Start looking at AI visibility software and many of the platforms can initially appear quite similar.
Among the products we have looked at so far, the central idea is broadly consistent: choose prompts that matter to your business, monitor what AI platforms return, record whether your brand appears, compare it with competitors and track citations and changes over time.
That raises an obvious question.
If they are all doing variations of the same basic job, how do you decide which one you need?
I think there is a better place to start than comparing feature lists.
Ask:
Who is actually going to do the AI visibility monitoring?
From that perspective, there appear to be three broad routes:
- Your business monitors its own AI visibility.
- You are an agency or consultant monitoring AI visibility for clients.
- Your business doesn’t want to do the monitoring itself and hires someone to handle it.
The underlying subject is the same in each case, but the requirements can be very different.
And before choosing any of those routes, there is another possibility worth considering:
you may not need software yet at all.
A snapshot of a fast-moving market
This article isn’t intended to be a definitive directory of every AI visibility platform.
The companies mentioned here surfaced during our own online research into AI visibility monitoring tools. Our view of where they currently fit comes primarily from looking at how they describe their products, pricing, features and intended customers on their own websites.
There will almost certainly be providers we have missed.
The market is also moving extremely quickly. New products are appearing, existing SEO platforms are adding AI-search features and specialist providers are expanding what their software can do.
So this should be treated as a snapshot of the market in August 2026, not a permanent classification.
It is also important not to place providers into rigid boxes. Several currently serve businesses, agencies and larger organisations at the same time.
What interests us more is where their features and positioning appear particularly relevant.
What are these platforms actually automating?
Before considering software, it helps to understand the manual process.
Suppose a business wants to know whether potential customers asking AI systems questions about its services are being shown its brand.
It could identify a group of commercially relevant prompts and test them manually.
For each search it might record:
- whether the business was mentioned;
- whether it was actually recommended;
- which competitors appeared;
- which websites were cited;
- how the business was described;
- where it appeared within the answer;
- whether the result changed when the same search was repeated.
A spreadsheet can handle this perfectly well at a small scale.
Manual testing is also useful because it forces you to understand what you are actually measuring rather than simply accepting a visibility score from a dashboard.
The problem is scale.
Five or ten important prompts on one platform may be manageable manually.
Increase that to dozens of prompts across ChatGPT, Google AI Mode, Gemini, Perplexity and other systems, add competitors and repeated testing, and the workload grows very quickly.
This is where automated monitoring starts to make sense.
Platforms such as OtterlyAI and Peec AI, for example, currently automate prompt monitoring and provide information around brand visibility, competitors and citations across AI systems.
The important question therefore isn’t simply:
Can this software monitor AI prompts?
Among the products we have examined, that is increasingly the starting point.
The more revealing questions are:
Who will be using it? At what scale? And what do they need to do with the results?
Route 1: Your business wants to monitor its own AI visibility
This could cover anything from a small business owner doing the work personally to a large marketing team running a sophisticated internal monitoring programme.
At the smaller end, the journey might begin without software at all.
You identify the important parts of your customer journey, select a manageable group of prompts and run some tests manually.
Eventually the workload may become inconvenient.
You want more prompts.
You want several AI platforms.
You want regular checks instead of occasional searches.
You want competitor tracking.
You want to know whether visibility is changing over time.
That is the natural point at which a self-service monitoring tool becomes interesting.
For a smaller business, useful questions might include:
- Is the software easy to set up and understand?
- How many prompts can I monitor?
- Which AI systems are covered?
- How often are prompts checked?
- Can I monitor competitors?
- Can I examine citations?
- Can I see the actual underlying AI responses?
- Does it help me organise or identify useful prompts?
- How quickly does the price increase as my monitoring grows?
- Can I export the data?
- Does it save enough time to justify paying for it?
Those requirements don’t automatically favour the platform with the longest feature list.
A relatively straightforward product may be a much better fit than a sophisticated enterprise platform if all you want is reliable monitoring of a sensible collection of commercially important prompts.
OtterlyAI currently illustrates the more accessible end of this market, with a Lite plan offering 15 monitored prompts before larger plans add substantially more capacity. Its current platform also allows multiple workspaces for managing separate brands or clients as requirements grow.
Peec AI similarly positions its Starter offering towards SEO and content managers beginning with AI-search visibility, while expanding into larger brand and agency requirements.
But “doing it yourself” can also mean enterprise
A large organisation running AI visibility internally has a very different version of the same problem.
Instead of 20 prompts for one company, it might have:
- several brands;
- multiple websites;
- different countries and languages;
- large prompt sets;
- numerous internal users;
- reporting integrations;
- security and access-control requirements.
At that point, APIs, role-based access, integrations, governance and scale may matter considerably more than having the simplest possible dashboard.
Scrunch, for example, explicitly positions its enterprise product around multi-brand, multi-domain and multi-region monitoring, role-based access, APIs and very large-scale prompt monitoring.
Profound describes itself as a purpose-built AEO platform for enterprise brands and agencies running dedicated AI visibility programmes.
These aren’t necessarily “better” products because they offer more complexity.
They are solving a different version of the problem.
Route 2: You are an agency or consultant doing it for clients
Now imagine using essentially the same underlying monitoring technology in an agency.
The prompts still need to be checked.
Brands, citations and competitors still need to be recorded.
But the operational problem changes dramatically.
One business monitoring 30 prompts is one thing.
An agency monitoring 30 prompts for each of 20 clients is another.
Now you may need:
- separate projects for different clients;
- multiple users;
- client access;
- automated reporting;
- branded reports;
- white-label dashboards;
- permissions;
- flexible allocation of prompts between clients;
- APIs or integrations;
- predictable costs as the client base grows.
This is where features that mean almost nothing to a small business can become major buying criteria.
