Our mission
Many consequential questions sit awkwardly between a web search and a full consulting engagement. A business owner may need to compare markets, a hiring team may need to understand a labor pool, or a household may need to compare the cost of living across cities. The underlying data often exists, but it is scattered across agencies, table formats, release calendars, and geographic definitions.
Milou’s purpose is to shorten the distance between the question and a defensible analysis. That means making the evidence traceable, stating the time period and geography clearly, and separating what the data shows from what must still be judged by a person.
What Milou is designed to do
Translate the question
Turn a plain-language decision into measurable concepts, suitable geographies, comparison groups, and time windows.
Work from sources
Use identifiable datasets and retain provenance so a reader can return to the publisher and inspect the source.
Explain the tradeoffs
Present results in decision-ready language while surfacing uncertainty, missing variables, and alternative interpretations.
What Milou is not
Milou is not a substitute for professional legal, medical, tax, investment, engineering, or safety advice. Public data can be delayed, revised, estimated, or too broad for a particular site or person. A statistical relationship does not by itself establish causation, and a ranked list is only as useful as its inputs and weighting choices.
We believe a useful analysis should make those constraints visible. Our methodology describes how sources, freshness, geography, calculations, and limitations are handled. The Austin sample analysis shows the intended level of specificity, including where a scoring model can mislead.
The public-data ecosystem
Depending on the question, relevant primary sources can include the U.S. Census Bureau’s American Community Survey, the Bureau of Labor Statistics’ Quarterly Census of Employment and Wages, and the Bureau of Economic Analysis’ Regional Price Parities. Milou is not affiliated with or endorsed by these agencies. Links are provided so readers can understand and inspect representative source material.
Who builds Milou
Milou is built by Reza Seyed, its founder. The work behind it is data engineering as much as product: ingesting and reconciling federal, state, and local statistical releases — Census, BLS, BEA, FHWA, FEMA, NOAA, CDC, NCES and others — into a catalogue an analysis can actually compute over, then building the agent that does the computing and reports what it did.
That background is why this site spends as much space on limitations as on capabilities. Most errors in public-data analysis are not arithmetic mistakes; they are vintage mismatches, boundary changes, small denominators, and estimates quoted without their margins of error. Questions about method are welcome — contact us.
Contact
Milou is an evolving product, and clear feedback is valuable. For product, methodology, privacy, or accessibility questions, contact us. If you want to walk through a use case, you can also book a product demo.