Triomics

Triomics develops AI software for cancer care workflows. Its platform applies AI agents, including a model the company calls OncoLLM, to reason across the entirety of a patient's oncology record — clinical notes, pathology, imaging, molecular reports and scanned faxes spanning years — and to return structured answers with citations linked back to the specific line in the record.

The product covers three principal workflows. Patient trial matching screens every patient on a clinic's schedule against every active trial and produces a prioritized, evidence-cited candidate worklist for research coordinators. Visit preparation and pre-charting assembles a patient snapshot covering disease status, treatment timeline and biomarkers, and drafts a pre-charting note in the physician's preferred format inside the EMR. Cancer registry curation generates structured abstractions aligned to NAACCR, SEER, CoC and QOPI measures, with each field traceable to its chart source. Audit trails and source citation are described as built into every output rather than added on.

Business model

Triomics sells a software platform to cancer centers and oncology practices, deployed inside existing clinical systems and covering multiple oncology workflows on a single platform.

Traction

The company reports reading roughly 120,000 charts per month and screening more than 65,000 patients for trials monthly, along with more than ten NCI-designated customers. Reported outcome figures include a 70% reduction in chart review time, a 30% lift in trial accruals and 40% more matches generated (from an ASCO 2025 abstract co-authored with an academic medical center), 80% and 45% reductions in pre-charting time for new and follow-up visits respectively (community oncology practice case study), and 96% abstraction accuracy with 75% faster case abstraction and 60% faster case finding (preprint on structuring unstructured medical records).

Latest developments

Company posts describe Memorial Sloan Kettering deploying the Triomics platform for clinical trial matching and screening (October 2025), an implementation of AI cancer clinical-trial screening to improve access in Connecticut (November 2025), Mount Sinai launching an AI-powered clinical trial-matching platform (January 2026), and work evaluating AI-enabled trial screening in real-world oncology workflows (February 2026).