Peec AI, for example, currently has specific agency plans designed around managing multiple client projects and allocating monitoring resources between them.
LLM Pulse places particularly strong emphasis on this part of the market. Its current agency and white-label offerings include branded dashboards, custom domains and client-facing delivery under an agency’s own identity.
Scrunch and Profound also explicitly address agencies alongside their other customer groups.
So an agency probably shouldn’t choose an AI visibility platform simply because someone has declared it the “best AI visibility tool.”
It should be asking:
Best for what?
A tool that is excellent for a marketing manager monitoring one company may become frustrating when used across dozens of client accounts.
Likewise, a sophisticated agency platform could be unnecessary and expensive for a business that only wants to monitor itself.
Route 3: Your business doesn’t want to do any of this
There is a third group that software comparisons can easily overlook.
A business might understand the importance of monitoring how it appears in AI search but have no interest in operating the process itself.
It doesn’t want to choose prompts.
It doesn’t want another dashboard.
It doesn’t want to interpret changing recommendations and citations.
It wants someone else to handle it.
For that business, the correct purchase may not be software at all.
It may need an agency, consultant or specialist service.
Interestingly, the software market itself provides evidence that this part of the ecosystem is developing. Peec currently operates an agency partner programme for agencies delivering AEO/GEO services using its platform, while several other platforms have built specific propositions around agencies managing client work.
For the business outsourcing its monitoring, the questions are therefore different again.
It might want to ask:
- How will you decide which prompts are worth monitoring?
- How do those prompts relate to our actual customer journey?
- Which AI platforms will you cover?
- How frequently will searches be monitored?
- How do you distinguish a brand mention from a recommendation or citation?
- How will competitors be assessed?
- Can we see the underlying results?
- What monitoring software do you use?
- How do you interpret fluctuations in AI responses?
- Do you independently check important findings?
- What happens after you identify a visibility gap?
- How will success actually be measured?
There should also be caution around guarantees.
AI-generated search results are dynamic. A provider promising that particular work will guarantee a recommendation from ChatGPT or Google AI Mode should therefore raise questions.
Measurement, analysis and sensible action are realistic services.
Guaranteed AI recommendations are something very different.
Where do some of the current providers appear to fit?
Based on the providers we have examined so far, a simplified view might look something like this:
| Provider | Self-service / brand | Agency use | Enterprise / advanced use | Current area of emphasis worth investigating |
|---|---|---|---|---|
| OtterlyAI | Strong | Yes | Available | Accessible monitoring with room to scale |
| Peec AI | Strong | Strong | Yes | Separate brand and multi-client agency workflows |
| LLM Pulse | Strong | Strong | Yes | White-label and agency delivery |
| Profound | Yes | Strong | Strong | Dedicated AEO programmes for larger brands and agencies |
| Scrunch | Yes | Strong | Strong | Monitoring plus auditing, optimisation and enterprise-scale capabilities |
This table should not be read as a ranking.
Nor does a tick in more columns make a product better.
It simply illustrates why the market becomes more understandable once we stop treating every AI visibility buyer as though they have the same requirements.
The platforms themselves are also evolving.
Scrunch, for example, goes beyond straightforward monitoring into website auditing, content optimisation and AI-focused content delivery.
That suggests even the term AI visibility software may eventually describe a much broader group of products than simple prompt trackers.
Perhaps the first question shouldn’t be “Which software?”
There is a temptation with any new category of marketing technology to start by comparing products.
But AI visibility monitoring may make more sense in a different order.
First ask:
What do we actually want to understand?
Then:
Which customer questions or prompts matter to the business?
Then:
Can we test a useful selection manually?
Then:
Has the number of prompts, platforms and competitors become large enough that automation would materially help?
Then:
Who is going to operate that monitoring?
Only after that does the software decision become much clearer.
A small business doing it itself has one set of requirements.
An agency running campaigns across many clients has another.
A large internal marketing operation has greater requirements again.
And a business that simply wants somebody else to handle the problem may not need to subscribe to monitoring software at all.
This also gives us a framework for reviewing AI visibility products
As we look at more AI visibility tools and services, we don’t want every review to ask the vague question:
Is this a good product?
That isn’t particularly useful.
Instead, our reviews can ask:
Who does this product appear to be built for, and how well does it solve that particular user’s problem?
That means establishing the criteria first.
For a business doing its own monitoring, we can look at areas such as ease of use, prompt allowances, AI-platform coverage, pricing, competitor monitoring and how understandable the results are.
For agencies, we can examine client management, project structure, reporting, white-labelling, permissions, integrations and the economics of using the product across multiple accounts.
And for businesses that would rather outsource the work, the useful comparison isn’t necessarily between software platforms at all. It is between the approaches and services being offered by agencies and consultants.
These will form three separate practical guides within this section.
They can then become templates against which future products and services are assessed, rather than changing our criteria to suit whichever provider happens to be under review.
One market, but several very different buyers
Among the AI visibility platforms we have examined so far, there is considerable overlap in the underlying monitoring function.
That isn’t surprising.
Prompt monitoring, brand visibility, competitor comparisons and citation analysis are fundamental parts of the problem these products are trying to solve.
The meaningful differences become clearer when we ask:
Who is doing the work?
For some businesses, manual testing may still be enough.
For others, self-service software removes a rapidly growing manual workload.
For agencies, multi-client management and reporting can become as important as the monitoring itself.
For enterprise teams, scale, governance and integrations may dominate.
And for businesses that want nothing to do with operating the process, the right answer may be to hire someone rather than buy another software subscription.
So before asking:
“What is the best AI visibility tool?”
there is a more useful question:
“What are we actually trying to do, and who is going to do it?”
Once that is clear, comparing the available tools and services becomes a much more meaningful exercise.