AI Research
Semantic Consensus: Process-Aware Conflict Detection and Resolution for Enterprise Multi-Agent LLM Systems
A new middleware framework eliminates agent coordination failures to achieve 100% enterprise workflow success.
Multi-agent large language model (LLM) systems are rapidly emerging as the dominant architecture for enterprise AI automation, yet production deployments exhibit failure rates between 41% and 86.7%, with nearly 79% of failures originating from specification and coordination issue...
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ArXiv CS.AI
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ArXiv CS.AI
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Generated insight by OnAirToday AI
Enterprise AI failure is increasingly a coordination problem rather than a lack of raw model intelligence. This framework provides a critical middleware layer to synchronize agent intent, effectively moving multi-agent systems from experimental prototypes to reliable production infrastructure.
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