Searchable vs Amadora AI: We Tracked the Same 11 Prompts on Both

Searchable and Amadora AI are GEO tools that track how AI engines describe your brand, and both report a visibility score. We ran the same eleven prompts through each platform for seven days to see whether those scores agree. They do not, and the reason sits in how each tool defines the metric.

This comparison covers what the two platforms measure, what they do with that data, and what each costs once engines, multiple brands and client reporting are included.

Quick comparison

How We Tested Searchable and Amadora AI on 11 Identical Prompts

We ran one brand across both platforms for seven days: eleven prompts in the AI image generation category, three answer engines each, daily tracking.

The setup was matched as closely as the two products allow:

• The same eleven prompts, entered on both platforms
• US location, daily tracking on both
• Seven-day reporting window on each platform
• Three answer engines each: ChatGPT and Perplexity on both, plus Gemini on Amadora AI and Google AI Overviews on Searchable
• 227 executions recorded by Amadora AI, 231 responses recorded by Searchable

The prompts:

1. What are the best AI image generators?
2. What are the best AI art generators?
3. What are the best text-to-image AI generators?
4. What is the best AI image generator in 2026?
5. Which AI image generator produces the highest-quality images?
6. What is the best AI image generator for photorealistic images?
7. What is the best AI image generator for cinematic images?
8. What is the best AI image generator for consistent characters?
9. Which AI image generator is best for consistent characters across multiple scenes?
10. Best text-to-image tool for designers that supports reference images and style matching
11. Best AI image generator for marketing creatives with commercial-use licensing

Two differences in method matter before any number appears.

The third engine is not the same surface. Gemini answers as a chat assistant. AI Overviews answers inside a search results page, shorter and pulled from live results. Amadora AI treats AI Overviews as separate tracking, available as a paid add-on rather than a base engine, so our account ran Gemini. Searchable ran AI Overviews.

Collection differs too. Amadora AI scrapes the interface, automating real browser sessions to capture what a user would actually see. Searchable does not publish its collection method.

Same Prompts, Different Numbers: What Each Tool Reported

Both platforms report a metric called visibility score. They do not calculate it the same way. Share of voice, by contrast, is defined almost identically in both sets of documentation, and that single difference explains most of what the numbers do below.

Visibility score

These two columns carry the same label and measure different things.

Amadora AI's visibility score is a presence rate. Responses mentioning the brand, divided by total responses, times 100. A brand either appears or it does not.

Searchable's visibility score is a composite. It weighs mention frequency, position in the response, context quality and sentiment into a single 0 to 100 figure. Searchable also reports a separate Presence Rate, the percentage of tracked prompts that mention the brand at all.

Presence Rate is the true counterpart to Amadora AI's visibility score. The columns above set a presence rate against a weighted composite, which is why nine brands diverge by 9.0 points on average while still ranking in a similar order, with a rank correlation of 0.82.

The formula difference explains why the absolute scores should not be compared directly. It does not account for every brand-level gap: the different third engine also affects the result.

Share of voice

Here the definitions converge. Both platforms calculate share of voice the same way: brand mentions divided by total mentions across every tracked brand.

The agreement shows. The mean absolute gap was 1.76 percentage points, and eight of the nine shared brands landed within three points. Midjourney, Adobe Firefly, Ideogram and Stable Diffusion all sit within one.

What the remaining gaps come down to

The third engine is a different surface. Gemini answers as a chat assistant. AI Overviews answers inside a search results page, in a shorter format with different retrieval behaviour. One third of each platform's sample came from a different surface, and every engine carries its own training data, ranking logic and refresh cycle.

The competitor sets were built independently. Amadora AI surfaced 63 brands from identical inputs, Searchable 55. Because share of voice divides by mentions across every tracked brand, differences in entity discovery and naming move the percentage even when the underlying answers are similar.

Brand naming is not standardised. The platforms do not always label the same company identically, so any cross-tool comparison needs the entities matched up by hand before the numbers mean anything.

