enterprise-ai-patterns
Production-grade AI architecture patterns for enterprise - security, governance, scalability, and operational excellence
浏览 frankxai 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。
已收录技能
165收录技能的仓库 Stars 合计
192仓库 Forks
36平均每个技能的仓库 Stars
1同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。
Production-grade AI architecture patterns for enterprise - security, governance, scalability, and operational excellence
Design and deploy AI workloads across AWS, Azure, GCP, and OCI with intelligent routing, cost optimization, and cross-cloud patterns
Build production-grade agentic workflows with LangGraph using graph-based orchestration, state machines, human-in-the-loop, and advanced control flow
Create professional architecture diagrams using D2, Draw.io, Mermaid, and OCI official icons for enterprise-grade visualizations
Patterns for multi-agent coordination, task decomposition, handoffs, and workflow orchestration. Best practices for building and managing agent systems.
Infrastructure as Code for AI workloads using Terraform across AWS, Azure, GCP, and OCI
Current best practices for Model Context Protocol server design, implementation, and integration. Updated patterns for 2025 MCP ecosystem including multi-server orchestration, security, and performance.
Deploy and operate AI workloads on Kubernetes with GPU scheduling, model serving, and MLOps patterns
Cost optimization for AI workloads - model selection, GPU sizing, commitment strategies, and multi-cloud cost management
Build autonomous AI agents using Claude Agent SDK with computer use, tool calling, MCP integration, and production best practices
Expert in Retrieval-Augmented Generation systems - knowledge bases, chunking strategies, embedding optimization, and production RAG architectures
Train and fine-tune LLMs using HuggingFace TRL, Transformers, and cloud GPU infrastructure with SFT, DPO, GRPO methods
Build AI applications on Azure using Azure OpenAI, Cognitive Services, and ML services with enterprise patterns
Patterns for multi-agent coordination, task decomposition, handoffs, and workflow orchestration. Best practices for building and managing agent systems.
Create professional architecture diagrams using D2, Draw.io, Mermaid, and OCI official icons for enterprise-grade visualizations
NVIDIA NIM inference microservices for deploying AI models with OpenAI-compatible APIs, self-hosted or cloud
Build AI applications on AWS using Bedrock, SageMaker, and AI/ML services with best practices for enterprise deployment
Enterprise AI security - OWASP LLM Top 10, prompt injection defense, guardrails, PII protection
Design and deploy AI workloads across AWS, Azure, GCP, and OCI with intelligent routing, cost optimization, and cross-cloud patterns
Production-grade AI architecture patterns for enterprise - security, governance, scalability, and operational excellence
Expert in OCI Generative AI Dedicated AI Clusters - deployment, fine-tuning, optimization, and production operations
Generate professional OCI architecture diagrams with verified Oracle styling and icons
Expert guidance on Oracle Cloud Infrastructure services, cloud architecture patterns, cost optimization, deployment strategies, and OCI best practices for enterprise solutions
Design framework-agnostic AI agents using Oracle's Open Agent Specification for portable, interoperable agentic systems with JSON/YAML definitions
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。