Product descriptions:
FinThrive serves more than 50% of hospitals and health systems, including some of the largest healthcare providers in the U.S., helping them optimize revenue cycle management through their comprehensive data intelligence platform. With petabytes of healthcare data flowing through their centralized lakehouse architecture built on Databricks, FinThrive’s life sciences division faced a critical bottleneck: Responding to complex data queries from pharmaceutical companies and channel partners required manual SQL development by analysts, creating 3–5 day turnaround times that impacted response times for competitive deals. By implementing Databricks AI/BI Genie, FinThrive has transformed how they deliver real-world healthcare insights, reducing query response times from days to minutes while ensuring consistent, accurate results that empower sales teams to respond instantly to customer requests without technical expertise.
Accessing life sciences insights at scale through centralized intelligence
FinThrive’s mission centers on providing the most comprehensive revenue cycle management (RCM) platform to help healthcare providers focus on patient care and reduce reimbursement administrative burdens. As a company managing revenue cycles from patient admission through discharge and payment collection, FinThrive processes enormous volumes of healthcare data.
FinThrive’s life sciences division supports pharmaceutical and research organizations by enabling access to de-identified real-world healthcare data — used to inform clinical development, market strategy and population health insights. However, this valuable data remained difficult to access due to technical barriers. When pharmaceutical companies or data brokers submitted feasibility requests seeking specific patient population data or therapeutic area insights, FinThrive’s small team of analysts had to manually write SQL queries for each unique request.
“Every time a request comes in, it comes with different logic and different criteria,” Hari Gummakonda, Senior Director of Data and Analytics at FinThrive, explained. “Each analyst writes these queries in different ways, and we don’t have consistent answers every time. This created inconsistency and delays that could cost us opportunities.”
The manual process created a significant bottleneck in FinThrive’s ability to deliver timely insights to life sciences partners. Pharmaceutical companies often engage through channel partners who shop around multiple providers, so speed became critical to winning business. The typical 3–5 day turnaround time for complex queries can be problematic in a highly competitive market.
Democratizing data access with natural language intelligence
To address these challenges, FinThrive implemented Databricks AI/BI Genie as part of their broader enterprise lakehouse strategy built on the Databricks Data Intelligence Platform and Unity Catalog for governance. Their approach focuses on three key use cases: enabling sales teams to respond directly to customer queries, empowering internal analysts with faster insights and eventually providing external channel partners with self-service access to data.
FinThrive’s implementation leverages materialized views built on top of their Gold-layer tables containing over 100 terabytes of de-identified real-world data, sourced from their provider network and used to support research, clinical development and market insights. This architecture ensures sub-second response times even when querying datasets with billions of records. The team carefully manages data security by providing only the high-level access required for calculations rather than exposing detailed patient information, with all data thoroughly de-identified and HIPAA-compliant.
“With AI/BI Genie, our sales team can directly ask questions based on customer requests instead of coming to the technical team every time," Hari noted. “The sales team becomes more like data analysts — they can ask questions and get responses back to customers quickly, and it frees up our analysts to do more meaningful, high-value tasks.”
The natural language interface eliminates the need for SQL expertise among business users. Sales representatives can now input customer criteria directly into AI/BI Genie and receive accurate responses within minutes rather than waiting days for analyst availability. This democratization extends beyond simple queries to complex analytical requests about patient populations, therapeutic areas and longitudinal data quality that pharmaceutical companies require before making purchasing decisions.
Driving growth through consistent, scalable and trusted insights
The impact of implementing AI/BI Genie extends far beyond faster query responses. FinThrive has achieved remarkable consistency in results, eliminating the variability that previously occurred when different analysts approached similar queries with different methodologies. This reliability has become crucial for maintaining customer trust and ensuring accurate data delivery to partners.
Looking ahead, FinThrive envisions expanding AI/BI Genie access across the broader organization, including marketing teams and other business units that frequently require data insights. Leveraging the AI/BI Genie API, they’re developing integrations through Microsoft Teams for internal users and planning secure application layers for external customers, ensuring proper tracking of user activity and query attribution for business intelligence purposes.