The three options on most shortlists
The problem usually shows up in one of two places. Either your website cannot answer customer questions on its own, or assistants like ChatGPT say things about your brand that you never wrote. Once a team decides to act on either one, the same three families of tools end up on the shortlist almost every time. Each is a rational choice for someone. A fair comparison says for whom.
| Option | Genuinely good at | Trade-offs to know |
|---|---|---|
| App-store chatbots (Tidio and similar) | Cheap and installed in minutes. You get a chat window on your site the same day. A reasonable first step if the goal is deflection: routine questions get answered automatically, so fewer tickets reach your support inbox. | Most cannot show which of your pages an answer came from, and there is usually no step where a human checks an answer before customers see it. They also do nothing about how your brand shows up inside AI assistants, and they do not measure it. |
| Enterprise search and answer platforms (Algolia, Coveo) | Powerful and proven at large scale. Companies with a very large body of content get deep relevance tuning (fine-grained control over which result ranks where) and integrations with almost anything. | Buying one means starting a project. You need engineers for setup and maintenance, implementation takes months rather than days, and pricing assumes an enterprise budget. |
| Do it yourself (maintained FAQ page plus manual ChatGPT use) | Free, apart from your time. A well-kept FAQ page has real value on its own, and it doubles as source material AI assistants can read. | You are flying blind. You do not learn which questions go unanswered, whether assistants cite you, or whether last month's work moved anything. |
Note what is missing from the table: a verdict. A three-person shop with simple support questions is well served by the first row. A corporation with a search team already in place belongs in the second. The problems start when a mid-size team buys row one expecting row two, or tries row three and expects it to keep improving with nobody measuring anything.
The four criteria real buying processes turn on
Strip away the feature grids, and the decisions we see in actual buying processes come down to four questions. They are worth asking about any option, including us.
Three checks. Can you see, on every answer, which page it came from? Does a person approve each answer before customers see it? And does anything re-check old answers once the content behind them changes? A chatbot that answers fluently but cannot be verified is a liability with a friendly face.
Time-to-value is the stretch between signing a contract and the first useful result. Here that means: how long until the first reviewed answer is live on your site? The honest unit of measurement is an afternoon versus a quarter. Anything that needs a project plan and engineering sprints before it delivers has to be worth that overhead.
The same reviewed content should work twice: as answers on your own site, and as material that shapes what AI assistants say about your brand. Both effects should be measured, not assumed. A tool that only does on-site chat solves half the problem and tells you nothing about the other half.
Four things to look for. Hosting in the EU. A data processing agreement, the contract GDPR requires whenever a vendor handles personal data for you. Pseudonymization, meaning names and email addresses get replaced with placeholders before anything reaches the AI provider. And a guarantee that your data is not used to train models. If any of these are "on the roadmap", your data protection officer will find out at the worst possible moment.
How that ongoing re-checking works in practice is a topic of its own; we cover it in What is prompt monitoring?. And the compliance questions from criterion 4 belong in front of every vendor on your list. Klariton answers them publicly in its Compliance Center, which doubles as a checklist for asking everyone else.
Price comes fifth, on purpose
Price matters. It comes last because a price tells you nothing until you know what you are getting for it. A cheap tool that fails criterion 1 costs you trust with every wrong answer. An enterprise platform that fails criterion 2 eats a quarter of engineering time before you see anything. So settle the four criteria first, then compare what each option charges for what it actually delivers. Done in that order, the price discussion tends to be short and unemotional.
Where Klariton honestly fits
Klariton is a fourth option. The fairest way to describe it is against the four criteria, not with adjectives. Every published answer shows the page it came from. Nothing goes live until someone on your team has approved it. The effect is measured on both ends, on your site and in AI assistants, through LLM Discovery Intelligence. And EU hosting, the data processing agreement and the pseudonymization step are part of the architecture, not options on a price list.
That does not make the other options wrong. Need basic chat coverage this week at minimal cost? An app-store chatbot is a fine answer. Running a large body of content with a dedicated team? The enterprise platforms are built for you, and evaluating them properly will take more than this article. Klariton is built for the team in between: too small for a platform project, too invested in its brand to leave AI answers unmanaged. Whether that is you takes minutes to find out. Run the free AI visibility check and read what assistants currently say about your brand. If the result stings, we covered how to win the internal budget discussion in How to build the internal business case for AI visibility.
Frequently asked questions
Is a cheap app-store chatbot enough to get started?
It can be, if all you need is a basic chat window on the site. Just know what you are trading away: these tools usually cannot show which page an answer came from, rarely let a human check answers before they go live, and do nothing about how your brand shows up in AI assistants. If any of that matters to you, budget for the later migration to a bigger tool.
Do we need an enterprise platform like Algolia or Coveo?
If you have a large body of content, an engineering team and an enterprise budget: yes, they are strong products and a legitimate choice. If you do not, the mismatch shows up as a months-long integration project before the first visible result. The useful question is not which platform is best, but which one fits the size of your team.
Can we just maintain a good FAQ page and use ChatGPT manually?
Yes, and it costs nothing but time. A well-maintained FAQ page is genuinely valuable, both for visitors and as source material AI assistants can read. What you give up is measurement: you will not know which questions go unanswered, whether assistants cite you, or whether last month's work changed anything.
Where does Klariton fit in this comparison?
Klariton is a fourth option: an AI answer platform where the four criteria above are the defaults rather than configuration work. Every answer shows its source, nothing publishes without human review, results are measured on your site and in AI assistants, and EU hosting, a data processing agreement and pseudonymization are built in. The free AI visibility check is the no-commitment way to see whether it is worth your time.
Before you shortlist anything, look at what AI assistants currently say about your brand. The free AI visibility check takes minutes and needs no setup. The result is your baseline: the starting point that every tool on your list, including us, has to improve on.