Understanding Conversations Using NLP and AI
At Xyonix, we use state of the art text analysis and NLP technologies to automatically understand conversations and converse with humans.
Users are increasingly accustomed to immediate responses on mediums like SMS, Facebook chat, and Twitter. Perhaps as a result, conversational interfaces like chatbots are becoming increasingly popular for applications like customer support, product recommendations, targeted promotions, product feedback aggregation and more.
“I don’t think a five out of five really encapsulates the work that they do. The work is top-notch. It’s what we ask for and more. They go the extra mile in terms of letting us know that whatever we need, they’re there for us to lend their expertise, to be in a meeting if they need to, to explain the project in more detail. So it’s really going above and beyond.”
Dominique Grinnell, Sr. Product Team Manager at Delta Dental of Washington [more]
What almost all conversational interfaces have in common are problems with machine reading comprehension. Leveraging our team's more than 60 years of combined deep NLP experience, we've helped a number of companies improve their conversational understanding capabilities.
In one case, we were able to efficiently extend one conversational domain from the recognition of just a handful of response categories, to over 50, all with very high accuracy. In another case, we were able to leverage modern LSTM deep learning neural nets (i.e. AI) to outperform more traditional SVM style learning techniques. In another case, we were able to, in just a few short days, improve net effectiveness of algorithms by a significant percentage through the use of deeper semantic grammar based model features to the thrill of the client's team. In all cases, off the shelf alternatives were entirely insufficient as these models are typically trained on very different data and have no means for heavily customizing conversations.

Smart Hospitality Concierge
Xyonix recently developed a cutting-edge virtual concierge system for deployment across thousands of hotels worldwide. This AI-driven system features a sophisticated knowledgebase for hotel-specific inquiries and an LLM-based dialog system for dynamic guest interaction. The system also includes advanced features to avoid bot hallucinations and maintain creative control over responses, offering broad guidance in general queries while relying on a curated knowledgebase for specific information. Additionally, it intelligently classifies guest questions, seamlessly directing complex issues to human staff. [Read more]
Virtual College Advisor
We worked closely with a company that helps colleges and universities better advise their student populations in a variety of areas including career choices, adjusting to college life, finding motivation and more. We built a virtual concierge like application that transcends traditional question/answering engaging in highly sophisticated and helpful conversation. We worked closely with the company CEO and product teams to think through a variety of advanced applications, build demonstrable prototypes, and facilitate easy deployment into production. [Read more]
Virtual Educational Coach
We helped a company developing a virtual AI tool for improving student progression understand how to facilitate interactions between students, parents, and teachers to optimize teaching outcomes. We proposed a system with the ability to analyze factors affecting student outcomes and use that information to instruct teachers and parents on how to best observe and assist their students.ns, and teacher actions. It could then use this knowledge to instruct teachers and parents on how to observe student progress and provide them with specific feedback on observational ability, engagement, and teaching plan quality.
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