Automated phone calls that help parents collect alimony payments using three bits of data

radiCall is a Polish startup that helps parents collect alimony payments.

The founders set up the company in 2019. In just one year, they’ve built a thriving community of 6,000-plus parents and legal experts — and rolled out a service that has significantly improved the success rate of alimony payment collection.

radiCall believed the only way to resolve the issues was to create an AI-enabled application: a means for parents to communicate with alimony debtors in an indirect way to improve the rate of maintenance payment.

The team called on DLabs.AI to work as a technical partner.

First, DLabs.AI was responsible for developing a minimum viable product. It served as a way to carry out closed testing before the application would become available to the general public.

The closed tests included consultations with a select group of parents alongside the Association for the Maintenance of Maintenance Matters ‘For Our Children.’ Once the closed tests were complete, we assessed feedback and adapted the development roadmap to reflect the end-users’ needs.

Today, the radiCall offering is an intuitive web application that uses simple information to nudge a debtor when payment falls due.

The nudge comprises automated phone calls made by the application on a predefined frequency over a selected time period — with each call coming from a different phone number.

The solution is effective as it focuses on five core areas:

Simplicity was the driving force of the app design. Users only need to enter three bits of data: the debtor’s phone number, the frequency of calls, and the message to relay.

The app takes care of the rest.

The application deals with sensitive information (that of the user and the debtor). Therefore, it is imperative it handles it with care.
The solution uses industry-standard encryption to protect all details — and never discloses the actual user’s data — while an extensive database of caller numbers adds another layer of user protection.
Moreover, as the caller system uses speech synthesis software supported by advanced artificial intelligence to relay a message as if spoken by a real person, the user never has to talk to the debtor directly.
Thus, the application eliminates the risk of the user suffering verbal abuse or enduring vulgar language.

The performance of the application relies on the quality of its architecture. DLabs has plenty of experience building fast, secure, and mobile-first web applications using ReactJS. And it made sense to leverage the skillset for this project.

Using ReactJS meant we could bootstrap development using existing solutions as a template for the code baseline, CI, and testing. At the same time, mockups of each interface allowed us to build a set of reusable components to serve as the basis for developing the rest of the in-app UI.

We created forms using a state-controlled approach, offering the flexibility to process information quickly for use in validating forms and formatting data.

Ultimately, the setup ensured the backend systems receive well-structured, high-quality data that’s fit-for-purpose for powering machine learning models. As a result, we can continually improve the system as we better understand the user’s needs.

The application’s success relies on giving users transparency over the process. This is achieved via a reporting feature that shows the status of calls made, which a user can view at any time, reviewing ‘completed calls’ and ‘calls in the queue.’

The user also has the option to modify how the app contacts the debtor: that could mean altering the frequency or period of calls — or adapting the spoken message.

radiCall identified a ‘lack of legal and substantive support’ as a key area of concern for parents. Therefore, it was critical to include this in the application, along with improving the actual collection of alimony.

A thriving community of 6,000-plus parents and legal experts now shares advice on alimony collection — as well as discussing possible solutions where complications arise.