Introducing NLX Boost™ - Turbocharge your NLP Accuracy
NLX is announcing NLX Boost™, a Large Language Model (LLM)-powered feature that can improve traditional NLP (like Amazon Lex or Google Dialogflow) performance by up to 90%.
NLX Boost evaluates and prioritizes the semantics of a customer’s utterance to improve intent detection accuracy. By doing so it “boosts” the performance of the underlying NLP model by leveraging the patterns and commonalities between different ways customers may express the same intent.
In real-world applications, customer input can often be noisy. Utterances contain typos, abbreviations, informal and nuanced language, and so on. Unless a customer’s training data is specifically structured to pick up on the differences between the two utterances in the above example, the NLP will more often than not fail to route the request to the correct intent. These small differences in language are incredibly common and are one of the big reasons so much effort is applied to tuning training data. Unlike traditional NLPs, NLX Boost focuses on the underlying meaning to pick up on these nuances rather than matching of words/phrases with minor deviations to classify intent more accurately and effectively.
“With NLX Boost, our customers will spend much less time fine-tuning their training data without having to sacrifice performance. In fact, they’re likely to see gains. This is a particularly big deal for our enterprise customers that are operating at scale, managing 100s of intents, across many languages, as many of them do. We’re giving them a bunch of time back to focus on building and automation instead of tuning training data.” - Andrei Papancea, CEO & Chief Product Officer, NLX
NLX Boost is available starting today and it works across all channels (chat, voice, multimodal) and languages. Read more about how it works by clicking the button below.
NLX will present at the AI-powered contact center webinar with AWS on August 9th! Generally, the webinar will cover how you can leverage Generative AI to tackle 3 key contact center use cases - Self-service virtual agents, Real-time call analytics and agent assist, and Post-call analytics.
NLX's portion, presented by our one-and-only CEO Andrei, will focus on practical ways to incorporate Generative AI and Large Language Model capabilities for Enterprises on AWS.
ICYMI, Andrei joined VUX World podcast with Kane Simms to discuss the value and realistic use cases for large language models (LLMs) in enterprise automation use cases, the emerging trend of multimodal customer experiences, and thoughts on what it takes to get AI automation right.
"We don't encourage customers to rely only on metrics like containment... I can give you 100% containment by not allowing you to ever get to an agent, but that doesn't mean you're going to want to do business with that brand anymore. We're being very thoughtful about accepting the chaotic nature of the environment you (brands) operate in -- where end-users can say whatever, whenever -- and rooting the latest innovations in the conversational AI space in practicality so it's usable by enterprises."
Listen in to the complete conversation by clicking the button below.
NLX Hosts AWS Travel & Hospitality Talk at HQ2 in Arlington, VA
Last week, Andrei met up with our peers at AWS to showcase NLX's latest innovations in conversational and generative AI for the travel & hospitality industry. Special shoutout and thank you to our friends at AWS for hosting!
NLX® Conversational AI SaaS products help brands transform their customer interactions into automated, personalized self-service experiences. When implemented, NLX empowers a brand's customers to resolve their own inquiries at their own pace - with no wait time or frustration.
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