Data-driven organizations use AI and ML, either natively within applications
or infused into applications, to obtain better insights into the content that drives their business and automate content-centric processes for greater efficiency. But the proliferation of AI projects, ML models, APIs, and data sets to enable these processes present serious challenges that stand in the way of successful AI and ML deployments.
An Enterprise AI platform solves these challenges by unifying AI models, model orchestration, data processing, storage, workflow, integration, and monitoring under a single platform approach. This type of platform helps organizations build applications that drive enterprise-wide data insights and intelligent process automation to digitally transform the enterprise.
With the ten must-have capabilities of an Enterprise AI platform outlined in this paper from Veritone, organizations can position themselves for rapid adoption of AI and ML at scale without requiring custom “from-scratch” model development, extensive AI expertise, or single-model dependency.
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