B2B SaaS has a specific AI search problem, and most generalist agencies are not set up to solve it.
Your buyers do not ask "best project management software" once and buy. They run a months-long evaluation, asking an AI model a sequence of increasingly specific questions: which tools integrate with their stack, which handle their compliance requirement, which one people switch to when they leave the incumbent. Being named in the broad category answer is worth far less than being named in the twenty narrow comparison answers that follow it.
Omni Eclipse is an AEO agency and appears in this comparison. That is a conflict of interest. We have applied the same rubric to ourselves as to every other firm, published our own drawbacks, and marked our pricing with the same evidence label. Read the methodology first, and discount our own entry accordingly.
Why B2B SaaS needs a different approach to AI search
Three things make SaaS harder than a typical local or ecommerce AEO engagement.
The buying committee asks different questions. A technical evaluator, a finance approver and an end user each query differently about the same purchase. Covering only one of those intents leaves most of the committee unreached.
Comparison queries dominate. Much of SaaS discovery happens as "X versus Y" or "alternatives to Z". Those answers are assembled from review platforms, comparison content and community discussion, much of which sits outside your domain.
Attribution is genuinely difficult. A model recommendation may influence a deal that closes months later through a branded search. If your reporting only counts last-click, AI visibility looks like it did nothing.
Gartner predicted at its 2025 IT Symposium that by 2028, 90% of B2B buying will be AI agent intermediated, pushing over $15 trillion through AI agent exchanges (Gartner, Oct 2025).
Semrush's study found LLM traffic converts 4.4x higher than organic search (Semrush, Jun 2025). Ahrefs published their own SaaS data showing AI search visitors converting up to 23x better, with 0.5% of traffic driving 12.1% of signups (Ahrefs, Jun 2025). That second figure comes from a small denominator on a single product, so treat it as directional rather than a benchmark, which is how Ahrefs themselves frame it.
How we scored these agencies
The rubric is weighted for SaaS specifically. An agency that is excellent for local services may score poorly here, and that is the rubric working correctly rather than a judgement on their general quality.
| Criterion | Weight | What earns a high score |
|---|---|---|
| Buyer-question coverage | 25% | Works the full evaluation sequence, not just category queries |
| Pipeline attribution | 20% | Ties AI visibility to opportunities, not sessions |
| Comparison surface work | 20% | Actively works review platforms and alternatives content |
| Engine coverage | 15% | Tracks multiple engines, not one |
| SaaS domain fluency | 10% | Understands technical products and buying committees |
| Transparency | 10% | Publishes method, states who it is not for |
Evidence labels are used the same way throughout: Verified means confirmed against a public source, Claimed means stated but not independently confirmed, and Not published means no public figure was found.
This is not a league table based on measured client outcomes. No agency in this category publishes comparable outcome data at a standard that would support that claim, including us. Positions reflect fit against the published rubric above. If you weight the criteria differently, the order changes, and it should.
Quick fit guide
| Your situation | Prioritise | Best fits |
|---|---|---|
| Early-stage, category undefined | Entity clarity and category association | Omni Eclipse, Discovered Labs |
| Product-led growth motion | Self-serve buyer questions and activation | RevenueZen, Minuttia |
| Sales-led with long cycles | Pipeline attribution and committee coverage | Directive, RevenueZen |
| Enterprise or regulated SaaS | Governance, technical depth, compliance | iPullRank, Brainlabs |
| Thin content foundation | Editorial capacity at volume | Siege Media, Minuttia |
| Funded and scaling fast | Integrated growth with AEO inside it | NoGood, Graphite |
The ten agencies
Directive
California / GlobalDirective is built around B2B SaaS and ties AI search performance to pipeline and revenue rather than stopping at visibility scores. Programs include conversion tracking against AI answer citations and prompt-level dashboards, which addresses the attribution problem that makes most SaaS AEO reporting unconvincing to a CFO. Pricing: not published (Not published). Drawback: the model assumes clean data foundations and internal analytics resourcing. If your attribution infrastructure is unreliable, early budget goes into fixing that before any AEO work can be credibly measured.
