A selection of technical writer portfolio projects across knowledge base writing, AI documentation, and eLearning, each one a real engagement with a real client problem to solve.
Case studies
illumin Documentation Created structured technical content for a programmatic AdTech platform, translating complex advertising workflows into clear, actionable guides to drive client adoption and campaign success. [Read the case study]
CourtReserve — Sports Tech Knowledge Base Built two knowledge bases from scratch for a tennis and pickleball facility management platform, covering multiple admin roles and end users across a 13-month engagement. [Read the case study]
AI Knowledge Integration: ServiceNow Now Assist Configured and optimized the NowAssist AI agent within ServiceNow to transform static documentation into a dynamic, synthesized self-service tool. [Read the case study]
Enterprise Learning: illumin Academy Architected a certification program for a programmatic DSP, currently in soft release. I developed four certification tracks comprising 31 lessons and managed the end-to-end instructional design within Absorb LMS to establish a scalable training foundation for global users. [Read the case study]
AI Knowledge Assistant: eslwriting.org Designed and deployed a full RAG pipeline on a 12-year, 1,000-post WordPress site — from content ingestion and vector indexing to live deployment. Built the complete documentation package, including technical specification, editorial guidelines, and content governance framework. [Read the case study]
AI Knowledge Assistant — AdTech and Programmatic Advertising
A Python-based RAG pipeline built on a curated Wikipedia corpus covering programmatic advertising, DSPs, SSPs, privacy regulations, and ad fraud. Ask plain-language questions and receive accurate, sourced answers grounded exclusively in the knowledge base. Built with OpenAI, Pinecone, Flask, and the Wikipedia API. Includes cross-topic retrieval connecting regulatory content (GDPR, CCPA) with programmatic concepts in a single answer. [Read the case study]
Material Specs KB — Python RAG Pipeline
A coded Python alternative to the no-code Flowise version of this same system. Ingests 33 manufacturer PDFs from Google Drive, indexes them in Pinecone, and serves precise technical answers through a Flask chat UI. Built for clients who need to own the codebase. [Read the case study]
Material Specs KB — Flowise (No-Code RAG Pipeline)
Thirty manufacturer PDFs. Four material categories. One chat interface that returns exact specification values — viscosity, thermal conductivity, shear strength — with source citations. Built in Flowise with OpenAI and Pinecone, connected directly to Google Drive. No developer required to maintain it. [Read the case study]