Skip to main content
The Model Governance API provides controls for responsible AI deployment: approval workflows before production promotion, automated drift detection, and fairness parity checks across customer segments.

GET /api/v1/model-governance

Retrieve governance status for a model including approval history and drift check results.

Query Parameters

Response


POST /api/v1/model-governance

Perform governance actions. Editor or Admin (review requires Admin).

Actions

request_approval — Request approval to promote a model version

Response (201):

review — Approve or reject a model promotion (Admin only)

Response:

drift_check — Run a drift detection check

Compares baseline vs. current score distributions using three methods:
  • PSI (Population Stability Index): measures shift between score distributions (< 0.1 OK, 0.1–0.25 monitor, > 0.25 retrain)
  • KS (Kolmogorov-Smirnov): max CDF difference between distributions
  • AUC decay: drop in AUC from baseline
Each check is persisted to the model drift-check history.
Response (200):

parity_check — Check fairness across customer segments

Compares mean scores across segments and flags those deviating more than maxDeviation from the overall mean.
Response (200):

POST /api/v1/models//drift

Feature-distribution drift check. Unlike the drift_check action above (which compares score distributions), this endpoint compares two feature-value snapshots keyed by feature name and returns PSI + KS per feature plus an overall severity verdict. The model id is used only for audit-log attribution — the trained model itself is not read.
This route lives at /api/v1/models/[id]/drift (the models prefix, not algorithm-models), parallel to the model registry surface. It is tenant-scoped, open to any authenticated caller, and rate-limited to 30 requests per minute per tenant.

Path Parameters

Request Body

Response

Error codes

Roles

any authenticated

POST /api/v1/models/import

Bring-your-own-model import. Accepts a multipart/form-data upload of an ONNX model, persists it as an AlgorithmModel with modelType: "onnx_imported", hashes the bytes (sha256), and stores them inline in modelState (or offloads to a configured blob store above the inline threshold).
Only ONNX is supported in V1. Single-file models only; multi-file bundles are rejected. File size cap: 100 MB. Admin role required.

Form fields

Response

Response: 201 Created

Error codes

Roles

admin