Mainstream media, bloggers, and YouTubers join marketers with opinions and expectations surrounding Augmented (Artificial) Intelligence (AI) especially with the breakout of energy-guzzling Large Language Models (LLMs).
Despite the hype, I have seen a few actual applications of embedding an LLM into software applications. So, the product development engineers among us (I used to be one) must ask themselves—can we turn this into a product?
Well, a company called Tecton announced last month a platform expansion that is said to unlock the full potential of Generative AI in enterprise applications. They say that they empower AI teams to build reliable, high-performing systems by infusing LLMs with comprehensive, real-time contextual data.
Their argument for the limited adoption of LLMs thus far is “the unpredictable nature of LLMs when faced with dynamic business environments. This stems from LLMs’ lack of up-to-date, domain-specific knowledge and real-time contextual awareness. The true value of AI for enterprises lies in leveraging their unique, company-specific data to create customized solutions that are deeply connected to all aspects of their business.”
That is a valid point.
Tecton enhances retrieval-augmented generation (RAG) applications by integrating comprehensive, real-time data from across the enterprise. This approach augments the retrieved candidates with up-to-date, contextual information, enabling the LLM to make more informed decisions. The outcome is hyper-personalized, context-aware AI applications capable of split-second accuracy in dynamic environments. For instance, an e-commerce AI could instantly consider a customer’s browsing behavior, inventory levels, and current promotions to retrieve the most relevant product candidates, significantly improving recommendation quality and conversion rates.
Check out the details at their website.
