Build Agentic AI solutions on AWS, using latest OSS Agentic Frameworks.

⚡Ship RAG Solutions Quickly and effortlessly

Курс "Разработка AI/LLM-приложений на Python: от идеи до релиза" предоставляет слушателям возможность пройти через полный цикл создания LLM-приложений, от идеи до релиза. В рамках курса вы познакомитесь с передовыми технологиями и инструментами, такими как Mistral AI API, LangChain, Arize Phoenix, FastAPI, PostgreSQL и Docker и т.д

OTel Plugin for Hermes Agent

Sage is a virtual Mythic agent that that uses an AI agentic system to operate Mythic and Mythic agents running on compromised hosts.

A production framework for DSPy implementing the Teacher-Student pattern. Distill the reasoning of expensive models (Teacher) into optimized prompts for cheap, fast models (Student) to reduce inference costs by up to 50x.

Root cause analysis for AI agents. Detects agent loops, retry storms, and optimization opportunities in LangSmith, Langfuse, Arize Phoenix, and OpenTelemetry traces.

a small space adventure showcasing the capabilities of retrieval augmented generation (RAG)

Modern Wisdom AI RAG Pipeline

A Gemini agent that reviews legal cases safely — real CourtListener case law only, no advice, safety-scored in Arize Phoenix.

🤖 Intelligent, secure, and multilingual chatbot backend for Lorenzo Maiuri's website. Built with FastAPI, Gemini LLM, LlamaIndex, and MongoDB. Features session memory, tool-calling, and robust security

A production-style multi-agent system that generates context-aware briefs. Built on MCP + A2A, with persistent memory (Chroma), dynamic tool routing, self-critique, distributed tracing (Arize Phoenix), an LLM-as-judge eval harness, and Redis caching.

Self-improving SRE agent for ML model observability with Gemini, Phoenix tracing, and MCP

Operational Engine for Managing and Auditing Private AI Agents with OpenClaw and Arize Phoenix.

TracePilot: Gemini CLI fork with Phoenix/OpenInference tracing, MCP self-introspection, safety gates, redaction, evals, and a verified broken-repo repair loop

An emergency call triage system that classifies and routes 911 calls using real-time speech recognition and natural language processing.

Production-style RAG pipeline with multi-strategy retrieval (sparse, dense, hybrid RRF), LangGraph orchestration, and full OpenTelemetry/Phoenix tracing over a 4M-review Amazon Electronics dataset (Cell Phone and Accessories)

Four deployable reference scenarios to govern GitHub Copilot and custom AI agents like any other enterprise actor: identity, audit, per-team cost, safety, quality evals, and per-PR agent-vs-human attribution. Azure AI Foundry, APIM AI Gateway, App Insights, OpenTelemetry

Orquestrador de agentes RAG corretivo (CRAG) para resolução de problemas de TI com rastreamento LangGraph, FastAPI, ChromaDB e OpenTelemetry/Phoenix.

Graph Observability Kit (graphobs) is a Python library for contract-first observability in graph-based applications. It helps teams describe graph state boundaries once, then reuse those declarations for trace payloads, structured logs, and validation.