From Text to Value: Pairing Text Analytics and Generative AI

Generative AI technologies have propelled AI to new heights this year, but challenges like hallucinations, a lack of transparency and discrepancies between enterprise vocabulary and the public terminology they’re trained on persist. Generative AI technologies can provide good general answers, but text analytics can add further precision, transparency and alignment with enterprise vocabularies. Text analytics have been instrumental in running innovative, knowledge-driven enterprises for years due to their ability to bring depth, meaning and intelligence to text. With text analytics, your business can uncover a wealth of information and provide it to generative AI for more accurate and trustworthy results. The collaboration between text analytics and generative AI is more than just a convenience—it’s a strategy that can transform how your business operates and competes. Tom Reamy, CEO of KAPS Group, and Imran Chaudhri, Principal Sales Engineer, Progress, explore how text analytics can lay the right foundation for generative AI. They explore the increasing application of LLMs—empowering non-technical end users and SMEs to use natural language to query data, thus solving complex decisions. You’ll learn: - Why text analytics are a key component of generative AI - What issues are common with enterprise generative AI - How text analytics enables more trustworthy and accurate results - How to apply generative AI and text analytics, including when to combine and when not to combine these technologies - How AI-driven decision-making is used to provide better business outcomes See how text analytics can drive enterprise AI to the next level.