Multi-Agent Verification Framework Prevents AI Confabulation in Production

LLM confabulation—where models generate plausible but false information with complete certainty—erodes user trust and breaks integrations in production systems. This multi-agent research pipeline leverages OpenClaw and FastMCP to automatically detect and prevent hallucinated outputs through consensus voting and real-environment validation. The approach provides a practical, scalable solution for embedding AI safety mechanisms into production applications.