Vellum
AutoResearch AI Startup Platform
Rebuilt the backend of an AI-powered startup documentation platform from Python/FastAPI into Java Spring Boot with production-oriented architecture.
Controller-Service-Repository
BCrypt & UUID identifiers
Multi-agent generation
Migration from Python to Java
The original prototype was built in Python (FastAPI). As the platform scaled to handle complex multi-agent document generation, maintaining type safety and robust enterprise patterns became critical. I led the complete rewrite into a Java Spring Boot monolith.
Layered Architecture
I enforced a strict Controller-Service-Repository pattern with constructor-based dependency injection. This decoupled our business logic from HTTP concerns, allowing us to easily write unit tests using JUnit 5 and Mockito, while keeping the API layer thin and maintainable.
RAG Pipeline for Business Documents
Currently developing a RAG-based multi-agent pipeline to generate BRDs (Business Requirement Documents) and market research. The Spring Boot backend securely manages the vector database connections, ensuring AI models are grounded with user-specific contextual data to prevent hallucinations.