"Many customers say, 'I don't really have an AI problem, I have a data problem.' They need to prepare their data. Files here, images there, videos elsewhere - they have these legacy platforms that don't support unified access. The challenge becomes quite complex because most enterprise data is unstructured: contracts, invoices, videos, presentations, and it's scattered across different systems. The real value comes from bridging unstructured and structured data."
"The challenge becomes quite complex because most enterprise data is unstructured: contracts, invoices, videos, presentations, and it's scattered across different systems. The real value comes from bridging unstructured and structured data. This used to require armies of people manually reviewing documents. Now AI can watch videos, read contracts, analyze images, and categorize everything intelligently. That's the fundamental shift, turning the vast amount of unstructured content enterprises have into actionable, information that can be queried."
Organizations increasingly identify a data problem rather than an AI problem, requiring data preparation and unification across scattered files, images, and videos. Legacy platforms often lack unified access, leaving enterprise information siloed. Most enterprise data is unstructured—contracts, invoices, videos, presentations—and value depends on bridging unstructured and structured data. Manual review of documents used to require large teams. Modern AI can watch videos, read contracts, analyze images, and intelligently categorize content. AI-driven classification converts vast unstructured repositories into actionable, queryable information that enables downstream analytics and decision-making.
Read at Computerworld
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