Neither metric transfers cleanly. Visibility fails on definition, share of voice on denominator. Both tools measure consistently over time, which is what a baseline needs to be, but a figure from one means nothing set against a figure from the other.

Same AI Answers, Different Source Intelligence: How Each Tool Maps Citations

Both platforms record every URL an AI answer cites, then classify what they find. The overlap in which sources matter is high. The way each tool describes those sources, and what it lets you do next, diverges sharply.

Eight pages appear in both platforms' top cited sources for the same eleven prompts. These are the pages feeding AI answers about AI image generators.

The two columns are not the same measurement. Searchable exposes a source usage rate. Amadora AI exposes citation volume.

A page can lead on one and trail on the other. Zapier had the highest Searchable Used rate at 33.3% while carrying 48 citation events in Amadora AI. Aimlapi accumulated far more citation events at 156, the highest in the set, on a Used rate of 15.2%. One measures breadth of use, the other citation frequency.

What the classification tells a brand trying to break in

Both tools label every cited source. They label it for different purposes, and that decides what you can act on.

Searchable tells you who owns the page. Every source is marked as editorial, competitor, corporate or your own. That tells you which cited pages a rival controls the framing of, and which are neutral titles you can pitch.

Amadora AI tells you what kind of source the engines trust. Its single most-cited domain in our test was a documentation subdomain with 341 citation events, ahead of every vendor homepage and every editorial site, even though blog articles were the largest URL-format category overall.

A brand with thin, unindexed or gated docs is missing from the retrieval step regardless of how good its marketing pages are.

Searchable's opportunity layer separately reported that ranked lists represented 71% of the cited content it was analysing and comparisons another 20%. Amadora AI uses a different taxonomy, so those percentages do not transfer across platforms.

What each tool adds beyond the list

Both offer gap analysis and export.

Searchable adds direction. Every source carries a growth figure. In our test week individual sources moved three points in both directions on the same prompt set, which turns a static source list into an outreach priority.

Amadora AI separates being discussed from being cited. Its brand-presence view reports 46.1% of AI-cited documents mentioning the brand against 1.3% of all references pointing at the brand's own site.

A brand can dominate the conversation and still own almost none of the sources feeding it. Being talked about is a PR outcome. Being cited is a traffic and control outcome, and they require different work.

Searchable builds a target list. Ownership labels plus growth turn cited sources into a ranked outreach plan.

Amadora AI builds a diagnosis. Source typing and the mention-versus-citation split separate absence from the conversation from absence from the sources behind it. Those look identical on a dashboard and need different budgets.

How Each Tool Reports Brand Perception and Sentiment

Visibility tells you whether an engine names you. It says nothing about how. A brand can lead its category on mentions and still be described as the expensive option, the one with weak support, or the risky choice for any commercial work.

Searchable exposed a much deeper perception interface in our test, including brand perception scoring, sentiment trends, head-to-head comparison, attribute-level analysis and a factual claim verification queue. None of the Amadora AI screens we captured exposed an equivalent attribute-level or claim-verification layer, although Amadora AI's documentation states that it tracks sentiment.

What Searchable measures

In our test week the leading brand returned a brand perception score of 83 out of 100, with 73% of mentions positive, 21% neutral and 7% negative.

Sentiment and visibility move independently. Over the same seven days visibility rose 3.3% while the sentiment score fell 9.7 points. A dashboard tracking only mentions would have read that week as unambiguously good. Engines were naming the brand more often and describing it less favourably at the same time.

Category leadership does not mean favourable description. Head to head against its nearest rival, the tracked brand led on visibility by a wide margin and on average position, and still scored lower on sentiment. The brand being outranked was the one being described better.

Leading on mentions is compatible with losing on attributes. Searchable scores how a brand is characterised across individual attributes and marks each as leading, at parity or behind. The category's most-mentioned brand led visibility while being marked behind on 52% of Searchable's 15 extracted attributes and leading on 27%.

The part that is not sentiment at all

Searchable separately extracts the factual claims engines make about a brand and puts each one in a verification queue for a human to mark correct or incorrect. In one week, for one brand, it captured 38 of them.

