00Fifteen production-oriented AI systems with interactive execution harnesses, architecture specifications, API contracts, implementation guides, evaluation metrics, security controls, and deployment patterns.
RAGLLMOpsInferenceAgentsVoice AIAI Security
01Applied AI · NLP
DefectOps
An end-to-end AI defect-management workflow—from intelligent triage and ownership mapping to root-cause analysis and suggested code fixes.
PythonRAGLLMsVector Search
02An AI-powered microstructure characterization platform that segments ferrite, pearlite, martensite, and inclusions; measures grain size and phase fractions; detects cracks, pores, and defects; and generates automated metallographic inspection reports.
PyTorchOpenCVU-NetFastAPIMLflow
03Engineering · Automation
Storage Validation Automation
Python automation for storage-controller configuration, firmware upgrades, and repeatable system validation in complex server environments.
PythonPytestLinuxCI/CD
04A seven-day multimodal agentic-AI platform implementing vision-language ingestion, hybrid GraphRAG, episodic memory, MCP-native tool execution, multi-agent orchestration, constrained decoding, and end-to-end LLM observability.
VLMGraphRAGMCPLangGraphvLLMOpenTelemetry
05LLMOps · Evaluation Engineering
EvalMesh
A continuous LLM-evaluation control plane implementing dataset versioning, prompt regression, RAGAS metrics, trajectory grading, calibrated LLM-as-judge ensembles, adversarial red teaming, drift detection, and release-gated model promotion.
RAGASDeepEvalPromptfooLangfuseMLflowOpenTelemetry
06Streaming ML · Anomaly Intelligence
PulseGuard
A low-latency anomaly-intelligence pipeline combining Kafka event ingestion, online feature computation, temporal transformers, isolation forests, Bayesian change-point detection, SHAP attribution, concept-drift monitoring, and automated incident correlation.
KafkaFlinkPyTorchRiverFeastSHAP
07Edge AI · Privacy-Preserving ML
FederatedVision
A federated computer-vision training substrate with differential privacy, secure aggregation, non-IID client sampling, LoRA parameter-efficient fine-tuning, quantization-aware training, ONNX graph optimization, and hardware-adaptive edge inference.
FlowerOpacusLoRAONNXTensorRTKubernetes