A Fundamentally Different Approach
As artificial intelligence continues to transform industries, healthcare presents both tremendous opportunity and significant complexity. Existing language-based AI systems like LLMs are remarkable at generating natural-sounding text, but they often fail to meet the transparency, accuracy, and compliance demands of medical applications. MST has expanded on a vectorized KG approach and utilizes transformer attention mechanisms, dot product and cosine and other modern techniques similar to the strategies LLMs use for determining similarity, which are applied to various size contextual windows and across multiple clinical documents.
Our proprietary technology offers a fundamentally different approach. While it shares some mathematical foundations with LLMs, it diverges in its core structure by explicitly modeling relationships and contextual dependencies within the data. This design enables a clearer representation of how information is connected, enhancing traceability and interpretability. More importantly, it preserves the integrity of source data, making it an ideal solution in highly regulated domains where accuracy is not just desired but legally required.
Our technology represents a major step forward in healthcare AI—offering the precision, auditability, and compliance that traditional language models simply cannot guarantee.
By grounding AI outputs in structured relationships and preserving original data fidelity, MST has built a platform not only capable of advanced reasoning but also worthy of trust in life-critical applications.
As regulatory pressure mounts and the need for explainable AI grows, MST’s technology offers a clear path forward—where innovation and compliance are not at odds, but integrated by design.