What You Should Know

• Oncology AI innovator Triomics has announced a $22M Series B financing round led by Battery Ventures, pushing its total venture funding past $36 million.
• The expansion round features strategic backing from Lightspeed, Nexus Venture Partners, Y Combinator, Oncology Ventures, and Precision Health Informatics (a subsidiary of Texas Oncology).
• Triomics replaces manual medical chart curation by deploying domain-specific AI agents that ingest unstructured longitudinal records, pathology data, biomarker panels, and radiology reports.
• Peer-reviewed validation published in Nature Digital Medicine documents that Triomics slashes manual chart review times by 67%, while boosting clinical trial matches by 40% and enrollment by more than 30%.
• The platform’s multi-workflow infrastructure has captured rapid adoption across elite networks, including Memorial Sloan Kettering (MSK), MD Anderson, Yale Cancer Center, Mount Sinai, and Texas Oncology.

Beyond the Registry Bottleneck: Why Triomics Raised $22M to Automate Oncology Record Curation

The clinical and operational lifecycles of modern oncology care are suffocating under an unprecedented data paradox. Cancer care is no longer constrained by a scarcity of clinical information; instead, it is profoundly bottlenecked by an inability to synthesize and act upon the massive datasets that already exist. A single oncology patient’s longitudinal record frequently expands into hundreds of narrative-heavy clinic notes, multi-page pathology and radiology profiles, genetic biomarker sequences, legacy external records, and historical treatment regimens.

Compounding this complexity is the rapid evolution of clinical trial eligibility protocols and National Comprehensive Cancer Network (NCCN) guidelines. Because legacy electronic health records (EHRs) function as passive digital filing cabinets rather than intelligent systems of action, oncology networks are forced to rely on manual chart scraping. Highly trained research coordinators, clinicians, and medical assistants spend hours manually auditing dense files to match patients to trials or compile mandatory state registries. This structural data fragmentation results in high operational friction, widespread clinical burnout, and missed enrollment windows for life-saving therapeutics.

To turn this multi-modal text overload into explainable, workflow-integrated intelligence, oncology infrastructure pioneer Triomics has finalized a $22 million Series B financing round. Led by Battery Ventures, with participation from existing backers Nexus Venture Partners, Lightspeed, and Y Combinator, alongside strategic healthcare networks like Oncology Ventures and Precision Health Informatics (Texas Oncology), the round brings Triomics’ total capitalization to more than $36 million. The funding will be deployed to expand its AI engineering teams, accelerate health system adoption, and scale its autonomous chart abstraction architecture across global provider and life sciences networks.

Source-Backed Reasoners vs. Lightweight Summarization

Founded in 2021 by Sarim Khan and Hrituraj Singh, Triomics completely bypasses the security risks of uncalibrated consumer LLMs by building a highly specialized oncology reasoning engine. While lightweight, general-purpose summarization software often drops vital clinical parameters or hallucinates critical diagnostic links, Triomics’ AI agents read the full longitudinal record to generate structured, explainable outputs. Crucially, every single algorithmic recommendation is source-backed, mathematically traceable, and entirely verifiable inside the clinician’s native workflow.

“Oncology is the hardest place to build AI, yet the most important,” stated Hrituraj Singh, co-founder and CTO of Triomics. “Getting a model to reason reliably across thousands of pages of notes, pathology, imaging, and evolving trial criteria, and show its work, is what separates a demo from software that clinicians actually use.”

This commitment to medical integrity has driven explosive adoption across elite academic cancer networks—including Memorial Sloan Kettering Cancer Center (MSK), MD Anderson, Yale Cancer Center, and Mount Sinai Tisch Cancer Center—as well as dominant community networks like Texas Oncology.

By deploying these autonomous agents, healthcare institutions are achieving dramatic operational efficiency. Peer-reviewed validation published in Nature Digital Medicine and presented before the American Society of Clinical Oncology (ASCO) demonstrates that Triomics users curb manual chart review times by 67%, while simultaneously expanding clinical trial matches by 40% and total enrollment numbers by over 30%.

Automating the Complex Cancer Registry Pipeline

Beyond immediate bedside triage and trial matching, Triomics is aggressively positioning its underlying AI infrastructure to handle the labor-intensive burden of cancer registry abstraction and mandatory reporting obligations. Lee Schwamm, MD, Chief Digital Health Officer at Yale New Haven Health System, emphasized that traditional chart abstraction is deeply subjective, slow, and challenging to complete within mandated federal timelines. Yale’s expanded integration with Triomics aims to deliver autonomous chart abstraction of true clinical registry quality, allowing human registrars to rapidly review and finalize data to comply with state, federal, and professional society reporting mandates without missing a beat.

Brandon Gleklen, Principal at Battery Ventures—who is joining the Triomics board of directors—noted that the company has built the precise infrastructure oncology has desperately required. Gleklen highlighted Triomics’ distinct platform leverage: the exact same underlying AI infrastructure seamlessly powers clinical trial matching, pre-visit chart preparation, and registry data abstraction without requiring redundant, costly EHR integrations. This architectural advantage delivers an undeniable operational moat within a highly coveted enterprise customer base.