Omni Eclipse
Globally distributed, HQ in UAEA pure-play AEO agency covering ChatGPT, Google AI Overviews, Perplexity, Gemini and Claude, with prompt-gap audits designed to find the specific evaluation questions a SaaS brand is missing from. All three co-founders work directly on accounts, and the sprint model targets measurable AI answer inclusion in 4 to 8 weeks. Pricing: not published, quoted per scope (Verified: we do not publish a rate card). Drawback and conflict note: we wrote this page. We are a specialist rather than a full-funnel B2B agency, so if you need demand generation and paid media in the same retainer, a broader firm fits better.
Minuttia
Remote (US)Minuttia built its reputation specifically in B2B SaaS content strategy, and the AEO approach follows the same content-led philosophy: citation-worthy assets built around specific buyer questions, produced with subject matter experts rather than generalist writers. That expert-led process is what makes the output usable as a cited source. Pricing: not published (Not published). Drawback: the expertise is concentrated in SaaS, which is an advantage here but means the methodology is less transferable if your portfolio spans other verticals.
RevenueZen
Portland, Oregon, USARevenueZen approaches AEO through product marketing, building citation strategies around product-led growth frameworks. That framing suits SaaS businesses where the product itself is central to the buyer query, and pipeline-focused reporting connects visibility to revenue rather than impressions. Pricing: not published (Not published). Drawback: a smaller team than the larger firms here. Businesses needing enterprise capacity for large-scale content production or simultaneous multi-market rollouts may find delivery speed a constraint.
iPullRank
New York, USAFounded by Mike King, iPullRank is the most documented technical operator in AI search, working on large complex sites across SaaS, ecommerce and media. For SaaS products with substantial technical documentation, large application surfaces or complex information architecture, the depth is genuinely differentiating. Public proof: extensive published technical writing (Verified). Pricing: minimum engagement reported at $50,000 and above (Claimed). Drawback: that minimum excludes most early and mid-stage SaaS companies, and the depth is wasted on a simple marketing site.
Discovered Labs
United StatesDiscovered Labs builds citation strategies specifically around the vendor-evaluation questions B2B buyers put to AI systems during a purchase process, which is the exact surface where SaaS deals are won or excluded. The vertical focus is genuine rather than positioning. Pricing: not published (Not published). Drawback: a newer agency with a shorter documented track record than established names here. Ask specifically for before-and-after citation results from comparable SaaS engagements before signing a retainer.
NoGood
New York, USANoGood built Goodie, their own AI tracking platform, giving them stronger proprietary measurement infrastructure than most agencies at their level. AEO sits inside a broader growth marketing framework, which suits funded SaaS companies wanting one partner across paid, content and AI visibility. Public proof: proprietary platform and documented case studies (Verified). Pricing: not published (Not published). Drawback: AEO competes for attention with other service lines. Buyers wanting specialist AEO-only depth may find it diluted.
Brainlabs
London / GlobalFormerly Distilled, Brainlabs pairs technical SEO with editorial authority building, centred on entity architecture, centralised schema strategy and enterprise measurement. For SaaS organisations with many stakeholders, multiple product lines and a real governance requirement, that structure is the differentiator. Pricing: not published (Not published). Drawback: the enterprise investment level outpaces what most early and mid-stage SaaS companies need, and buyers outside the UK should verify regional localisation and compliance handling directly.
Siege Media
San Diego, USAOne of the strongest content production operations in the US, applied to AEO with a focus on high-volume citation-worthy editorial. The right call when the gap is genuinely a missing content foundation rather than a technical or entity problem, because few agencies can build that foundation as efficiently. Pricing: not published (Not published). Drawback: the AEO work is content-first, and technical depth on schema and entity architecture is less prominent than the editorial capability. Confirm the technical layer separately if you need both.
