product interacts directly with people in the EU, or generates synthetic text, audio, image or video, Article 50 of the EU AI Act sets transparency duties that apply from 2 August 2026, written around what reaches "a natural person who is reasonably well-informed, observant and circumspect".

None of that is standard agency work, which is why the check for a named AI-native client matters. Our guide to SEO, AEO and GEO for AI startups sets out the pages this buyer opens, and our developer tools work covers the engineer half of the audience.

LoudFace's evidence for AI startups

Three of our clients sell AI products. Two of them, Bluefyn and Pond, have movement measured on a fixed prompt set rather than a hand-picked screenshot, and both sets of figures carry their windows. Pond's programme is four weeks old and started from a near-zero base, so its multiplier describes a small base. The third is Eraser, a website build and maintenance engagement with no AI-search figure published.

The method behind both is a per-engine read. A blended AI number hides which engine is losing. Visibility and position are reported by engine because they move separately. Share of voice is measured once, against the tracked competitor set. On the Bluefyn programme ChatGPT climbed hardest by multiplier, more than 13x, while Google AI Overviews gained the most percentage points, and a blended figure would have shown neither.

We publish our limits on the methodology page, including where we hold no evidenced revenue figure yet. We would rather you read that than a chart with no denominator under it.

What LoudFace runs: organic and AI search under one team, and no paid media. If your buyers are consumers, Search Agency has the consumer-brand record.

How should you choose between them?

Work down four questions in this order.

Has it worked with a company like yours? Six agencies here name an AI-native client on their own pages: LoudFace, NoGood, Breaking B2B, Omniscient Digital, DerivateX and Veza Digital. Only LoudFace and Breaking B2B attach a published AI-search result to one of those clients. DerivateX names Prophet Security with nothing beside it, Veza's two are website builds, and everyone else is a maybe.

Can it show you the window and the denominator? Without a sample size, a percentage tells you nothing about how many answers were checked. Ask for the prompt list, the engines, the number of answers sampled and the dates. Our checklist on verifying an agency's results is the version we would hand a friend.

Does it report per engine? ChatGPT, Perplexity, Gemini and Google's AI surfaces behave differently and move at different speeds. One blended number hides the engine you are losing.

Can it fix the entity problem? If engines cannot tell your company apart from a common noun or a better-known namesake, nothing else works. Our guide to entity disambiguation covers that work.

Profound is software, and buying it is a different decision

Profound appears in this category because AI engines cite it, though it describes itself as "the full stack marketing platform for the marketer of the future" rather than an agency. Its customer story on OpusClip, an AI video clipping tool, reports brand visibility and citation share gains in 30 days plus a 37% increase in new user signups from answer engines, achieved through self-service software rather than agency delivery. Tools measure. People still have to do the work.

Where to start

Pick the two questions your buyers ask an AI engine most often, run them in ChatGPT and Perplexity today, and write down who gets named. That list is your real competitive set, and it rarely matches your pitch deck. Then check whether the search crawlers are allowed in, and whether the pages a security reviewer needs exist at all.

If you want that scored against your competitors with one fix you can ship this week, start with a free AI visibility audit. Retainers are a separate decision. Engagements start from $5k /mo, and the pricing page sets out how the plans are structured.