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A global contract development and manufacturing organization (CDMO) specializing in drug substances, products, and analytical services struggled with fragmented competitive and regulatory intelligence. Partnering with Data Science Dojo, they built an Azure Synapse-powered platform with AI agents to automate data extraction, centralize knowledge, and deliver timely, actionable insights.
The competitive intelligence and regulatory affairs teams at a global CDMO relied on manual processes to track critical industry updates through a patchwork of disconnected platforms. Regulatory notices from FDA dashboards, inspection data from OpenFDA, competitor updates from Feedly, and filings from SEC Edgar all lived in silos, each demanding manual downloads, formatting, and interpretation. With more than 1000 new documents and articles appearing every month, analysts struggled to keep pace, often discovering meaningful insights only after decisions had already been made. Delays stretched from days to weeks, and with no centralized structure to compare trends or cross-reference events, leadership lacked a dependable view of emerging risks or market movements.
The organization knew that in a tightly regulated, highly competitive domain, this fragmented approach was unsustainable and was limiting its ability to act proactively.
Data Science Dojo engineered a robust automation framework using Azure Synapse for data pipelines and AI agents for intelligent querying, transforming disparate sources into a unified, secure intelligence hub. Azure Synapse became the backbone of ingestion, orchestrating pipelines that pulled data from FDA, OpenFDA, Feedly, SEC Edgar, and internal competitor resources. PySpark notebooks standardized and transformed raw feeds, while Azure Data Lake Gen2 and Blob Storage provided scalable storage so regulatory events, filings, and news articles could be archived, queried, and traced over time. SharePoint and file shares served as accessible distribution layers for team-specific reports. On top of this foundation, AI agents built using a ReAct architecture with retrieval-augmented generation allowed users to ask natural-language questions about inspections, citations, competitor movements, biologics trends, or shifts in market positioning, receiving immediate and context-aware responses.
This intelligence platform brought structure, automation, and AI-driven reasoning to a previously chaotic workflow, and hence, turning competitive intelligence from a manual task into an automated strategic solution that drives both compliance and business growth.