Conversational agents that uncover
deep insights from users,
at scale

Use AI interviews with either voice or chat, that can do deep qualitative studies, at quantitative scale. Learn why your users do what they do.

Interview Product Screenshot

1. Skylight conducts natural voice conversations with users.

Given your product information and a study goal, it selects the most relevant users, interviews them to uncover deep insights. You can set the themes or spesific questions to ask, or let Skylight reason to automatically ask the most insightful questions.

Deep conversations, deep insights

Conversations that feel natural

No awkward scripts or robotic questions. The AI adapts as it goes, asking follow-ups that actually make sense.

Ask the Right Questions

Picks up on what users say and asks smart follow-ups.

Actually Listen

Catches the subtle stuff - tone, hesitation, what they really mean.

Find Patterns

Spots themes and opportunities you might have missed.

Make it Useful

Turns everything into reports you can actually act on.

See insights as they happen

Watch patterns emerge in real-time as conversations unfold. No waiting around for results.

Interview Started
Insights Generated
Agent

Organized by what matters to you

Set up themes like "pain points" or "feature requests" and watch everything sort itself automatically.

Voice processing
Real-time insights

Works with what you already have

Got old interview recordings sitting around? Just drop them in and get insights from conversations you've already had.

Qualitative insights at quantitative scale

5k+

Interviews

50K+

Insights Generated

1M+

Hours Analyzed

Real-time

AI Processing

Frequently asked questions

Have more questions? We are here to help. If you don't find what you need, please contact us at info@launchskylight.com

What exactly does this do?

How is this better than doing interviews myself?

Can I customize it for different types of research?

What kind of insights will I actually get?

How does this fit into what I'm already doing?

What makes this different from surveys or other tools?

Who should actually use this?