Why Intimeros spent 500 hours testing 50 AI companion apps
Mia Morin is Editor & AI Quality Analyst at Intimeros, a site that evaluates AI companion apps through hands-on testing. Morin and a colleague logged 500 hours across more than 50 apps to judge conversation quality, privacy and what actually happens after weeks of use – a process that defines their reviews and reader trust.
Human, hands-on testing remains essential for judging whether AI companions feel emotionally real and for protecting reader trust; AI is useful for background research but cannot replace human judgment on conversational authenticity.
What’s the quick origin story of your business, and what makes what you do genuinely different from the other options your customers are looking at?
When Intimeros began, most of the coverage of AI companion apps was either a list of promotional apps or a rehash of marketing copy. No one was actually spending time in these apps. I proposed that we focus on real-world testing. My colleague and I then spent 500 hours testing 50+ apps, testing conversation quality, privacy and what really happens after using those apps for weeks.
Where does most of your new business come from today, and where do you wish it came from?
The majority of traffic is from organic search and readers who are comparing certain apps before subscribing. I’d be happy to see more from word of mouth and community, as people would have faith in a recommendation from someone they follow.
What’s one thing you’ve actually handed over to AI in the last year, and one thing you tried it on and went back to doing the human way?
We use AI to quickly gather background research before we start testing. We tried using AI to judge whether chatbot conversations felt emotionally real, but we handed that job back to humans. A computer can only guess, so deciding if a conversation actually feels real takes a real person.
Have you noticed a change in how customers find you or what they already know before they reach out? Is anyone arriving through AI assistants like ChatGPT yet?
Now readers are better informed. Many have a specific app in mind and are looking at features before they get to a review. We’re starting to see early traffic referred from AI assistants, still small, but it’s clearly growing month over month.
If you were advising someone in your industry on all of this for the next 12 months, what would you tell them to actually do, and what would you tell them to ignore?
Do the actual testing yourself, hands-on time is the one thing AI still can’t fake convincingly for a reader. Don’t rush to publish before you are sure. A bad review in this space is a loss of trust that will take months to rebuild.
Thank you to Mia Morin and the team at Intimeros for sharing what actually worked with Leaders Perception readers.
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