This is a different risk from tone. An engine describing you as expensive is an opinion you counter with positioning. An engine stating you lack a capability you shipped last quarter is a factual error, and it needs a named owner rather than a marketing response.

What Amadora AI gives you instead

Amadora AI answers the perception question by working backwards from sources. Rather than scoring tone, it shows which documents shaped an answer, whether the brand appears in them, and whether its own domain is among the references.

For a brand where the description is wrong, that is the more direct route to a fix. Sentiment scoring tells you the characterisation is poor. Source analysis tells you which pages produced it.

Which matters for your situation

Take sentiment scoring seriously if you are already visible. Once engines reliably name you, the remaining risk is how. Tone tracking, attribute-level comparison and claim verification are the tools for a brand defending a position rather than building one.

Take source analysis seriously if you are not visible yet. A perception score on a brand engines rarely mention measures a handful of responses. Getting into the answer comes first, and that work runs through citations.

From Visibility Gap to Action: Amadora AI Optimization Plans vs Searchable Opportunity Cards

Both platforms turn visibility data into instructions. One produces a scored diagnosis and a page-level specification for a single prompt. The other maintains a running queue across the whole account. The difference is depth against breadth, and it decides which team each suits.

Amadora AI: one prompt, taken apart

An Optimization Plan is generated against a single tracked prompt and returns a score out of ten for how well the brand fits what engines look for when answering it. In our test that came back at 7.6.

The score breaks into weighted criteria, each carrying a required standard rather than a vague recommendation. The strongest of these is the one most brands underestimate: third-party validation, with a stated minimum of presence on at least one major review platform and coverage in two or more major publications. That is a testable bar. Either you clear it or you do not.

Each criterion then gets scored individually with a severity rating and a note on what evidence was found and what is missing. In our test the lowest score was integrations and enterprise readiness at 4 out of 10, marked high severity, against a category leadership score of 9.

The output is a page brief, not a suggestion. Deliverables are ranked by impact and priority, and each arrives with:

• the URL slug, page title and H1
• the sections to include
• the schema types to deploy
• an acceptance test

One item required key evidence pages to be fetchable without authentication and return a 200 response. Another set a target of five new or updated top-tier mentions within six months.

There is a cost to that depth. A full audit plus AI visibility action plan costs 200 credits, and Amadora AI separately lists a comprehensive Optimization Plan at 100. With 3,000 monthly credits, the Agency tier's base allowance covers fifteen of the 200-credit bundles before rollovers or top-ups. You are not running this against every prompt you track.

Searchable: the whole account, continuously

Opportunities is a standing queue rather than a generated artefact. In our test it held 26 open items across three areas: platform setup, on-page work and off-page outreach. Each card carries a priority, a short instruction and Done or Decline buttons, so the list functions as a worklist with state rather than a report.

The cards cite live account data. One flagged that ranked lists account for 71% of cited content and comparisons another 20%, while the brand had published neither. Another identified a single domain appearing in 53 AI citations as an outreach target. A third pointed at a competitor outperforming the brand on typography and named the specific product parameter to write a guide around.

Two categories have no counterpart in a per-prompt plan.

It audits your own configuration. Two items were marked critical, both because analytics connections were missing. It also surfaced two utilization gaps: 11 of 500 prompt slots used and 1 of 1,000 audits used.

It flags its own data quality. Two cards identified competitor entries that likely represent the same company under different names and offered to merge them. Duplicates inflate the brand set that every share-of-voice figure divides by.

What each one is actually for

Amadora AI answers: how do I win this specific answer? The plan is deep enough to hand to a writer and a developer without further scoping, and credits make it a scarce resource to aim carefully.

Searchable answers: what is wrong across my account right now? The queue is broad, refreshes against live data and covers work a prompt-level plan never reaches. It will not tell you how to build the page.

