Enigma Content Pipeline

TypeSystems

OrgEnigma Technologies

Dates2025-26

Summary

I built an agentic research pipeline for data journalism: queries, entity resolution, analysis notebooks, and bulletproof verification leading to published investigations.

Project Notes

My work at Enigma was powered by an agentic research system for data journalism. The system balanced automation and human steering to dramatically accelerate the most challenging aspects of data-driven reporting: how to ask precise questions of a dataset and build a verified path from sources to claims, all the while maintaining close human oversight of automated steps.

I built that pipeline from warehouse queries through local analysis (Databricks, DuckDB, Marimo) and into agent-assisted research workflows that reused the same checks and criteria across topics. The aim was modest and operational: preserve method across sessions, including what was queried, what a result meant, which verification steps had run, and when a human still had to decide.

The investigations listed below are outputs and stress tests of the system I built, published under Enigma’s institutional byline. The stories follow shell companies, mass litigation, licensing carve-outs, and jurisdictional patterns, but they are best read as evidence that the pipeline could carry a story from raw records to a publishable claim. Specific counts and case examples (for instance Schedule A litigation in RECAP, or state registration data joined to federal licensing) live in those pieces; the durable product of the work is the method underneath them.

Related systems work at Enigma included reusable research skills, entity-resolution clients, and multi-model evaluation (see Content Engineering at Enigma).