Built for cancer
care's complexity
Our AI agents reason across every note, report and fax in a patient’s record and deliver structured, cited answers with expert-level accuracy directly into the workflows that run a cancer center.
One patient view, every oncology workflow.
A single cancer patient’s chart can run hundreds of pages across years. Most medical AI reads one page at a time. Triomics reads across the whole record and produces a structured, cited patient view that teams can act on, before the visit, during screening and after the appointment.
For every
oncology
Workflow.
A screened, cited worklist, ready before the clinic starts.
Every patient on the schedule is matched against every active trial, every day of the week. Coordinators stop reading charts to rule patients out. They start the day with a prioritized list of candidates, each with the evidence already cited back to pathology, molecular, and note-level details.
Providers step into the visit already informed
Every patient on the schedule has their expert-level snapshot assembled with current disease status, treatment timeline, biomarkers andalong with the pre-charting note completed right inside your workflow, leading to fewer 'pajama-time' hours.
Registry-ready abstractions. A citation behind every field.
Same platform, next workflow. Our agents produce structured abstractions across NAACCR, SEER, COC, and QOPI measures, with each field linked back to the line in the chart it came from
A screened, cited worklist, ready before the clinic starts.
Every patient on the schedule is matched against every active trial, every day of the week. Coordinators stop reading charts to rule patients out. They start the day with a prioritized list of candidates, each with the evidence already cited back to pathology, molecular, and note-level details.
Results from our ASCO 2025 abstract, co-authored with a leading academic medical center
Providers step into the visit already informed
Every patient on the schedule has their expert-level snapshot assembled with current disease status, treatment timeline, biomarkers andalong with the pre-charting note completed right inside your workflow, leading to fewer 'pajama-time' hours.
From our case study with a leading community oncology practice.
Registry-ready abstractions. A citation behind every field.
Same platform, next workflow. Our agents produce structured abstractions across NAACCR, SEER, COC, and QOPI measures, with each field linked back to the line in the chart it came from
Results from our preprint on structuring unstructured medical records.
Press coverage from our work with leading cancer centers
MSK to Deploy Triomics’ AI Platform to Improve Clinical Trial Matching and Screening
Triomics implements AI cancer clinical-trial screening to improve access in Connecticut
Mount Sinai Launches AI-Powered Clinical Trial-Matching Platform to Expand Access to Cancer Research
Evaluating AI-Enabled Trial Screening in Real-World Oncology Workflows
Built for cancer center complexity.
Oncology workflows demand more than generic AI. They require clinical depth, traceable answers, and seamless deployment. Triomics was designed around all three.
Every output carries a source citation the team can click back to. Research Coordinators, MAs and Physicians can trace every answer to the line in the record it came from. Audit trails are built in, not bolted on.
OncoLLM reasons across hundreds of pages of notes, pathology, imaging, molecular, and scanned faxes going back years. That is the only way to answer the questions oncology actually asks, such as trial eligibility, line of therapy, recurrence, or registry variables, and it is why page-by-page approaches fall short.
HL7, FHIR, CCDA, PDF, TIFF, JPEG, ingested and normalized natively. Live inside EMRs such as Epic, OncoEMR and iKnowMed. Approved on the Epic App Marketplace.
How leading cancer centers run oncology with Triomics.
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