How Real Chemistry Cut Healthcare AI Prototyping from Months to Days with Databricks Apps

Real Chemistry partners with life sciences and healthcare companies on some of the most data-intensive challenges in the sector: identifying undiagnosed patients with rare diseases from clinical data, mapping complete patient journeys from social media and health records, measuring pharmaceutical ad campaign effectiveness, and surfacing insights to commercial teams. The analytics group builds advanced AI models against these questions, but the organisation faced a consistent bottleneck: getting those capabilities into the hands of non-technical experts.

Before Databricks Apps, building a custom application to expose an AI model to a marketing professional or business analyst required a dedicated team managing full-stack development, infrastructure provisioning, and application hosting. The average build time was six months to a year per application — too slow to match the pace of client needs or data science output.

Real Chemistry adopted the Databricks platform approximately three years ago to consolidate data infrastructure and eliminate manual connections between disparate data sources. Delta Lake provided reliable storage; Unity Catalog provided unified governance with fine-grained access controls that kept healthcare privacy requirements intact. 'Once we put all our data together inside Databricks, it became accessible for everybody, and we could expand how the data was used, producing results faster than before,' said Rocket Williams, SVP of Technology.

When Databricks Apps launched, the AI engineering team moved quickly to adopt Agent Bricks for building intelligent, agentic applications. The first applications handled information extraction, data annotation, and unstructured-to-structured data transformation — use cases that had previously required specialist engineering support per request. The most popular application became an 'easy button' interface giving analysts access to a menu of pre-built agents covering the team's most common analytical workflows.

The timeline shift was immediate. Proofs of concept that had taken months now deploy for testing within a week, enabling rapid iteration. One example: HealthGEO, an application that analyses what large language models say about Real Chemistry's clients and products across content and sentiment, was built end-to-end on Databricks Apps — data ingestion, NLP pipeline, analytics, data agent orchestration, and a custom frontend, all within the platform. 'That includes data ingestion, scalability, NLP, an analytics pipeline, plus data agent work — all working behind a custom frontend,' said Helene Brashear, VP of AI Engineering.

Real Chemistry is now rolling out Databricks Apps to over 200 users across the organisation, giving data scientists, analysts, and business professionals self-service access to agentic AI workflows that previously required specialist support tickets.