For years, we’ve built tools that help people see what’s easy to overlook, notice what matters, and understand their work with greater clarity.
No matter the role or industry, we’ve seen the same pattern: the most meaningful patterns are hard to explain, but easy to recognize. Users often tell us, “when I see it, I know.”
We’re now bringing these proven approaches into healthcare to help organizations spot issues sooner, understand what matters, and make better decisions with confidence.
A structure everyone can see is a change everyone can discuss.
AI models that turn large, hard-to-manage datasets into information teams can use every day—built with healthcare workflows in mind.
Models that learn how your organization actually works — from its own records, not a template.
AI that brings the right details forward and presents them in a way that fits naturally into how you work.
Our DgPg research—a compact transformer model that learns the ordering of diagnostic codes in medical records and visualizes the patterns around any given code—was published as “Visualizing Medical Coding Practices Using Transformer Models” (ICPRAM 2025). The model is openly available on Hugging Face. See the announcement and more of what we're building in our LinkedIn post.
You can also explore WhyHC, our open research platform — a coordinated map of U.S. care pathways built from public national datasets. Explore it directly, or connect your AI assistant to it via MCP and just ask.
Led by researchers and engineers from the University of Tennessee.
CEO
Professor, University of Tennessee. Expertise in big data, visualization, AI, and scalable systems.
Head of Algorithms
Research Assistant Professor in Computer Science. Expertise in AI, transformers, visualization, and cloud computing.
Head of Infrastructure
20 years of full-stack experience. Expertise in big data, and scalable infrastructure.
We partner with teams who need clearer, faster ways to see what’s happening in their data— and act on it.
One email is enough. Share a bit about your team and what you’re exploring—we’ll take it from there.