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#rag

Retrieval augmented generation, or RAG, is an architectural approach that can improve the efficacy of large language model (LLM) applications by leveraging custom data.

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SELFTEST Production Document Ingestion and Structure-Aware Chunking

SELFTEST Production Document Ingestion and Structure-Aware Chunking

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10 min read
My RAG Chunk Was Timestamped 00:01:25. Its First Words Were Spoken at 00:00:56

My RAG Chunk Was Timestamped 00:01:25. Its First Words Were Spoken at 00:00:56

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6 min read
Make your AI assistant answer only from what each person may see

Make your AI assistant answer only from what each person may see

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3 min read
Evaluating RAG — retrieval + generation metrics that matter

Evaluating RAG — retrieval + generation metrics that matter

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8 min read
Agentic search over a hierarchy of document clusters

Agentic search over a hierarchy of document clusters

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6 min read
Architectural Deep-Dive: Qdrant Vector DB: v1.20.0

Architectural Deep-Dive: Qdrant Vector DB: v1.20.0

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3 min read
Day 07/90:Taking RAG from Notebook to Production — Challenges and Research-Backed Solutions

Day 07/90:Taking RAG from Notebook to Production — Challenges and Research-Backed Solutions

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3 min read
RAG vs CAG vs KAG: Choosing the Right Context Layer in NodeJS

RAG vs CAG vs KAG: Choosing the Right Context Layer in NodeJS

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9 min read
What I Learned Building a RAG Chatbot From Scratch: 3 Lessons

What I Learned Building a RAG Chatbot From Scratch: 3 Lessons

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2 min read
Can Retrieval Tell Which Source to Trust?

Can Retrieval Tell Which Source to Trust?

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12 min read
Understanding RAG: When AI Needs to Open a Book Before Answering

Understanding RAG: When AI Needs to Open a Book Before Answering

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8 min read
Turn PDFs (even scanned ones) into RAG-ready chunks with one API call

Turn PDFs (even scanned ones) into RAG-ready chunks with one API call

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4 min read
Healthcare Search Boundaries — Isolating Appointment Context Across Tenant Collections

Healthcare Search Boundaries — Isolating Appointment Context Across Tenant Collections

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8 min read
5 Ways to Make Insurance Claims Retrieval Deletions Trustworthy — A Build Log

5 Ways to Make Insurance Claims Retrieval Deletions Trustworthy — A Build Log

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5 min read
Day 06/90: Reranking in RAG — When the Right Evidence Isn’t Ranked First

Day 06/90: Reranking in RAG — When the Right Evidence Isn’t Ranked First

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5 min read
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