Overview
STRATA estimates the most likely race/ethnicity of individuals from name and US address using a published char-LSTM + geography model refined by gradient-boosted soft-voting, deployed as a SageMaker real-time endpoint or Batch Transform in your own AWS account - your input records never leave your account and the vendor never sees your data. Each record returns calibrated probabilities for five classes (White, Black, Hispanic, Asian, Other), the argmax label, and a per-record uncertainty index (IU). Resolved geography is withheld; output carries privacy-preserving anonymous cohort tokens (cohort_tract, cohort_zcta) that let you group results by geography without exposing census identifiers. A waterfall selects the best-supported geographic tier per record (block-group+tract, tract, ZCTA, or name-only) and reports the geographic lookup level used (lookup_level, with lookup-quality codes). Method reproduces a published methodology that improves on BISG/BIFSG with lower false-positive bias. Licensed for aggregate, population-level analysis only (e.g. HMDA/ECOA/CRA fair-lending monitoring, housing-equity and disparity research) - NOT for decisions about identified or identifiable individuals. See the EULA for permitted-use and prohibited-use terms.
Highlights
- Name + US address -> calibrated 5-class race/ethnicity probabilities (White/Black/Hispanic/Asian/Other) plus a per-record uncertainty index (IU).
- Runs entirely in your AWS account (real-time endpoint or Batch Transform); input PII never egresses. Resolved geography is withheld - output carries privacy-preserving anonymous cohort tokens.
- Licensed for aggregate, population-level analysis ONLY (fair lending/HMDA/ECOA/CRA, housing equity, disparity research) - not for individual decisions. See EULA.
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Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.xlarge instance type, real-time mode | $13.58 |
ml.m5.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $13.58 |
ml.m5.2xlarge Inference (Real-Time) | Model inference on the ml.m5.2xlarge instance type, real-time mode | $24.33 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $24.33 |
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Software charges are metered per instance-hour through AWS Marketplace. Contact terry@aequum.ai within thirty (30) days of an invoice for a billing adjustment for a verified duplicate charge, metering error, or material inability to use the product caused by a confirmed defect; approved adjustments are issued through AWS Marketplace. AWS infrastructure charges are governed solely by AWS.
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Version release notes
Initial release of STRATA (M8-BGT). National US name+address race/ethnicity probabilities (5-class) with per-record uncertainty (IU), waterfall tier selection, and privacy-preserving anonymous cohort tokens. Real-time endpoint or Batch Transform.
Additional details
Inputs
- Summary
CSV with a header row; one individual per row. Columns: fname,mname,lname,address,city,state,zip5. fname and lname are required; mname optional. The name drives the character-LSTM; the US address adds geographic signal via an offline resolver. Any extra columns (e.g. a record id) pass through unchanged. US scope.
- Input MIME type
- text/csv
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