Artificial Intelligence Integration

Effective AI integration starts with workflow modeling, not tool selection. Architecture decisions include LLM selection, prompt engineering, and retrieval-augmented generation pipelines using vector databases and domain-specific embeddings. Enterprise system connections require well-defined APIs, structured data contracts, and access control layers. Orchestration frameworks like n8n coordinate multi-step AI processes across services. Security design governs which decisions stay human-controlled. Production systems require observability, logging, and evaluation pipelines from the start. Data quality upstream determines output quality downstream.