[ ABOUT ]
Richard Callaghan
I'm the founder of HospitalCost.com — independent consumer intelligence on top of public hospital pricing data — and VirginiaCourtFile.com, public-records analysis of Virginia criminal courts. Both built solo.
By day, I'm a Senior Marketing Manager at Microsoft. The day job and the founder work aren't in competition — both reward the same discipline: methodology over noise, the decision over the output, trust over reach. I write about what compounds across both.
I'm not building a price-comparison tool. I'm building something patients, journalists, and academics can rely on — independent, transparent about its sources, and held to a standard people can verify.
That's the work. Everything on this site is built around it.
[ WHAT I BELIEVE ]
Trust compounds, features depreciate
Anyone can ship more features. The work that holds up over time is the work people can verify and cite. That's what gets built here.
Decisions are expensive, information is cheap
The machine hands you output for free. What compounds is the record of what you chose and why, especially the times you overruled the confident answer and were right. That log is the one thing nobody else can reproduce.
AI makes good calls better and bad calls faster
AI makes good decisions better and bad decisions faster. Without a clear point of view going in, you get more output, not better outcomes.
Patient-first, not engagement-first
The right question is whether the tool makes the 2am moment better for the person in trouble. If the answer's no, the click-through rate doesn't matter.
[ WHAT I FOCUS ON ]
Civic Data Accountability
Public datasets the people they're meant to serve can't actually use
Trust Engineering
Building data tools people can verify, cite, and rely on
Decision Quality
The decision over the output. Frameworks that compound. Knowing what not to do.
[ BEYOND WORK ]
When I'm not building or writing, you'll find me:
Family First
Spending time with the people who matter most
[ WHEN HOBBIES MEET CODE ]
OcheIQ
Film a 3-dart visit, get instant mechanics analysis. Computer vision tracks each throw and tells you exactly which dart drifted and why.
Throw Corridor
See exactly which dart drifted — and why.
OcheIQ detects each throw automatically, tracks 5 mechanics metrics, and gives you feedback-first insights — like “Dart 2 rushed by 0.65s” — so you know exactly what to fix.
Throw Corridor Pattern
Color-coded ribbon shows where throws drift
Side-by-Side Comparison
Compare steadiest vs. outlier throws
Wrist Heatmap
Release point clustering with tightness scoring
AI Coaching Drills
Targeted drill for your weakest metric
Let's connect
Building something in civic data, public-records accountability, or consumer-facing data products? Working with a journalist on a story I might be a source for? Always happy to talk.
Get in Touch