AI Layer

The AI Layer hosts model services for analytics and decisioning:

  • Model Registry: Central repository for storing and versioning trained artifacts (e.g., PyTorch, TensorFlow, ONNX) with associated metadata (training data, hyperparameters, performance metrics).

  • Inference Services: Containerized microservices exposing REST/gRPC endpoints for real‑time scoring, batched inference, and streaming analytics. Auto‑scaling based on request load.

  • Fine‑Tuning Framework: Supports transfer learning and reinforcement learning pipelines. Integrates with hyperparameter optimization tools (e.g., Optuna) and GPU orchestration (e.g., Kubernetes, AWS SageMaker).

  • Monitoring & A/B Testing: Observability via Prometheus and Grafana dashboards, enabling latency tracking, throughput metrics, and performance comparison of model variants.

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