Deduplication of Graphitic RAG Evidence Segments in lucidRAG

NOTE: This is not a conventional blog article. It is a technical spec written for a concrete feature in lucidRAG. I iteratively feed this document to code-focused LLMs during development to reason about trade-offs, validate assumptions, and converge on a…

StyloFlow: Constrained Fuzzy Signal-Driven Workflows

I built StyloFlow because I kept writing the same pattern over and over: components that react to what happened before, emit confidence scores, and sometimes need to escalate to more expensive analysis. Existing workflow engines wanted me to think in terms of…

DocSummarizer Part 5 - lucidRAG: Multi-Document RAG Web Application

This is Part 5 of the DocSummarizer series, and it's also the culmination of the GraphRAG series and Semantic Search series. We're combining everything into a deployable web application. 🚨🚨 PREVIEW ARTICLE 🚨🚨 Still working out some kinks and adding…

Zero PII Customer Intelligence - Part 1: The Philosophy

What This Series Builds This series builds a working ecommerce system that proves you can have sophisticated customer intelligence without storing personal information. What We Build How It Works Semantic segmentation Vector embeddings group similar interests…

Zero PII Customer Intelligence - Part 1.1: Generating Sample Data (and Images) Locally

In Part 1 we covered the philosophy: transparent segmentation without PII. Part 2 covers session profiles, signals, and segment definitions. But first: how do you validate any of this without ever touching real customer data? For this series I generate a…

Zero PII Customer Intelligence - Part 2: Profiles, Signals & Segments

In Part 1 we covered the philosophy and series overview. In Part 1.1 we built the sample data generator. Now let's build the core system. This part focuses on: Zero-PII profile architecture - Ephemeral sessions vs persistent profiles Signals and weights - What…

DocSummarizer Part 4 - Building RAG Pipelines

NuGet npm .NET Node.js This is Part 4 of the DocSummarizer series. See Part 1 for the architecture, Part 2 for the CLI tool, or Part 3 for the deep dive on embeddings. The hard part of RAG isn't the LLM. It's everything before the LLM. You've probably seen the…

DataSummarizer: Fast Local Data Profiling

Most “chat with your data” systems make the same mistake: they treat an LLM as if it were a database. They shove rows into context, embed chunks, or pick “representative samples” and hope the model can infer structure, quality, and truth from anecdotes. It…

DocSummarizer Part 3 - Advanced Concepts: The "I Went Too Far 🤦" Deep Dive

This is Part 3 of the DocSummarizer series: Part 1: Building a Document Summarizer with RAG - The architecture and why the pipeline approach beats naive LLM calls Part 2: Using the Tool - Quick-start guide for the CLI Part 3: Advanced Concepts (this article) -…

DocSummarizer Part 2 - Using the Tool

GitHub release .NET Version This is Part 2 of the DocSummarizer series. See Part 1 for the architecture and patterns, or Part 3 for the deep technical dive into embeddings and retrieval. Turn documents or URLs into evidence-grounded summaries - for humans or…