Open source software for machine learning production monitoring : maintain control over production models, detect bias, explain your results.

Production operations framework for AI-powered SaaS. The architectural patterns, failure modes, and operational playbooks that determine whether your AI systems scale profitably or fail expensively.

🚀 Build AI Agent Teams as Production-Ready APIs. Orchestrate CrewAI agents with FastAPI for enterprise-grade AI services. Leverage Groq's lightning-fast LLMs to deploy collaborative AI workflows at scale.

Production-grade architecture patterns, decision frameworks, and best practices for building reliable AI agents. Framework-agnostic reference for engineers.

Production-ready agentic AI framework. High-performance, lightweight, simple. Built-in safety, memory, and 4 reasoning patterns. Ships to production fast.

Next-gen enterprise multi-agent AI framework for autonomous agent swarms with code-level control, military-grade efficiency, and hybrid intelligence.

40x faster AI inference: ONNX to TensorRT optimization with FP16/INT8 quantization, multi-GPU support, and deployment

Real-world patterns for shipping AI agents to production. Learn versioning, cost optimization, multi-tenancy, guardrails, and observability through runnable TypeScript examples.

Production-Ready AI Systems • Enterprise Architecture • Azure & Beyond

Production-grade AgentOps control plane for safe AI agent execution. Dual-plane architecture: Rust governance engine + Python LLM runtime + Next.js dashboard. Deny-by-default policies, budget enforcement, approval gates & audit logging.

Central hub for Enterprise AI Architecture: 55+ production-ready repos, consulting toolkits, Azure solutions & Three-Layer AI Framework

Production-ready enterprise AI framework with three-layer architecture: UX Automation → Data Intelligence → Strategic Intelligence

Production-ready Agentic AI Data Pipeline built with LangGraph for cleaning and segmentation. Bridging the gap between RAG and Deterministic AI Architecture for Enterprise Data Engineering.

Universal autonomous agent framework with ReAct loop, multi-provider LLM routing, reasoning graph, and MCP integration, domain-agnostic for building specialized AI agents.

A local-first C# reference for intent routing with deterministic guardrails and constrained LLM usage.

Spec-driven, markdown-only control plane for AI-assisted coding with explicit agent boundaries and human approval gates.

An educational example showing how to build a guardrailed, tool-augmented AI assistant in C# (.NET 10) using Ollama, with deterministic validation, tool constraints, timeouts, and safe fallbacks.

Enterprise AI Agent Orchestration for Java/Spring Boot. Sequential, parallel & conversational flows with Apache Camel integration.

ModelSpec is an open, declarative specification for describing how AI models especially LLMs are deployed, served, and operated in production. It captures execution, serving, and orchestration intent to enable validation, reasoning, and automation across modern AI infrastructure.

Professional AI consultancy toolkit with case studies, templates, and reference implementations