Using NLP to Analyze Documents

At Xyonix, we use state of the art natural language processing to automatically read your documents and distill valuable insights across your corpora.

Modern applications generate troves of documents; if mined effectively, these documents can provide valuable insights. In order to effectively mine text, we must teach machines to read these vast collections and understand the content. State of the art NLP technologies allow us to leverage hard fought machine knowledge gained from public texts available on the Internet. NLP capabilities can help in multiple areas like understanding conversations, analyzing sentiment, or automatic content creation.

testimonials

“Deep is an expert in NLP and machine learning. His team gave us regular progress updates, milestones, and deliverables, and showed a high level of professionalism. I’m very happy with our partnership.”

Dr. Dennis Tenen, Professor at Columbia University [more]

Think there’s value in your corpus that could be automatically extracted? Reach out to us, maybe we can help.

our capabilities are showcased by some of our recent NLP projects:

AI Driven Video Summarizer

For an extremely rapidly growing startup, we built an AI system that transforms lengthy, often instructional videos into concise, optimized segments. The system cleanses transcripts, then leverages LLM models we fine tuned using training data meticulously annotated by a combination of other LLMs and our human team at Xyonix. It's adept at extracting key topics, generating summaries, easing navigation, and producing short, impactful videos in various formats. Already in public use and benefiting millions daily, this system is a game-changer for educational and instructional content, making complex information more accessible and engaging.

Video Content Creator

In collaboration with a rapidly growing startup, we've crafted an AI-driven solution for helping users rapidly create high-quality video content by automatically analyzing user generated movie scripts and identifying optimal video assets for inclusion in short videos. Our role extended beyond data science; we engineered and now host a fully scaled system. This platform excels in generating scene text and keywords, leveraging semantic search within a bespoke imagery index, and creating video metadata from video frames. Designed to facilitate the production of engaging videos and scripts for social media and advertising, this service is robust, fully managed, and caters to millions of users daily.

Vaccine Hesitant Persona Mapper

We were asked by Columbia University to help build a map of vaccine hesitancy to assist public health officials in increasing vaccination rates. We built a corpus of millions of social media messages from platforms like Twitter, Reddit and Youtube comments. We are now analyzing this data by manually annotating thousands of training examples using a multi-parent taxonomy and iteratively (active learning driven) training a multi-label machine learning and NLP powered parser. If we are successful, we hope to save lives by convincing the vaccine hesitant to protect themselves and their communities. [Read more]

Virtual Patient Intake Specialist for Online Health Services, A Case Study

Virtual Intake Specialist

We helped a company build a powerful virtual intake specialist that automatically communicates with patients to route them to the best care for their condition. Our AI system listens to patients and asks them just the right follow up questions, much like a traditional intake nurse might, to help schedule the best care option. [Read more]

AI Med Spa Assistant

Xyonix teamed up with an early-stage startup to launch an AI iPhone app based assistant to help Med Spa nurse practitioners. The AI technology adeptly categorized facial features, aiding in the assessment of treatments and spotting issues like temporal visual changes, ineffective product batches or injector performance. Integrated with iOS for precise patient driven photo alignment, the system enabled consistent treatment tracking. We played a pivotal role in technology development and strategic product planning; our involvement was key in fusing medical accuracy with technological innovation in product development. [Read more]

AI Backed Surgery

For a fortune 500 company, our Xyonix built models are in production today constantly analyzing thousands of recent in body surgery videos and reviews across many hundreds or thousands of surgery rooms around the world. Our models watch never ending streams of surgery videos, and read countless reviews. Our models power dashboards that help surgeons improve. [Read more]

Medical Treatment Author

We worked closely with a company to empower consumers with readily accessible quality health information by building systems that read large volumes of unstructured medical texts using deep NLP relation parsing techniques, and automatically authored millions of web pages. Our work resulted in site traffic growth of 10,000% averaging 6% week over week growth. The site attracted primarily physicians, physician specialists, and other researchers due in large part to the quality of the automatically generated text.

Fan Response Parser

We built a system that helped our client help popular artists like Metallica and Beyonce communicate with their massive fan base by automatically interpreting millions of fan text messages sent to artist’s personal phones. Our parser was capable of accurately recognizing over 70 detailed conversation statements.

Sales Lead Conversation Bot

We worked closely with executives and data scientists of a major automated sales lead generation system to define an AI path forward that enabled their system to not only understand conversations, but to also generate responses for human consumption. 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.

