Clean & Normalize Your Data Using AI

At Xyonix, we train custom AI systems to recognize and correct errors in your data.

Your data might be wrong. Much of organizational data is entered by human hands, and humans often make mistakes like typos and spelling variations. Data errors often propagate downstream which can lead to operational errors costing a business time and money. Machines can be trained to recognize where there might be errors in data entry, and can help to correct the data. Machines can also be used to prevent incorrect data from being entered in the first place, by, for example, suggesting likely values and prompting humans to make a simpler, less free form decision. Off the shelf solutions can be cumbersome to configure, and often don't take advantage of the structures unique to your data. In addition, privacy, security and other constraints may prevent you from allowing your data into commingled cloud environments.

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Sherri Engvall

“Xyonix’s most impressive characteristic is their passion for helping us solve our problems. They truly believe in what we’re trying to achieve — they’re excited about it. Their members see the value of our work and understand our vision.”

Sherri Engvall, IT Manager @ Delta Dental of Washington [more]

Check out some of our recent projects to get a taste of our capabilities
AI Driven Video Summarizer

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

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.

NLP for Public Health: Vaccine Hesitant Persona Mapper, A Case Study

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.

Interested in learning more? Check out one of our articles on applications of ai in the real world
Securing the Conversational Frontier: Advanced Red Team Testing Techniques for Chatbots
Securing the Conversational Frontier: Advanced Red Team Testing Techniques for Chatbots

Chatbots, now omnipresent, face a crisis of accuracy and security highlighted by recent public blunders at Air Canada and Chevrolet, where bots made unintended promises. Air Canada's attempt to deflect blame onto its bot was rejected by authorities, underscoring a harsh reality: companies are indeed responsible for their bots' actions. Despite the prowess of language models like ChatGPT, their inherent nature to occasionally fabricate with confidence poses unique challenges. Drawing lessons from cybersecurity, this article explores four advanced red team testing strategies aimed at reining in bot misstatements and significantly bolstering chatbot security.

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