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.
“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]
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]
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.
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.
The global food supply is on the brink of crisis. Facing challenges like an aging workforce, labor shortages, declining crop yields, and climate change amongst others, farming is in dire need of a lifeline. AI and AgTech are emerging as the saviors of agriculture, transforming everything from crop breeding to farm-to-table traceability. These revolutionary technologies promise to enhance sustainability, improve yields, and reduce environmental impact. With the urgency for innovation greater than ever, AI is the essential lifeline the agricultural industry needs to secure a resilient and efficient future.