Our client, an innovator in conversational AI, provides multiple banks with fully automated AI assistance. Consequently, they need to integrate data with a variety of core banking APIs. But data orchestration is more than integrating the data, it needs to model the data in unified way in order to enable their AI assistant to operate consistently across partners.
Core banking APIs are complex, and data integration requires encapsulating dozens of unrelated entities. The most complicated task we faced was analyzing the requirements of and mappings between APIs. Different providers use different taxonomies and different functional designs to expose their services. We needed to expose them in a way that enables the data to be activated consistently by the AI platform. Throughout the process, we ensured accurate data mapping at every level using validation processes and automated verification.
In the end, we mapped 19 endpoints used by our client’s downstream assistant systems into 5 services covering dozens of functional interfaces of a third parties’ APIs. We focused our solution on two key points: planning and managing the mapping process and employing rigorous testing and verification.
Using core banking data orchestration, Lineate resolved our client’s issues with data integration across multiple APIs. As a result, our client was able to deliver a seamless conversational AI experience to their banking customers.