Researcher
Interviews customers at scale to learn why they stay, leave, and what they would pay for.
Each AI worker owns one customer job and shares one memory of your customers. You pay for the work, not headcount.










Most teams start with the Researcher to find where revenue leaks, then add the other roles.
Interviews customers at scale to learn why they stay, leave, and what they would pay for.
Reaches customers before they go quiet, recovers failed payments, and learns why others left.
Walks every new signup to first value and collects their documents and KYC.
Follows up abandoned carts and quotes with a checkout link to close the sale.
Works down re-KYC, data refresh, and compliance reviews continuously so nothing piles up.
The roles share one memory, so context follows the customer. Win-back knows what they told research. You give a brief, not a flowchart, and each role improves with your feedback.
A lending team ran 15 effective customer interviews in two days with the Researcher, versus 2 by hand in a full week.
Customer research pilot, lendingA healthtech win-back reached inactive customers at a 25 to 30% response rate, people one-way notifications never wake.
Research deployment, healthtechA DTC e-commerce team reached 502 customers in a research run, and half replied and engaged in conversation.
Research demo, DTC e-commerceNo. Most teams start with the Researcher, prove the value, then add roles. Each new role starts with everything the last one learned.
It shows where revenue actually leaks, told by customers in their own words, before you automate around a guess. That becomes the brief for retention, recovery, and sales.
Neither. The comparable is a human customer team. We train and operate the workers, they run conversations without flowcharts, and you keep the data and decisions.
Every channel your customers use, with shared context across them. Start where they already answer and add others over time.
Book a 15-minute walkthrough and we will run the role that matters most to you.