Account propensity scoring service with domain features, deterministic scoring, segments, and ranked feature explanations.

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GET /events protected when API_KEY is set

See DEMO.md for terminal demo steps, curl commands, and sample request/response files.

Example:

Set API_KEY to require X-API-Key on scoring/event endpoints. Set APP_DB_PATH to control the SQLite event database location.

With the server running, use a second terminal for the smoke check:

Docker:

Kubernetes manifests live in k8s/deployment.yaml and include probes, resource limits, a Service, and a PVC for the SQLite event store. The default manifest uses one replica because SQLite is the default event store.

Dockerfile, Docker Compose, and Kubernetes configuration are validated by static inspection/YAML parsing in this workspace. Runtime container and cluster validation remains a CI or cloud-environment step.

Purpose: account propensity scoring with ranked feature explanations.

Quickstart: run tests/eval, start uvicorn api.server:app --reload --port 8000, then run python scripts/smoke_test.py.

Demo path: use DEMO.md for curl examples and sample request/response files.

Deployment status: local tests and smoke tests pass; Docker/Compose/Kubernetes config is present; Docker image builds are validated in CI; cloud deployment is pending.

Remaining gaps: real CRM feeds, model monitoring, retraining workflow, managed auth/secrets, cloud deployment, and production data governance.

Portfolio index: https://github.com/Adityansh-Chand/ai-engineering-portfolio

CRM-style feature schema.

Propensity score and low/medium/high segment.

Ranked explanation contributions.

Evaluation over labeled sample accounts.

SQLite event audit trail for score results.

GitHub Actions CI for tests, eval, and container build.

Production data contract in datasets/production_schema.json.

MIT