SPi Global suite of AI-driven solutions promise to unlock new opportunities for content businessesBack to list
Manila, Philippines, May 22, 2019 - In a recently published whitepaper, SPi Global, the biggest content technology solutions company in the world and industry-leading provider of content-driven solutions, discusses how AI technology can help maximize the value of information assets for businesses in highly specialized domains.
Titled, “Transform Content to Actionable Data and Unlock New Business Opportunities with AI”, the whitepaper highlights that strategic adoption of AI-built tools ultimately results to faster speed- to-market, cost reduction, and value creation for data-rich companies in the scientific, technical and medical publishing; risk and financials; and data services. The whitepaper discusses how AI-led tools have become indispensable as more businesses rely on valuable content to drive positive experience for customers. With AI, content-driven companies can streamline predominantly manual processes, such as content analysis, enrichment and classification.
SPi Global Chief Technology Officer Jishnu Gupta says that content businesses are just beginning to uncover possibilities through AI. “At SPi Global, we see AI as an augmentation for our deep subject matter expertise. With AI, professionals can accomplish more than they ever could before and improve the timeliness and quality of their content data,” he shares.
In the whitepaper, SPi Global fully establishes that emerging and new-age technologies can provide companies with the ability to disseminate massive volumes of content, eliminate bottlenecks, and make informed and timely decisions to achieve untapped scale previously impossible prior to the AI boom. Showcasing SPi Global’s suite of revolutionary proprietary tools developed using machine learning (ML), natural language processing (NLP), and deep-learning methodologies, it underscores that with the right AI-built tools, companies can increasingly reduce the need for human manipulation in transformation processes of structured and unstructured data, thus improving accuracy, productivity, and revenue.