Perplexity AI Integration for Data Analysis

Published on Jun 07 2025 by Avinash Veerella

Client: Global Data

Role: Senior Software Developer

Skills used: C# 13, NET Console Application (ASP.NET Core / .NET 8), Perplexity API, Amazon SES, Windows Scheduler.

Tools used: Visual Studio 2022, SQL Server Management Studio 19.

Description

Developed a high-performance console application that integrates with Perplexity AI’s “sonar-reasoning-pro” model to extract and analyze drug profiling insights from unstructured pharmaceutical data. The system transforms AI-generated content into structured formats to support new drug research and decision-making.

Responsibilities

• Integrated Perplexity AI’s API using RESTful services to send structured prompts and receive intelligent, context-aware responses.
• Designed and implemented data models for seamless JSON serialization/deserialization of request and response payloads.
• Built a dynamic prompt management system, enabling tracking, auditing, and batch execution of analytical queries.
• Transformed raw AI outputs into structured data to support pharmaceutical profiling workflows.
• Implemented robust error handling and logging, ensuring reliable API interaction and troubleshooting.
• Optimized batch processing logic, improving throughput and minimizing latency in large-scale data analysis.
• Used Dapper ORM for high-performance interaction with SQL Server, enabling fast data storage and retrieval operations.