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DEEPEXI TECH Founder: General AI Models Struggle with Enterprise Pain Points; 'Ontology Large Model' Drives Subscription-based Transformation
DEEPEXI TECH (01384.HK), the first enterprise-level large model AI application stock and an enterprise-level token productivity platform company, saw its Founder, Executive Directo...
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DEEPEXI TECH Founder: General AI Models Struggle with Enterprise Pain Points; 'Ontology Large Model' Drives Subscription-based Transformation
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DEEPEXI TECH (01384.HK)  -5.650 (-8.679%)   , the first enterprise-level large model AI application stock and an enterprise-level token productivity platform company, saw its Founder, Executive Director, Chairman and CEO Zhao Jiehui publish an article on AI industry insights in mainland media today (14th).

He pointed out that one of the core solutions to difficulties in enterprise AI implementation lies in the "ontology large model". This technology not only compensates for the lack of proprietary business logic in general models, but also transforms previously high-cost "manually customized" AI projects into standardized products, directly driving a shift in business models toward a "subscription-based" model. This provides a clear pathway for AI enterprises to move from "concept demonstration" to “creating tangible results”.

To break through this bottleneck, DEEPEXI TECH has launched the Deepexi Ontology Large Model tailored specifically for enterprises. The model is built on the humungous dataset accumulated over the past eight years from serving nearly 400 large clients. This includes 108 "business ontologies" deeply covering key industries such as manufacturing, consumer retail, healthcare, finance and government affairs. These core operational data have never appeared in public corpora, successfully establishing a technological and data moat that pure model developers find difficult to replicate.

In terms of commercialization, the ontology large model has enabled DEEPEXI TECH to achieve a leap in engineering economics. Zhao wrote in the article that enterprise AI applications previously relied on frontline deployed engineers (FDEs) to conduct manual instantiation and customization on-site at client locations, similar to the deep engineering service model validated by US giant Palantir. Through the ontology large model, DEEPEXI TECH has successfully distilled and "modelized" these heavy tasks, radically reducing customization costs per client and becoming a productization pioneer of this pathway in the China market.
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