End-to-end ML lifecycle platform with reproducible training, policy-based promotion, progressive delivery, and rollback.

Shadow-permanent 1% + SLO-gated canary ramp for Next.js on Vercel. Reusable pattern with Claude Code skill, docs, and drop-in templates.

Credit scoring (Probability of Default) with SHAP explainability via FastAPI and shadow deployment in Vertex AI. AUC>0.89 · KS + Gini reported.

Production-grade async middleware for shadow testing ML models. Features real-time traffic forking, drift detection (latency/accuracy), and automated regression suite generation.

Adversarial bot detection pipeline utilizing a hybrid spatial-temporal deep learning network (GraphSAGE + Bi-GRU). Includes LLM-powered multi-agent traffic simulation, weak labeling heuristics, active learning uncertainty sampling, and CALEB CGAN adversarial training.

Progressive rollout, shadow mode, and auto-rollback for AI agents. Sticky-percent routing with promote/rollback gates driven by real metrics. Platform engineering reliability for the agent era.

Production-grade Go runtime for OAuth proxying, MCP integration, shadow deployment, auditability, and future Hugo MCP migration.