The product
Pendella is a digital life-insurance platform that uses AI to personalize coverage. It serves two audiences: employees, who receive tailored policy options through their employer, and consumers, who can secure coverage directly — in under ten minutes, through a three-step process.
The problem
Life-insurance applications are traditionally long, unfamiliar and easy to abandon. Pendella’s product bet is that a well-designed sequence of questions, followed by a personalized recommendation, can remove most of that friction.
What made it complex
- The flow is the data collection. Every answer feeds the personalized suggestions, so what is asked, and how answers are captured and validated, directly shapes the result.
- A long-term financial decision. Users are choosing cover that lasts years; clarity and trust matter as much as speed.
- Two channels, one product. Employer-provided and direct-to-consumer journeys serve different audiences with different expectations.
My responsibility
I worked on the functional steps of the application flow — the sequence in which users answer questions and receive personalized insurance package suggestions — with the aim of making the process shorter and easier to complete.
Why it matters
Pendella is work outside gaming, in a regulated, financial-services domain. The engineering problem is familiar from any complex product: turn a complicated process into a sequence of simple, reliable steps, where the structure of the flow is itself a product decision.
What changed
The guided steps are the core of Pendella’s promise to users: personalized coverage in three steps and under ten minutes.
