Transforming Market Research With AI and LLMs

TRANSFORMING MARKET RESEARCH WITH AI AND LLMS

Introduction

We Collaborated With A Leading Pharmaceutical Company in The U.S. To Develop A Powerful Al-driven Platform For Market Research And Stakeholder Engagement. The Solution Harnesses Large Language Models (Lims) To Analyze Transcribed Expert Interviews, Physician Discussions, And Internal Data To Extract Insights That Support Product Positioning, Regulatory Planning, And Go-to-market Strategies.

Challenges Faced by the Client

The client needed a secure and scalable solution to:

Analyze vast volumes of transcribed market research interviews,
medical rep notes, and advisory board sessions.
Identify therapeutic area-specific trends and prescriber sentiment.
Enable real-time, interactive exploration of insights across commercial,
regulatory, and medical affairs teams.
Maintain data privacy and compliance with HIPAA and GxP guidelines.

Our Solution

1: Al-Powered Insight Engine

Integrated LLMs (OpenAl & Sonet 3.0) to uncover patterns, KOL sentiment, and emerging market opportunities.
Customized prompt chaining for pharmacovigilance signals and competitor analysis.

2: Real-Time Expert interaction

Developed a Python Flask-based, context-aware chat assistant to query transcribed conversations
Enabled commercial teams to instantly explore therapeutic nuances and market readiness

3: Enterprise-Grade Infrastructure

Deployed on AWS with role-based access, audit trails, and encrypted storage.
Utilized MySQL for structured metadata and a vector database for unstructured transcript embeddings

4: Intuitive Front-End

Angular-based dashboards for deep exploration of insights.
Designed for regulatory and commercial teams to collaborate seamlessly.

Impact

The deployment of this platform significantly enhanced the client’s capabilities in
marketing research:

Deeper Insights:

Al-based conversation analysis led to improved forecasting, better message testing, and data-backed strategic planning.

Scalability:

The AWS-based architecture scaled with growing datasets and evolving analytical demands.

Cross-Functional Enablement:

Empowered commercial, regulatory, and medical teams with real-time access to conversational intelligence.

Compliance-First Design:

Built-in HIPAA and GxP-aligned practices ensured enterprise-level data security.

Technologies Used

Programming Language and Frameworks:

Python Flask

Large Language Models:

OpenAI API, Sonet 3.0

Front-End Development:

Angular, Vanilla JavaScript

Cloud Infrastructure

AWS

Database:

MySQL, Vector Database

Conclusion

This Al-powered market research platform helped a top pharmaceutical company unlock deeper insights, shorten decision cycles, and enhance market preparedness. Interested in deploying something similar for your enterprise? Let's talk.

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