Google AI Overviews: Dedicated Module in Amadora AI, Broader Engine Tracking in Searchable

Google AI Overviews are triggered by a typed query rather than a conversation, making them a surface where AI visibility and traditional search rankings directly overlap. The two platforms handle that overlap in opposite ways.

Searchable runs AI Overviews as one of its tracked engines. Your prompts go to it the same way they go to ChatGPT or Perplexity, and you get one comparable visibility figure per engine.

Amadora AI runs a separate Google AI Search module built on keywords rather than prompts, alongside offering AI Overviews as a paid add-on engine inside prompt tracking.

What the dedicated module gives you

Amadora AI's module reports four things against every tracked keyword:

• whether an AI Overview appeared at all
• whether the brand was mentioned inside it
• whether the brand's own pages were cited as a source
• where the brand ranked organically on the same query

Three of those have no equivalent in a per-engine visibility score.

Trigger rate is the first thing worth knowing. AI Overviews do not appear on every search. If the feature fires on a fraction of your category's queries, optimising for it is a low priority no matter what your score says.

Mention and citation are counted separately. Being named inside an AI Overview is a positioning result. Having your pages used to build one is a content and technical result. A single visibility figure merges them.

Organic position sits next to AI Overview presence on the same query. Ranking page one and being named in the summary above those results are separate outcomes, and knowing which one you are losing determines what you fix.

What the engine approach gives you

Searchable trades that detail for consistency. Every engine takes the same prompts and returns figures on the same scale, so AI Overviews compare directly against ChatGPT and Perplexity without reconciling two measurement systems.

Cadence differs as a result. In our test Amadora AI's keyword module refreshed twice a week while its prompt tracking ran daily. Searchable ran the full prompt set daily across all three engines.

Which design fits your work

If Google decides your category, the dedicated module earns its place. Trigger rate, organic position and citation status in one view shows whether an AI Overview is taking traffic you used to win, and whether your own pages are feeding it.

If you want engines lined up against each other, folding AI Overviews into the prompt set is simpler. Same input, same denominator, one comparable figure across the board. The mistake is assuming the two designs produce the same insight.

What Each Platform Costs Once You Add Engines, Brands and Client Delivery

Both platforms sell prompt tracking by tier, and at first glance the sticker prices look close. The differences that decide the bill sit underneath: what an AI action costs, how many engines the base price covers, and how early white-label and API access unlock.

Searchable runs two separate pricing tracks, one for brands and one for agencies. Amadora AI runs a single ladder, with its top tier aimed at agency work.

For in-house brand teams

Amadora AI's $59 entry is the cheapest way onto either platform, but fifteen prompts is a pilot allowance. At the same nominal 100-prompt allowance, Searchable costs $125 against $179 and includes API access that Amadora AI holds back until $499.

Searchable states prompts per model while Amadora AI states prompts, so these unit costs are nominal rather than strictly like for like.

The entry decision comes down to brand count. One brand makes Searchable cheaper. Several brands invert it, because multi-project access on Searchable does not arrive until $400.

For agencies serving multiple clients

Searchable's agency entry undercuts Amadora AI by half. White-label reporting and API access arrive at $250 rather than $499, at $1.25 a prompt against $1.66.

Amadora AI's answer is unlimited client brands and consolidated billing. An agency running twelve clients hits Searchable's ten-project ceiling on Growth and moves to a $999 tier. On Amadora AI the brand count never becomes the constraint.

The crossover sits around ten clients. Below that Searchable is cheaper for the same delivery capability. Above it, project caps start forcing upgrades that Amadora AI's model does not.

The engine question changes every figure above

Amadora AI includes three engines on every plan and sells the rest as add-ons from $9 a month.

Searchable shows the same three engines active across every listed tier, with the remaining models reserved for its custom plan.

Neither platform gives full engine coverage at the advertised price. If your buyers are asking Claude or Copilot, that is a published add-on on one platform and a sales conversation on the other. Budget for it before comparing tiers.

Credits against fixed allowances

This is the structural difference and it decides which plan runs out first.

