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Multi-Agent AI — Orchestration Framework

Enterprise multi-agent orchestration framework with specialized agents, workflow engine, quality gates, and audit trails.

Role
Creator
Year
2026
Stack
Python · LangGraph · OpenAI · Anthropic · PostgreSQL · Docker

Context

Single LLM calls are insufficient for complex enterprise workflows. Multi-step processes need specialized agents with structured handoffs, validation at each gate, and human-in-the-loop approval for critical decisions.

Approach

Designed a multi-agent framework where specialized agents (analyst, developer, QA, architect) collaborate through defined workflows. Features include structured agent handoffs, automated quality gates between stages, error recovery with retry logic, and immutable audit trails for compliance.

Outcome

Production-ready orchestration system used as the architectural foundation for CourseSmith and other multi-agent projects. Demonstrates mastery of complex agent coordination patterns with enterprise-grade reliability and observability.