This article introduces BriX, a platform that transforms AI prototypes into enterprise-grade production tools without requiring deep DevOps expertise.
- •"Deployment slop" describes three failure modes when AI prototypes hit enterprises: version chaos across teams, reliability breakdowns under concurrent load, and accidental data leaks from hardcoded credentials
- •BriX offers model agnosticism, letting users switch between Claude, GPT, and Gemini with a dropdown—no code changes required
- •Model Context Protocols (MCPs) provide secure, pre-built connectors to enterprise data sources with built-in access controls and automatic audit logging
- •Centralized system prompts and context files lock consistent AI behavior across all users, eliminating version drift
- •BriX's architecture uses six layers: a streaming frontend, FastAPI gateway, LangGraph orchestration, hot/cold memory storage, on-behalf-of identity propagation, and full-context data processing
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