
OncoLLM
TM
AI Agents Built for Oncology, Ready for Production
Built for Oncology
OncoLLM is Triomics' enterprise-grade AI platform purpose-built for oncology. Rather than being a single monolithic model, OncoLLM is a framework—a system of interoperable AI components engineered to integrate into clinical environments, automate data abstraction, and enable real-world decision-making at scale.

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Patient Level and Not Document Level Reasoning
OncoLLM is a constellation of 8 models (from 3B parameters to 72B parameters) that function in an agentic manner to interpret information at patient level and not document level. This is vastly superior to prior approaches such as named entity recognition or relation extraction at sentence or document level. It analyzes information at patient level just like oncology data specialists instead of acting like a keyword highlighter.

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Purpose Built Agentic Architecture with SOTA Foundations
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Ability to Ingest all types of EHR data
Triomics has built the most sophisticated and advanced EHR data ingestion pipeline which can ingest HL7, FHIR, XMLs, CCDAs, PDFs, TIFF, JPEG or any other EHR data format and convert this into standardized stream of information. This is extremely important for the downstream input into the AI pipeline. This system, called OncoIndexer, makes the raw EHR data LLM ready.

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Trained Like ODSs, Acts like ODSs
Triomics has also finetuned LLMs to act like agents which can search for information in EHR records in multiple steps. This goes beyond off the shelf RAG techniques which fall short of solving complex queries. The system acts very much like human abstractors by searching for information, navigating through EHR records, curating and aggregating information and finally normalizing that information to standard terminologies like ICDO3.

In an era of rapidly evolving frontier models, the real innovation lies in how well you align and operationalize them. OncoLLM is not a model - it’s a solution.
Modular Framework for OncoLLM







Patient Level and Not Document Level Reasoning
OncoLLM is a constellation of 8 models (from 3B parameters to 72B parameters) that function in an agentic manner to interpret information at patient level and not document level. This is vastly superior to prior approaches such as named entity recognition or relation extraction at sentence or document level. It analyzes information at patient level just like oncology data specialists instead of acting like a keyword highlighter.
Patient Level and Not Document Level Reasoning
OncoLLM is a constellation of 8 models (from 3B parameters to 72B parameters) that function in an agentic manner to interpret information at patient level and not document level. This is vastly superior to prior approaches such as named entity recognition or relation extraction at sentence or document level. It analyzes information at patient level just like oncology data specialists instead of acting like a keyword highlighter.











Patient Level and Not Document Level Reasoning
OncoLLM is a constellation of 8 models (from 3B parameters to 72B parameters) that function in an agentic manner to interpret information at patient level and not document level. This is vastly superior to prior approaches such as named entity recognition or relation extraction at sentence or document level. It analyzes information at patient level just like oncology data specialists instead of acting like a keyword highlighter.



Ability to Ingest all types of EHR data
Triomics has built one of the most sophisticated and advanced EHR data ingestion pipeline which can ingest HL7, FHIR, XMLs, CCDAs, PDFs, TIFF, JPEG or any other EHR data format and convert this into standardized stream of information. This is extremely important for the downstream input into the AI pipeline. This system, called OncoIndexer, makes the raw EHR data LLM ready.