On the front lines, field teams had access only to static dashboards with limited interactivity. They couldn’t ask follow-up questions of their data, couldn’t surface insights on demand, and couldn’t act with the agility the market required. Meanwhile, coaching and performance feedback data sat in unstructured formats, requiring laborious manual processing before any meaningful pattern could be extracted.
Together, these inefficiencies compounded. The organization was carrying the weight of a data infrastructure that had served it well in a previous era but couldn’t support the speed, scale, or personalization that modern commercial operations demanded. The cost wasn’t only operational. Delayed reimbursement processing, incomplete HCP views, and slow therapy initiation had direct consequences for patients who needed faster access to care.
Solution
To lead the modernization, the company partnered with our experts at Brillio, selecting the firm for its pharmaceutical domain expertise, full-stack agile delivery model, and hybrid Core-Flex resourcing approach designed to maintain continuity without disrupting ongoing operations.
We executed a multi-pronged transformation across five workstreams. First, commercial operations were unified by integrating IQVIA, CRM, claims, and sales data into a 360-degree HCP-patient view built on Snowflake, Tableau, and Spark, giving field representatives a complete picture of each engagement.
For financial operations, our team deployed an LLM-powered chatbot integrated with Snowflake Cortex Analyst. The chatbot automated SQL query generation and delivered contextual insights through natural language interactions, removing the manual bottleneck entirely. Contract data retrieval was addressed through GenAI-powered chatbots that extracted and classified metadata from unstructured contracts stored in Snowflake, cutting retrieval time significantly.
Static reporting was replaced by a Snowflake-based conversational chatbot embedded directly in Qlik dashboards. Field teams could now generate insights through natural language queries and engage in multi-turn conversations with their data in real time. Finally, coaching and performance feedback data were made actionable through a Cortex LLM-powered chatbot that combined structured metrics with free-text sentiment analysis, surfacing competency trends and performance themes at scale.
The deployment was consulting-led and phased, reinforced by SLA-backed governance models, KPI tracking, iterative feedback loops, and end-to-end operational support covering incident management and platform monitoring.
