The problem AI SmartMatch solves

The problem addressed by Niti AI’s solution is to build and ship personalized user journeys in financial services. Today, financial institutions struggle to deliver contextual, data-driven experiences that adapt to individual customer needs.

1/ Complexity in building personalized experiences: Building and deploying highly personalized in-app experiences traditionally requires intensive engineering resources, long development cycles, and domain expertise, making it challenging for non-technical teams to quickly iterate and adapt user journeys.

2/ Scalability and speed of deployment: Even when solutions are built, financial institutions face obstacles in deploying them at scale, often needing app updates and extensive backend integrations, which delay time-to-market and limit agility.

Challenges we ran into

1/ Designing a user-friendly and intuitive interface for non-tech-savvy users without compromising on the depth of insights provided.

Solution: Invest time in user research and iterative testing to ensure that the interface is clean, accessible, and easy to navigate for diverse user groups.

2/ Designing AI models that provide accurate, meaningful recommendations without being intrusive or irrelevant to the user’s financial context.

Solution: Use a blend of machine learning algorithms, including collaborative filtering and content-based filtering, and continuously refine these models using feedback loops from user interactions.

3/ Challenge: As the number of users grows, so does the volume of data and processing requirements. Ensuring the platform remains fast and responsive, especially during peak usage, can be difficult.

Solution: Build on a cloud-native architecture with microservices and leverage scalable databases, caching strategies, and load balancing to handle growing demand.