Multi-Agent AI Content Pipeline: Built & Deployed

Designed and built a complete multi-agent AI content system: a 6-stage pipeline with brief interpreter, research collector, outline architect, draft writer, voice harmonizer, and QA reviewer. Fully functional Streamlit app with dual workflow pipelines, brand voice pre-flight, and human oversight gates.

6-Agent

Pipeline

6-Stage

Pipeline Framework

637

Lines of Python

The Challenge

A 21-client digital marketing agency needed to scale content production without sacrificing quality or brand consistency. Manual workflows couldn't keep pace. Writers were producing content without research backing, brand voice was inconsistent, and there was no quality gate before publication.

The Solution

Designed and coded a complete multi-agent AI content system in Python with a Streamlit frontend. The pipeline runs content through six sequential stages: brief interpretation, automated research collection, outline architecture, draft generation, voice harmonization, and QA review (each with human oversight checkpoints).

The system supports dual workflows (human-only and AI-enhanced paths), includes brand voice pre-flight checks pulled from client-specific guides, and features prompt version control so every output is reproducible. Delivered with full technical specification documentation across 7 documents covering the MVP, full systems map, editorial review gates, and pre-editorial processing layer.