Depression Text Analyzer

We built a system that helps artists like Metallica and Beyonce interpret the results of millions of fan text messages. During our analysis, we found that many fans were expressing depression related thoughts. We honed our AI models to more accurately differentiate between those discussing sad things and those more at risk of self harm. The results help get these fans professional help.

want to learn more? check out Some of Our Recent NLP Related Articles

When Is the Right Time for Your Business to Invest in Custom AI Solutions?

80% of AI projects fail—not because the technology isn’t ready, but because businesses aren’t. Companies that thrive with AI begin by identifying clear, high-impact problems it can solve, backed by quality data and a strategic vision for success. This article explores the critical elements of AI readiness: defining your business challenges, ensuring your data infrastructure is robust, and leveraging AI to gain a competitive edge. Whether it’s automating repetitive tasks, personalizing customer experiences, or predicting trends, the key to success isn’t adopting AI early—it’s adopting it smartly. Learn how to assess your readiness and prepare for an AI-powered future.

Why a Virtual Concierge is the Key to Superior Customer Service

Explore how AI-powered virtual concierges are transforming customer service in industries like hospitality and education. With 80% of customers likely to switch brands after two bad experiences, businesses are turning to AI to meet rising expectations. This article delves into real-world examples of AI concierges offering personalized recommendations, streamlining tasks like bookings and check-ins, and supporting students with career guidance—all while allowing human teams to focus on more complex customer needs.

From RAG to Riches: A Practical Guide to Building Semantic Search Using Embeddings and the OpenSearch Vector Database

In this article, we delve into the evolution of search technologies, tracing the journey from the conventional keyword-based search methods to the cutting-edge advancements in semantic search. We discuss how semantic search leverages sentence embeddings to comprehend and align with the context and intentions behind user queries, thereby elevating the accuracy and relevance of search outcomes. Through the integration of vector databases such as OpenSearch, we illustrate the development of sophisticated semantic search systems designed to navigate the complexities of modern data sets. This approach not only delivers a more refined search experience but also enhances the precision of results by accurately interpreting the intent of user inquiries, representing a notable leap forward in the progression of search technology.

AI Gone Wrong? The Critical Role of Chatbot Testing and Certification

AI chatbots are transforming customer service by providing 24/7 availability and interactions that resemble human conversation. It's anticipated that by 2025, 80% of customer support will utilize Generative AI to improve the customer experience and increase agent efficiency. However, the swift adoption of this promising technology has faced obstacles, particularly miscommunications that have risked brand reputations. To prevent inaccuracies it's essential to adopt thorough AI testing and certification processes. In this article, learn more about why rigorous testing and certification are critical for the successful integration of AI chatbots in customer service.

Measuring Accuracy and Trustworthiness in Large Language Models for Summarization & Other Text Generation Tasks

Large Language Models (LLMs) are increasingly popular due to their ability to complete a wide range of tasks. However, assessing their output quality remains a challenge, especially for complex tasks where there is no standard metric. Fine-tuning LLMs on large datasets for specific tasks may be a potential solution to improve their efficacy and accuracy. In this article, we explore the potential ways to assess LLM output quality:

Why NLP is a Game-Changer for the Insurance Industry: Implementation Benefits and Best Practices

The insurance industry is moving towards a more tech-driven future with the help of natural language processing (NLP). Artificial intelligence could improve productivity and save up to 40% on insurance costs by 2030, according to a 2021 McKinsey report. In this article we address how you can utilize NLP to automate customer service, streamline underwriting, and analyze social media data:

Practical Applications of AI and NLP for Automated Text Generation

In this article, we explore some practical uses of AI driven automated text generation. We demonstrate how technologies like GPT-3 can be used to better your business applications by automatically generating training data which can be used to bootstrap your machine learning models. We also illustrate some example uses of language transformations like transforming english into legalese or spoken text into written.

Modern AI Text Generation: An Exploration of GPT-3, Wu Dao 2.0 & other NLP Advances

Within this last year alone, there has been a paradigm shift in model development as research groups are ingesting (nearly) the entire world's worth of information on the internet to train massive deep learning models capable of performing fantastic or frightening feats, depending on your perspective. In this article, we explore an AI compositional technology, known as generative modeling, and demonstrate its ability to simulate human-realistic text.

Understanding Conversations in Depth through Synergistic Human/Machine Interaction

Every day, billions of people communicate via email, chat, text, social media, and more. Understanding the conversation begins with understanding one document. Once we can teach a machine to understand everything in a single document, we can project this understanding up to a collection, thread or larger corpus of documents to understand the broader conversation.