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Beyond RAG: How Articul8’s supply chain models achieve 92% accuracy where general AI fails
Articul8's specialized models tackle complex industrial sequences where timing and order matter, challenging the one-size-fits-all approach to enterprise AI.
In the race to implement AI across business operations, many enterprises are discovering that general-purpose models often struggle with specialized industrial tasks that require deep domain knowledge and sequential reasoning. Unlike existing frameworks like LangChain or LlamaIndex that provide predefined workflows, ModelMesh combines Bayesian systems with specialized language models to dynamically determine whether outputs are correct, what actions to take next and how to maintain consistency across complex industrial processes. “While these models are impressive in open-ended tasks, we quickly discovered their limitations when applied to our highly specialized semiconductor environment,” Srinivas Lingam, corporate vice president and general manager of the network, edge and AI Group at Intel, told VentureBeat.
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