Building Mira, an AI tool for customer research

Customer research is one of the most important things you can do when building products.

It’s also one of the hardest things to do well. Real conversations with real users reveal insights that no amount of analytics or A/B testing can match. But they take time. They’re hard to schedule. And they don’t scale.

So what happens? Teams ship features based on three interviews. Or they rely on NPS scores that tell you something is wrong but not what or why. Or they just skip the research entirely and hope for the best.

I’ve seen this pattern over and over in my work as a designer. And I’ve always wished I could have more customer conversations. Not surveys. Conversations.

Why I built Mira

The frustration had been building for years. I’d join a project, ask what research had been done, and hear things like “we did some interviews last quarter” or “the NPS is trending down.” Useful, maybe. But not enough to really understand what users need.

The problem isn’t that teams don’t value research. They do. The problem is that traditional research doesn’t scale. You can interview five people or fifty, but you can’t interview five hundred. Not with real, open-ended conversations.

When AI started getting good enough to hold natural conversations, I realized there might be a way to solve this. What if you could have AI conduct interviews for you? Not rigid surveys with preset questions, but actual conversations that adapt and dig deeper based on what people say.

That’s the idea behind Mira.

What Mira does

Mira conducts customer interviews automatically. You define what you want to learn, and Mira has conversations with your users. Real conversations that feel natural, not scripted.

It works around the clock, in any language. You can embed it in your product, send it as a link, or make it available on your website.

The magic is in what happens after. Mira synthesizes all those conversations into actionable insights. Patterns emerge. You see not just what people say, but why they say it. The depth of 1:1 interviews with the scale of surveys.

Building it myself

This is where it gets personal.

A few years ago, I couldn’t have built Mira. I’m a designer, not a developer. I can prototype in Figma and write enough HTML to be dangerous, but building a real product? That required a team.

Not anymore. Using AI to code, I built Mira myself. I designed it, and then I actually built it. The same tools that make Mira possible, AI that can hold intelligent conversations, also made it possible for me to go from concept to working product without a traditional development team.

There’s something deeply satisfying about building a tool that solves your own problem. Every feature decision came from firsthand frustration with how research works today. Every interaction was designed by someone who actually needs this tool.

What this means

Mira represents something bigger than just a research tool. It’s proof of what becomes possible when AI lets individuals build things that used to require entire teams.

I built Mira because I wanted it. Because I’ve spent years wishing for a better way to understand users. Now I have it. And now you can too.

Try Mira yourself or visit letmira.com to learn more.