A digital platform that redefined how renting works in the UK

Renting a home in the UK often means paying a large deposit upfront and going through time-consuming checks. People are asked to provide a packet of documents, fill out multiple forms, and collect references to prove they are trustworthy. And even if they always pay rent on time, it rarely influences their credit score. A London-based PropTech startup set out to change this. The idea was to develop a platform to digitize the entire screening process, help users build a credit score through rental payments, and offer landlords and agents a much faster, more data-driven way to assess tenant risk.

To bring their product vision to life, the founders turned to an external software development vendor. The plan was to build a microservice-based, easy-to-scale system to support financial integrations like Open Banking and credit reporting. The direction was well thought out, but the process turned out to be more complex than expected.

Although the system followed a microservice-based structure in theory, its architecture lacked the consistency needed for smooth operation. Some services didn’t communicate reliably, performance was poor, and the overall setup made the platform harder to support and scale. This placed the solution at risk of losing competitiveness. Without a reliable technical system, the startup couldn’t deliver on its promise of helping users build a credit profile or attract B2B partnerships with landlords, letting agents, and service providers.

With a regional product launch approaching, the company needed an experienced team that could step in, take responsibility quickly, and get the product back on track. At that point, one of the startup’s investors—who had previously worked with EffectiveSoft—recommended approaching us. The company followed this advice, leading to a partnership that has lasted more than five years.

Working under tight deadlines, we focused on the most critical areas:

• Performing an extensive code review and deep refactoring of the apps.
• Building a new architecture and using it to redevelop flawed code.
• Redesigning the database architecture to add new functionality.
• Creating new UX/UI design for mobile and web platforms to enhance user onboarding, data presentation, and usability across all portals.
• Setting up CI/CD pipelines and introducing a proper staging environment to ensure safer, faster releases.

Once that foundation was in place, we could finally concentrate on what mattered most: creating a seamless, secure experience for renters and agents through reliable, well-designed apps.

We kept moving forward despite late-arriving requirements, missing details, tight deadlines, and frequently changing priorities. Working under these conditions required flexibility, and our Agile process—with regular sprints, backlog grooming, and rapid iterations—allowed us to continuously reprioritize and adapt. It wasn’t easy, but it gave us the opportunity to improve our skills, think beyond execution, and make valuable contributions.

External data integration

One of the most complex elements of the system was the deep integration of user financial and behavioral data from multiple sources into a unified profile. The platform aggregated banking data through Open Banking, credit history from Experian, and employment and rent history into a comprehensive user snapshot. Each source came with its own structure, reliability level, and integration constraints.

Additionally, our team integrated Plaid—an Open Banking platform we had successfully used in previous projects—which greatly accelerated the verification of users’ income and rent payments.

Risk assessment interface

Originally, the founders planned to show agents raw financial and behavioral data and let them draw their own conclusions. To facilitate decision-making, we built a complex rule-based system that analyzes user data for various red flags—credit score, documentation mismatches, or residential history gaps—and generates targeted warnings for agents.

We customized these rules for each large agency, adding specific screening criteria to the default set. As a result, the same user can be assessed differently by different agencies according to the organization’s individual policies.

Fraud detection

As the platform matured, we started noticing fraudulent behavior patterns, such as users connecting someone else’s bank account to appear financially sound. This created a risk for both agents and landlords who relied on that data for screening. To address this issue, our team suggested a protection mechanism that flagged mismatches between the tenant’s identity and the bank account holder’s name. We also enabled agents to manually flag users within the admin system when they noticed signs of fraud. This approach helped reduce the risk of false approvals and added an extra layer of control to the screening process.

Over the course of our five-year partnership, the company grew from a chaotic early-stage startup into a mature, high-performing product with over 500,000 renters. The company raised over £20 million in funding, expanded its B2B partnerships, acquired its direct competitor, and became one of the top three players in the UK rental market.