PRANAV K P
Backend Dev | FastAPI, PostgreSQL, Scalable APIs
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Built a backend system for monitoring business-critical events in SaaS applications, detecting silent failures that traditional infrastructure monitoring tools miss.
Heron tracks application-level events (like payments, signups, and background jobs), learns their expected frequency, and alerts when they stop occurring—helping businesses detect issues before users report them.
Key features:
• Real-time event tracking and pattern learning
• Detection of missing or delayed business events
• Incident creation and recovery tracking with downtime calculation
• Slack alert integration for instant notifications
• Multi-project support with API key-based isolation
• Built using FastAPI and PostgreSQL for scalable backend performance
This project demonstrates my ability to design and build production-ready backend systems that solve real business problems for SaaS platforms.
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Built a real-time fraud detection backend system using FastAPI, Kafka, and PostgreSQL.
The system processes transactions in real-time, detects anomalies, and ensures high performance under load. I optimized database queries to improve response time by 60% and designed a scalable architecture for handling continuous data streams.
Key features:
• High-performance REST APIs using FastAPI
• Real-time processing with Kafka
• Optimized PostgreSQL queries
• 85%+ test coverage for reliability
• Dockerized deployment with CI/CD pipelines
This project demonstrates my ability to build scalable, production-ready backend systems.
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Developed an AI-powered backend system that generates and optimizes SQL queries from natural language input using FastAPI and NLP models.
The system allows users to interact with databases more efficiently by converting plain English queries into optimized SQL, reducing manual effort and improving productivity.
Key features:
• REST APIs built with FastAPI for seamless interaction
• Natural language to SQL conversion using NLP models
• Optimized SQL queries improving execution time by 40%
• Integration with PostgreSQL for real-time data retrieval
• Automated CI/CD workflows and testing for reliability
This project demonstrates my ability to integrate AI capabilities into scalable backend systems.
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Developed a backend utility that automatically generates SQL schemas from Pydantic models, simplifying database setup and reducing manual effort.
This tool helps developers quickly convert data models into structured SQL schemas, improving development speed and consistency in backend systems.
Key features:
• Automated SQL schema generation from Pydantic models
• Clean and modular Python architecture
• Reduced manual database design effort
• Integrated testing and version-controlled workflows
• Designed for scalability and easy integration into backend systems
This project demonstrates my ability to build developer-focused tools that improve productivity and streamline backend workflows.
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