Graphite
United StatesGraphite applies AI tooling to growth marketing broadly, combining AI-assisted content production with distribution and tracking. For SaaS companies that need volume and have internal strategy capability, the production model can be efficient. Pricing: not published (Not published). Drawback: AEO is not the primary specialisation. In a generalist growth model, AI answer visibility competes with other service lines inside the same retainer, which suits companies bringing their own strategy more than those needing it supplied.
If you would rather compare across all verticals first, our global comparison of the best AEO, GEO and AI SEO agencies scores 15 firms against a general-purpose rubric.
The SaaS-specific questions to ask on a sales call
Generic agency questions will not separate these firms. These will.
- How do you find the comparison queries we are losing? You want a method for surfacing "alternatives to" and "X versus Y" prompts, not a keyword export.
- How do you work review platforms and community sources? Much of the SaaS comparison answer is assembled from sources you do not own.
- How will you attribute an AI recommendation to a deal that closes in four months? Listen for assisted conversion and branded search modelling, not last-click.
- Which engines do you track, and how many repeat runs per prompt? A single run per prompt is not a measurement.
- How do you cover different buying-committee roles? Technical, financial and end-user prompts need separate coverage.
For establishing your own baseline before any of these conversations, see how to check if your business appears in AI search. For the measurement standard to hold an agency to, see our metrics framework. If you are still weighing whether to hire at all, DIY AEO versus agency covers what is realistic in-house.
Want to see which evaluation prompts you are missing from?
Book a free AI Visibility Audit. We will map the buyer questions in your category, show you where competitors are named and you are not, and explain what is causing the gap.
Book Your AI Visibility AuditFrequently Asked Questions
Should a SaaS company hire an AEO specialist or a full-funnel B2B agency?
It depends on where the gap is. If you have functioning demand generation and are simply absent from AI answers, a specialist closes that faster. If your whole go-to-market motion needs building, a full-funnel agency with AEO capability inside it avoids running two retainers with overlapping scope. The mistake is hiring a full-funnel agency and assuming the AEO line item carries real depth. Ask for prompt-level reporting before you assume it does.
How do we measure AI visibility against a long sales cycle?
Do not try to force a direct-response measurement onto it. Track share of answer on your core evaluation prompts as the leading indicator, then watch branded search volume and direct traffic as intermediate signals, and connect assisted conversions where your analytics allow. ChatGPT referrals may arrive carrying utm_source=chatgpt.com, which makes a portion of AI traffic directly visible, but that captures clicks only and misses every answer where you were named without a click.
Do review platforms like G2 matter for AI recommendations?
They matter as corroboration. Yext found 42% of AI citations came from business listings across categories (Yext, Oct 2025), and in B2B SaaS the review platforms function as the category directory. What is worth avoiding is treating review volume as the whole strategy: the useful signal is recent, specific reviews that mention actual use cases, not a high count of generic ones.
Is it worth targeting "alternatives to competitor" queries?
Yes, and they are among the highest-intent prompts in SaaS. Someone asking for alternatives to a named product is actively evaluating a switch. The work is mostly off-site, since those answers draw heavily on review platforms, comparison content and community discussion. Our guide to earning AI citations covers the legitimate routes into those sources.
How long before we see results in a SaaS engagement?
On-site and entity changes can surface within weeks as engines recrawl. Comparison and review-platform work compounds over months because it depends on third parties. Pipeline impact lags further still, on your own sales cycle. A reasonable expectation is early prompt-level movement in the first quarter and revenue signal in the second, with the caveat that repeat measurement is required to distinguish real movement from normal model volatility.
Ashur Homa
Built and scaled a digital brand to $100M+ in sales with zero ad spend. Has helped businesses generate millions through AI go-to-market strategy. Leads growth at Omni Eclipse.
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