Simply put, our remarkable platform transforms both unstructured text and structured data into meaningful, actionable insights.

It all begins with a deep understanding of contextual relationships within clinical narratives. Even the smallest nuance can mean the difference between a flood of false positives and a clean, actionable dataset.

In healthcare, the challenge is compounded: medical conditions and diagnostic tests are expressed in many ways, and in a fragmented care delivery system, crucial signals often appear across notes from multiple providers.

Our models use multiple layers of representation and inference to connect those dots — extracting context, resolving ambiguity, and surfacing clinical meaning. This enables us to tackle real-world challenges like risk adjustment, fraud waste and abuse (FWA), denials management, de-identification, and more.

When other models fail, ours succeed — surfacing insights that lead to better patient outcomes and significant financial impact.