TU Delft Ms CS - RAGs, LLMs, NLP

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Abhishek Kuber  • Peerlist

<ul><li>Built a RAG application that ingests user-uploaded documents and websites to enable context-aware question answering over multi-modal data (text, images, tables).</li><li>Architected the full knowledge pipeline from ingestion to answer generation, covering parsing, chunking, embed- ding, retrieval, reranking, and citation-backed responses.</li><li>Developed agentic workflows and asynchronous job processing to keep long-running ingestion tasks off the server and the product responsive under load.</li><li>Integrated secure user authentication and provisioning, and wired the system to handle large-scale unstructured content reliably from upload to storage.</li><li>Strengthened observability and debugging with end-to-end trace analysis, then shipped the application as a modular containerized stack on AWS with a PostgreSQL backend.</li><li>Tech Stack: Next.js, TypeScript, TailwindCSS, Clerk — Python, FastAPI, PostgreSQL, Amazon S3, Redis, Celery — LangSmith, LangChain, LangGraph, <a target="_blank" rel="noopener noreferrer" class="break-all link-break text-gray-500 hover:underline" href="http://Unstructured.io">Unstructured.io</a> — Docker, AWS</li></ul>