Be the business AI recommends, and turn AI’s answers into your warmest leads
Win high-intent buyers
When someone asks AI who to hire, you want to be one of the names it recommends, not an invisible option.
Control how AI describes you
If AI has old, incomplete, or wrong information about your business, it can lose the customer before they ever call.
Catch competitor movement early
See when a rival starts showing up more often in AI answers, and know what they are doing better.
Done with you, not instead of you
We bring the tools, the data, and the expertise, then pick the best approach for your business, and work alongside you, month by month.
Onboarding & audit
A full AI-visibility and competitive audit of where you stand today, for you and your rivals.
Personalized roadmap
A prioritized plan built for your niche and your gaps, not a template, sequenced by payoff.
Agree the split
We define together who does what, your team, your contractors, and us, so nothing overlaps or falls through.
Monthly work plan
Concrete actions for each month, sized to your capacity, with the expected impact spelled out.
Re-measure
We re-run the scan and check the work actually moved the numbers, with confidence intervals, not vibes.
Monthly review & course-correct
A report, a debrief, and an adjusted plan, so the strategy keeps pace as AI changes.
We measure the sources and signals AI relies on, for you and your competitors
We measure the sources and signals AI systems commonly rely on: your website, structured data, Google Business Profile, reviews, directories, local listings, community mentions, citations, competitor pages, and live AI answers. Then we compare you against the competitors AI already names.
How often your brand appears, whether it is recommended or merely mentioned, how accurately AI describes you, which sources AI cites, and how you compare against competitors, all across the same prompts, locations, and models.
The capabilities, each with why it matters to your business
Discover the whole field, then benchmark against it
| Business | AI visibility | AI recommend | Brand accuracy | Sentiment | Rating | Reviews | Review velocity | Citation share | Local listings |
|---|---|---|---|---|---|---|---|---|---|
| Your brand You | 16% | 1 / 4 | 85 | Mixed | 5.0★ | 20 | +1/mo | 0% | 3 / 10 |
| Market leader | 22% | 4 / 4 | 92 | Positive | 4.6★ | 162 | +9/mo | 6.1% | 9 / 10 |
| Strong rival | 15% | 3 / 4 | 88 | Positive | 4.8★ | 98 | +6/mo | 3.4% | 8 / 10 |
| Mid-pack rival | 11% | 2 / 4 | 80 | Neutral | 4.5★ | 73 | +3/mo | 1.8% | 6 / 10 |
| Regional specialist | 9% | 1 / 4 | 83 | Positive | 4.9★ | 55 | +4/mo | 1.1% | 5 / 10 |
| National aggregator | 12% | 2 / 4 | — | Neutral | — | — | — | 4.0% | 10 / 10 |
When someone asks, does each engine actually recommend you?
Does AI know your brand, and does it get you right?
Can AI and agents actually read your site?
Drag the handle: the same page, as a customer sees it (left) and as AI actually reads it (right). A human infers meaning from design; AI mostly depends on crawlable text, structured markup, accessible labels, links, and metadata. If key information is trapped inside images or unclear buttons, AI can miss it, which is why clear copy and clean markup get you described and recommended correctly.
What actually moves the needle in your category
Where you win and lose, topic by topic, in SEO and in AI
The sites AI trusts, and where to earn presence
Prove the work moved the number
Not “get more reviews”: the exact number to aim for
For the dials you can turn, review count, rating, freshness, we benchmark where recommended competitors tend to sit, show where you are now, and set practical targets. These are smooth trend lines across an observed set, and planning targets, not guarantees.
AI visibility vs. review count
AI visibility vs. average rating
And always know the next move
Opportunities ranked by impact; bracketed values fill in from your scan.
Where to publish next: decided by data, not hunches
We combine your topic gaps with the sources AI actually cites to produce a ranked, specific placement plan: the exact pages to build and the exact places to earn citations so AI starts recommending you.
Each recommendation carries the reason, the source of evidence, an effort level, who should own it, and the AI-visibility metric it’s expected to affect.
Built for where AI is going, not just where it is
Sentiment & framing
Measures not just whether AI mentions you, but how positively it frames you vs. rivals, tone, emphasis, and the adjectives it reaches for.
Multi-location coverage
Runs the whole analysis per service area, because AI answers differ by city, and a brand strong in one market can be invisible in the next.
You pick the AI panel
Curated model catalog with per-scan pickers; we add new AI surfaces as they become relevant to your customers and measurable reliably.
This isn’t one search. It’s a measurement system you can’t run by hand.
AI answers are non-deterministic, ask the same question five times and you get different brands. A screenshot proves nothing. We run a whole prompt set across markets and engines, repeat every prompt many times, then aggregate into a number you can trust.
One check tells you almost nothing. We report an interval, and reproduce it.
