AI Workflows & Agentic Architecture Directory

Building an autonomous code reviewer with Claude 3.5 involves integrating the Anthropic API with GitHub Actions to analyze pull request diffs for logic errors, security gaps, and architectural consistency. Teams deployin...

A financial RAG synthesizer is an agentic AI system that uses LangGraph and Llama 3.1 to automate complex financial analysis by retrieving SEC filings, market data, and news sentiment in a stateful graph. Financial firms...

Monitoring brand reputation with LangChain and RSS involves building an autonomous AI agent that scans news feeds, analyzes the sentiment of mentions using models like GPT-4o, and triggers alerts for potential PR crises....

Building an automated prospecting agent involves using n8n to orchestrate a pipeline between Apollo.io for lead discovery and Claude 3.5 Sonnet for real-time qualification. Companies using this autonomous system report r...

RAG-Powered Legal Citations is a multi-agent AI architecture that uses Gemini 1.5 Pro and Pinecone to verify the accuracy of legal briefs. By retrieving the full text of cited cases from a vector database and analyzing t...

Automating an e-commerce catalog with Vision AI involves using a multimodal model like GPT-4o to analyze product photos and automatically generate SEO-friendly titles, descriptions, and tags. By integrating this with Mak...

Deep research for supply chains uses LangGraph and Claude 3.5 Sonnet to build autonomous agents that monitor logistics risks, demand trends, and supplier reliability. By using stateful cyclical logic and the Model Contex...

Agentic Security Ops is a framework that uses autonomous AI agents—typically powered by GPT-4o or Gemini 1.5 Pro—within orchestration platforms like n8n to investigate security alerts and execute remediation steps. By mo...

An internal HR oracle built with n8n and Pinecone uses agentic RAG to automate policy inquiries, resulting in a 60% reduction in onboarding time and resolving 94% of routine questions in 2026.

An autonomous support swarm uses n8n and LangChain to coordinate multiple specialized AI agents that resolve customer queries without human triage. By assigning tasks to specialist agents for technical, billing, and acti...

Microsoft's Eric Horvitz and EPFL's Robert West warn that AI is advancing faster than our ability to understand it. Three trends are making AI more opaque: AI judges scoring other models, multi-agent AI societies, and LL...

Microsoft MAI-Thinking-1 is a 35B active parameter sparse MoE reasoning model (approximately 1T total parameters) that matches Claude Opus 4.6 on SWE-Bench Pro at 52.8% and achieves 97% on AIME 2025. It was trained from...