Skill UI

Comprehensive skill covering the full lifecycle of visual AI systems. Expertise includes object detection (YOLO, Faster R-CNN), instance and semantic segmentation (SAM, Mask R-CNN), and video analysis. The workflow guides users through dataset preparation, selecting optimal architectures, training using frameworks like PyTorch, and achieving production readiness via model optimization (ONNX, TensorRT) and deployment on various edge or cloud targets.

Geniml builds machine learning workflows around BED and scATAC datasets to learn embeddings for regions, metadata, and cells, enabling similarity searches, clustering, consensus peaks, and downstream analysis of genomic intervals.

Uses the Shodan and InternetDB APIs in Python to enrich IP addresses, detail open ports/services, pull CVEs, and compute reputation scores to support threat triage and SOC workflows.

Phoenix Evals lets teams build evaluators for AI/LLM apps by wiring deterministic code with LLM nuance, running Python or TypeScript workloads, validating against humans, and iterating through error analysis, RAG, and production workflows.