Enterprise RAG AI: Private Doc Intelligence A fast-growing B2B software firm needed a secure, enterprise-grade Retrieval-Augmented Generation (RAG) system to query thousands of confidential internal documents (legal contracts, technical architecture specs, Notion pages, and employee SOPs) in real time without third-party data leakage.

Key Challenges:

High hallucination risk and irrelevant context retrieval using standard keyword search.

Managing multi-format files (scanned PDFs, tables, markdown) with strict access control based on user hierarchy.

Technical Implementation & Solution: • Engineered an automated ingestion pipeline in Python with LlamaIndex and LangChain for semantic chunking and metadata preservation. • Integrated a hybrid vector search architecture pairing dense embeddings (OpenAI text-embedding-3) with sparse BM25 indexing in Qdrant. • Added a cross-encoder re-ranking layer (Cohere Re-ranker) to prune low-relevance chunks, reducing API token costs by 40%. • Built robust Role-Based Access Control (RBAC) via FastAPI endpoints, ensuring departmental data isolation.

Results & Impact: • Dropped internal information retrieval time from 20 minutes to under 4 seconds. • Attained 98% factual precision with traceable in-line page citations. • Full on-prem Docker deployment ensuring 100% private data security.

I'd test revoking a user's document access mid-conversation. In your RBAC flow, do cached retrieval results get rechecked against current permissions before they're sent to the reranker or model?

Week 1 of moving into web design - building my first portfolio piece. For the project, I picked a fintech company that runs live auctions for debt portfolios, a marketplace where banks sell and investment funds bid in real time. Its a genuinely interesting product, but their current website looks like it was generated with AI in one go, and it doesnt properly show what the product actually is and how it works. So far I've researched the company and its market, written a brief, and started moodboarding. Its still in progress, but I like where the direction is heading.

For a product that's hard to see, I'd be curious whether the hero could simply show the auction itself, a portfolio listed and bids coming in, instead of explaining it. Are your moodboard references leaning that way?