Tagged
#rag
11 articles
Document parsing for AI: PDFs, tables, and the messy rest
Before a model can reason over your documents, something has to turn them into clean text. That unglamorous step quietly decides everything downstream.
Retrieval-augmented generation (RAG), from first principles
RAG is often explained as a stack of tools. Strip that away and it is one simple idea: let the model read the right material before it answers. Here is how it really works.
Choosing an embedding model for your project
Picking an embedding model is less about leaderboards than fit. Here is what actually decides whether retrieval works for your data and your budget.
Document Q&A that actually works: patterns and pitfalls
Asking questions over your own documents is the most useful AI demo and one of the easiest to get quietly wrong. Here are the patterns that survive real use.
Vector databases without the hype: what they do and when you need one
Vector databases became a buzzword overnight. Here is what they actually do, the problem they solve, and the honest signs you do or do not need one.
Add citations to AI answers
Citations turn an unverifiable answer into a checkable one. Here is how to get a model to cite its sources, and to cite them honestly.
Chunk documents well for retrieval
Retrieval is only as good as its chunks. Here is how to split documents so the right passage comes back whole and in context.
Build a simple RAG pipeline: a conceptual walkthrough
Retrieval-augmented generation, built up one stage at a time. No magic, no specific stack — just the shape of the pipeline and the decisions that matter.
Fine-tuning vs RAG vs prompting: a decision guide
Three ways to make a model do what you want — and most teams reach for the heaviest one first. Here is how to choose in the right order.
AI search inside your company: the realistic version
Ask a question, get an answer from all your internal documents. The demo is magic. Here is what makes it hard once real data and real permissions arrive.
Putting an LLM in customer support: what breaks first
A support chatbot is the easiest AI demo and one of the hardest things to run well. Here is where real deployments break — and what separates the ones that survive.