ChrionML® transforms Zillow’s published ZHVI market histories into quality-checked datasets, independently evaluated forecasts, and decision-ready findings—with transparent methods, limitations, and source links.
64-city intelligence · research archive
Four matchups. Eight city models.
Explore four published matchups covering eight condo markets, with model forecasts, validation results, and source data. Forecast target months are labeled for each study.
Featured research · Week 04Published · October 14, 2026
Brooklyn vs. Philadelphia
Brooklyn · 11201
$1,308,132
+0.16% forecast
Philadelphia · 19107
$257,048
-0.29% forecast
Brooklyn leads forecast index value; Philadelphia has lower scale-adjusted backtest error (0.170% vs. 0.285%). October 2026 · Holt damped trend / Holt damped trend
SIGNATURE INTERACTIVE EXPERIENCE · WEEK 01 RESEARCH BETA
Don't just read the forecast. Run the model.
Explore published condo-market research, train an experimental forecasting model in your browser, and evaluate forecasts against a baseline. Boston vs. Providence is live; additional markets will launch after validation.
Ithaca growth since 2020+29.5%Observed cumulative change
Applied machine-learning projects
Real data. Reproducible evaluation. Operational context.
Project 01 · Forecasting
From published market history to decision-ready evidence
ChrionML® locates the appropriate Zillow ZHVI geography and housing-type series, compiles and quality-checks the monthly dataset, compares time-series candidates, runs chronological backtests, quantifies uncertainty, and publishes the findings.
Zillow ZHVI source data · ChrionML® Python workflow, modeling, evaluation and interpretation
A platform proof of concept that converts experimental workflows into governed, versioned, observable services consumable by scientists and autonomous tools.
MLOps · API contracts · Governance · Observability
Four markets complete. A reusable system is taking shape.
The objective is not simply to publish 64 forecasts. It is to build a comparable evidence base across markets—using consistent evaluation, clear local context, and a production workflow that can scale without sacrificing rigor.
4 / 64 cities published
Next phase: validate the publishing workflow across additional Northeast markets before expanding regionally.
01
Boston, MA Forecast and box score
Published
02
Providence, RI Forecast and box score
Published
03
Cambridge, MA Forecast and box score
Published
04
Ithaca, NY Forecast and box score
Published
Research partnerships
Bring a market, dataset, or decision problem.
We are building partnerships around local data access, independent model validation, sponsored city research, and applied machine-learning systems. Every engagement starts with a defined question and an evidence plan.