Amadora AI meters AI actions from a credit pool. A full audit and action plan costs 200 credits, a content plan 100, a draft 40, a brief 20. On the $179 plan that is five full plans a month, or twenty-five drafts, or some mix. Spend the pool and the work stops until it resets.

Searchable issues fixed counts. Twenty articles and two hundred audits at entry, eighty and a thousand at $400. Searchable provides separate fixed monthly allowances for articles and audits rather than one shared pool.

Credits suit uneven workloads where one month is research and the next is production. Fixed counts suit steady output where predictability matters more than flexibility.

Which Platform Fits an Agency Delivering GEO and AEO to Multiple Clients?

An AEO agency and GEO agency buys three things from a visibility platform: enough client capacity to cover the roster, deliverables that leave the building with your logo on them, and a per-client cost that survives contact with a retainer. The two platforms answer those differently.

Client capacity is where the ladders cross

Searchable caps clients by project. Five on the $250 agency plan, ten at $400, unlimited at $999.

Amadora AI does not cap brands at all from its $179 tier upward, and its $499 agency plan adds multiple workspaces and consolidated billing on top.

Searchable's agency plans cap projects at five on Launch and ten on Growth, with unlimited projects requiring the $999 tier. Amadora AI's $499 plan includes unlimited brands and multiple workspaces, so an agency past ten client accounts avoids a project-count tier jump. The trade-off is tracking capacity: the shown Amadora AI configuration includes 300 prompts against 1,250 per model on Searchable's $999 tier.

White-label arrives at very different prices

Client-branded output costs half as much on one platform as the other. Searchable includes white-label reporting across its entire agency track from $250, with platform-level white-label listed as coming soon on its top tier. Amadora AI includes white-label branding at $499.

Deliverable production works differently

Searchable builds reports inside the platform. A block-based editor assembles visibility, citation and sentiment components into a document, with an assistant that reviews structure and prunes weak sections. For a retainer shipping a monthly deck, that removes the export-and-rebuild step.

Amadora AI produces a weekly report view and a share link per project, alongside CSV export across its data panels. Its agency tier adds premium Slack support and consolidated billing, which shape how an agency runs rather than what it hands over.

The constraint most agencies will model first

Amadora AI's credit pool is shared across the whole account rather than allocated per client. At $499 that is 3,000 credits against 200 for a full audit plus action plan, so every deep analysis draws on the same pool the rest of the roster uses.

Searchable's equivalent at $400 is eighty articles and a thousand audits, issued as separate fixed counts.

Neither model is better in the abstract. Credits suit an agency where one client needs heavy analysis this month and another needs volume next. Fixed counts suit a standardised retainer.

The plans side by side

Amadora AI does not meter its Agency tier by brand count, but usage still depends on its prompt and credit pools. The shown $499 configuration includes 300 prompts and 3,000 monthly credits.

Which one to choose

Take Searchable if your deliverable is a client-branded report. White-label from $250, API access at every tier, a lower nominal prompt cost, and report production that happens inside the platform.

Take Amadora AI if brand count is your constraint. Unlimited brands, multiple workspaces and consolidated billing at $499 without a project-count tier jump. Model the prompt and credit pools before signing, since both are shared across the roster.

Final Verdict

Neither platform is the better product in the abstract. They diverge on measurement, on what they turn that measurement into, and on where the price sits as you add engines, brands and client delivery.

Choose Searchable for deeper perception analysis and client reporting. It exposed a far richer brand-perception layer in our test, maintains an account-wide opportunity queue, builds editable reports inside the platform, and offers more prompt capacity per dollar on the published tiers. API access starts at $125 and agency white-label at $250. The constraints are project caps below the top tier and full engine coverage reserved for a custom plan.

Choose Amadora AI for multi-brand work and Google-focused categories. It starts cheaper at $59, removes brand limits from $179, and runs a dedicated Google AI Search module reporting trigger rate, citation status and organic position against the same keyword. Its per-prompt optimization plans go deeper than anything in Searchable's queue. Model the shared prompt and credit pools before signing.