One of the Leading Healthcare Product Company intended to improve patient satisfaction by recommending videos based on various parameters
Legacy recommendation engine driven based on pre-defined set of rules, that recommends users based on preset interest category or Health service provider’s preset video options.
Client needed to move towards a much more personalized solution that takes into account Realtime feedback and makes recommendations accordingly
The solution is deployed across various Health care Institutions where the videos are aggregated from content providers and stream them for the end user;
Evaluated AWS Personalize Vs. Custom Solution and Created connectors with client data sources by defining glue data catalog
Raw Data is dumped to s3 and further processed to publish to Dynamo DB and Models were trained on CPU based EC2 Compute instances and served based on docker pod scaling architecture
An API that generates recommendation scores for the videos watched by the
A feedback loop that aggregated changes to