Leveraging our client’s data assets, we built a modern data platform deployed on Azure Cloud. In phase one, our client had partnered with Palantir Foundry (using a rules-based approach) based on a data dictionary and discovery framework developed by Infogain. We took over the support and maintenance of phase one and initiated phase two enhancements.

We improved entity resolution processes through machine learning and identified critical gaps by auditing existing data assets and processing infrastructure.

Collaborating with a vendor team, we built two custom statistical enrollment models using the existing platform and developed a machine learning-based synthetic tagging approach.

An analytics data workflow was designed to efficiently manage and process both internal and external data sources.

Databricks was leveraged for efficient, scalable data pipelines, improving performance, and avoiding licensing costs.

To support new products, we built seven AI models using Databricks. Our client can use vocal biomarkers to predict depression and improve patient care. They can provide real-time transparency in participant recruitment and retention, identify principal investigators and more.