Domain-specific data models
GenAI is quickly changing the way technology impacts business, but general-purpose data model will quickly disappoint.
VOR’s heavy industry supply chain data model provides superior context-driven AI capabilities – increasing generative accuracy and reducing the hallucinations that generalised models are prone to throwing out.
Accuracy in GenAI
The language of heavy industry supply chains is highly nuanced – with terms and phrases that only apply in these applications. The tasks often involved numerous actions that may span across the globe.
Streamba’s data model was specifically built around the processes our customers use daily, giving the VOR platform an unparalleled ability to work alongside your experts.
Cost efficiency
Processing overhead increases exponentially with the size of the underlying LLM. This is driving the switch of enterprise AI solutions away from generic models, as shown in a recent study by Gartner, suggesting more than 50% of GenAI models used by enterprise will be domain-specific by 2027.
Compared to general-purpose models, domain-specific models, trained for a specific purpose, offer substantially increased computationally efficiency & superior response times.
Fit for (your) purpose
VOR’s data model is not only specifically designed for heavy industry supply chain, but it is also optimally efficient.
Collating disparate information from a wide variety of data sources (such as data lakes, unstructured & blog data, documents and communications), VOR hosts knowledge from across the supply chain in a central unified view.