Userology AI - The AI user research agent for busy product teams

@shubhra_motgill When setting up, it integrates with your PRD, understands your product, and generates a guide which consists of a list of questions, tasks, instructions, and topics to it will cover. This is where you get to see how it will handle the questions.

@iftekharahmad Thanks! Honestly, it handles both really well.

For early validation, you can embed Figma prototypes, and for mature products, we support Live Product Research.

I’m personally a big fan of using it for complex flows on live products though; mostly because the AI can 'watch' the user navigate and adapt its questions based on what's happening on the screen.

Hey   @kate_ramakaieva ! Jumping in here - great question

The key is that our AI moderator works from clear study objectives that the researcher defines upfront. When you launch a study, you tell the AI exactly what you're trying to uncover - whether that's understanding pain points in a checkout flow or evaluating how users navigate a new feature.

The AI then uses those objectives as its north star. During the session, it's continuously analyzing:

• Is the participant saying something surprising or unexpected?

• Is their behavior revealing something relevant to the study goals?

• Are there gaps in understanding that need probing?

When it detects something worth exploring (like confusion, a workaround, or an unexpected mental model), it asks targeted follow-up questions to dig deeper.
For example, if the objective is "understand pain points in expense splitting," and a user hesitates or takes an unexpected path, the AI will probe with questions like "What made you try that approach?" or "What were you expecting to happen?"

We also structure studies with both high-level objectives and section-specific goals, so the AI knows what to focus on at each stage of the research session.

@yashankgoswami Great question! That balance is everything. We solve it by making every insight traceable.

The AI generates the structured report (the 'What'), but every single claim is linked directly to a video clip and transcript timestamp (the 'Why'). So you get the high-level pattern, but you can always one-click to watch the raw human moment behind it.

@odeth_negapatan1 Thanks! We know how painful it is to coordinate translators or schedule across 5 different time zones. We wanted to make 'Global Research' as easy as sending a single link. Appreciate the support!

@iamanantgupta Thanks! That was a huge focus for us. We know that data is good, but video proof is better.

The AI automatically generates an Executive Report with those clips embedded right next to the key themes. It makes it so much easier to walk into a meeting and actually show the team what users are struggling with, rather than just telling them

@iftekharahmad hanks! It works for both, but it actually shines on mature products because of our Vision-Aware AI.

Unlike standard tools that just follow a script, our AI 'sees' the user's screen in real-time. So if a user gets stuck deep in a complex workflow on a live app, the AI notices the hesitation and asks — 'I see you paused there, what were you expecting to happen?'

But it handles early Figma prototypes just as easily :)

@pasha_tseluyko Recruiting is definitely the bottleneck!

It’s actually not a manual board like Upwork. We connect you to a massive pool of 10 million+ participants.

To ensure you get that 'specific audience,' you set up rounds of screening questions. The system automatically filters that and only lets through the people who pass your specific checks. It handles all the vetting for you!

@shemith_mohanan Spot on. 💯 A summary that says 'Users found it confusing' isn't helpful.

We pushed for Traceability; meaning every AI claim is backed by a timestamped source. We want to give teams the confidence to make product changes immediately, not just 'good to know' information

@vik_sh Great question! They mostly use the Executive Report to prioritize the backlog.

Since the report highlights 'Friction Points' with severity scores (and video proof), PMs can instantly see what needs to be fixed in the next sprint without spending 3 days analyzing raw footage