Years of customer research taught us one thing.
We've spent years in innovation consulting, working alongside product, brand and strategy teams across pharma, energy, FMCG, travel and finance. Running discovery, validation and concept testing for teams trying to build the next thing.
The pattern was unmistakable. The work that moved the needle most always started with talking to real customers. And yet, again and again, we saw teams structurally talking to their customers too little.
Not because they didn't believe in it. Because the maths didn't work. Teams doing research themselves got a fraction of the budget it needed. Teams that outsourced it waited months for answers. And if a question was forgotten along the way, there was no second round. By the time the insights landed, the decision had often already been made.
So we kept asking the same question: what if running a customer study was as fast and affordable as writing a brief?
Echo started as an after-work experiment around that question. Could the latest generation of AI, grounded in real research and checked against real interviews, take on the front 80% of a customer study? So that the time and budget for human research go where they matter most.
Along the way, we looked closely at how others were approaching synthetic research. Most of it was built for numbers: multiple-choice answers at scale, fast but shallow. That wasn't what we were after. We wanted to understand the why: the long, open answers a real interview gives you. Get the why right, and you can turn it into numbers whenever you need them. Get only the numbers, and the why is lost. So that's what we set out to build.
Today Echo is a standalone product, used by product and insights teams across companies. The mission hasn't changed since the first sketch: help teams unlock customer insight more, better and faster.





