Irving-based Pieces, a healthcare AI company that addresses clinical and social determinants of health, has acquired fellow Dallas-based company Bowtie Business Intelligence, a data management and intelligent company that connects organizations to nearly any data source.
Pieces aims to help organizations streamline clinician workflows and improve patient outcomes. Its technology, Pieces Predict and Pieces Connect, creates a comprehensive solution for connected community health.
Through the intelligent software and services, like cloud-based AI, clinically-based natural language processing and and physician-supervised machine learning, Pieces is able to real-time interpret patient information and link health systems to community-based organizations.
Overall, the goal is healthier outcomes—in and out of the hospital.
With the deal, Pieces will be able to enhance its analytics and reporting capabilities to turn data into actionable insights, allowing the company to maximize its impact on the community. Bowtie Business Intelligence (Bowtie BI) enables data interoperability for organizations of any size, allowing them to have advanced reporting and analytics.
“The Bowtie platform will enhance the interoperability and reporting capabilities of our current solutions to create an even richer data ecosystem for our clients,” Pieces President Fayiaz Chaudhri said in a statement. “By leveraging Bowtie’s data platform and flexible APIs, Pieces can quickly connect to nearly any software system used by community and healthcare customers and provide deeper, more actionable insights as they strive to make a difference in the lives of those that they serve each day.”
Bowie BI’s platform—dubbed ‘extract, transform and load’ (ETL)—is lauded by the company as a powerful data management tool. Organizations are able to take complex data sets and turn them into a scalable, secure single spreadsheet, regardless of the systems already in place.
This allows businesses to be managed at an affordable price point, Bowie BI says, which is beneficial to community orgs and nonprofits. And, it makes the data actually useful for analytics, reporting, and other use cases.