Ask an AI the same question twice and you can get two different answers, so a single check is not a measurement. We run a fixed panel of buyer prompts repeatedly, across providers, and report an aggregated estimate with a confidence interval around it. Two things widen or narrow that interval, and only one of them is the number of runs: repeats of the same prompt are correlated with each other, so panel breadth — how many distinct prompts and providers you measure — carries more of the real information than raw response count does. We estimate the interval by resampling whole prompts rather than individual responses, and compare periods on paired per-prompt differences. It is also reproducibility: re-run the same panel next week and you get a comparable number, so a reported change is a change we can distinguish from noise. The full contract is on our measurement methodology page.
Four things others skip, and why they decide whether AI recommends you
Many measurements, not one
Others take a single snapshot. We run iterations across models and locations and report statistical significance.
Why it matters: otherwise you can’t tell a real win from a lucky day, and you’ll burn budget chasing noise.
Full SEO + GEO, not a bolt-on
We’re not an SEO platform with a GEO tab stapled on. We study search and AI visibility together, in depth.
Why it matters: one strategy where search and AI reinforce each other, instead of two teams pulling apart.
Factor-influence analysis
We don’t hand you a generic checklist. We measure which factors actually drive visibility in your category and rank them.
Why it matters: your budget goes to the few levers that move your market, not a one-size-fits-all to-do list.
We move as fast as the field
AI search changes monthly, new models, new answer formats, new signals. We continuously update our checks, recommendations, and tracking.
Why it matters: your plan stays valid as models shift, so the work you pay for this month still counts next month.
How that compares
The honest version of where each approach helps, and where it stops. Hover any capability or cell for what it means.
| Capability | AIReady | Typical GEO tracker | Traditional SEO platform | Manual spot checks |
|---|---|---|---|---|
| Queries the AI engines directly | ✓ | ✓ | ∼ | ✓ |
| Covers every major engine (ChatGPT, Claude, Perplexity, Google AI Overview) | ✓ | ∼ | ∼ | ∼ |
| Runs from multiple locations / markets | ✓ | ✕ | ✕ | ✕ |
| Repeats each prompt across many iterations | ✓ | ✕ | ✕ | ✕ |
| Reports statistical significance & confidence intervals | ✓ | ✕ | ✕ | ✕ |
| Per-model and aggregated visibility views | ✓ | ∼ | ✕ | ✕ |
| Verifies AI’s knowledge of your brand is accurate (hallucination check) | ✓ | ✕ | ✕ | ∼ |
| Measures sentiment & how AI frames you | ✓ | ∼ | ✕ | ✕ |
| Topic-level visibility: SEO vs. AI, side by side | ✓ | ∼ | ∼ | ✕ |
| Analyzes which factors actually drive visibility | ✓ | ∼ | ✕ | ✕ |
| Technical & schema readiness for AI & agents | ✓ | ∼ | ∼ | ∼ |
| AgentReady 1.0 conformance (the agentic web) — experimental | ∼ | ✕ | ✕ | ✕ |
| Citation-source intelligence, where AI pulls from | ✓ | ∼ | ✕ | ✕ |
| Full SEO + GEO depth (not a bolt-on) | ✓ | ✕ | ∼ | ✕ |
| Discovers & fully scans every competitor (500+ checks each) | ✓ | ∼ | ∼ | ✕ |
| Side-by-side competitor comparison on every metric | ✓ | ∼ | ∼ | ✕ |
| Content-placement plan (topics × citation sources) | ✓ | ✕ | ✕ | ✕ |
| Turns findings into concrete numeric targets & cost | ✓ | ∼ | ✕ | ✕ |
| Historical tracking & momentum over time | ✓ | ∼ | ∼ | ✕ |
| Updates checks & recommendations as AI changes | ✓ | ∼ | ✕ | ✕ |
| Practical to repeat every month | ✓ | ✓ | ✓ | ✕ |
Competitor categories are generalized from common market approaches; exact capabilities vary by provider.
Future readiness for AI agents
Today buyers ask AI for recommendations. Next, AI agents may compare, shortlist, and complete tasks for them. This is a forward-looking preview, not part of what we sell today — agent surfaces are still emerging and we cannot yet measure them reliably. The groundwork overlaps with the work we do measure: clean structured data, consistent listings, and verifiable facts are the same signals that make you recommendable now. The illustration below shows the kind of checks this would cover; we will add agent surfaces to the measurement when they become measurable.
The sources & surfaces we check
We don’t sample a corner of the web. Across 500+ AI-visibility factors, we read the platforms AI leans on, the listings and reviews that shape trust, and the technical signals that let models and agents understand your site, for your brand and every competitor.
Be the business AI recommends, before your competitors are.
Get your free AI visibility snapshot. We’ll show whether AI recommends you, how it describes your business, which competitors it names instead, and the top 3 fixes to improve your visibility.