Triomics builds software that uses oncology-specific AI to read messy cancer records and automate work like clinical trial matching, chart prep, and registry reporting. The oncology AI startup has now raised $22 million in Series B funding. Battery Ventures led the round, with returning backers Nexus Venture Partners, Lightspeed, Y Combinator, and others joining in. Founded in 2021 by CEO Sarim Khan and CTO Hrituraj Singh, the company is chasing a very real bottleneck: cancer patients are living longer, which is great news, but it also means staff are stuck digging through years of physician notes, pathology reports, imaging, and even scanned faxes before they can do basic operational work. Khan put it plainly in the source interview: “We have seen medical records [with] thousands of pages of information.”
What does Triomics’ oncology AI platform actually do?
At the center of the product is OncoLLM, Triomics’ oncology-focused AI framework. It isn’t a single model. It’s a system of 8 models, ranging from 3B to 72B parameters, designed to reason at the patient level rather than just summarize one document at a time. That matters in oncology, where the signal is spread across a long timeline and buried in different record types.
The clearest example is PRISM, Triomics’ trial-enrollment software. In practice, PRISM pulls from both structured and unstructured EHR data. It checks a patient’s chart against active trial criteria and generates match summaries that coordinators and physicians can review before the visit. In one deployment at the Medical College of Wisconsin Cancer Center, the system screened 100% of upcoming visits across 5 disease teams against more than 100 recruiting trials after just a 2-hour onboarding workflow for coordinators.
That’s only one layer of the product now. Triomics started with clinical trial matching, but as large language models got better, it expanded into verifiable patient summaries for appointment prep. It also added data-curation tools that support quality reporting, cohort analysis, precision oncology, and cancer registry workflows. The company’s 2024 materials also described Harmony, a product for curation and reporting, alongside software embedded into health-system EHRs for task-specific work rather than generic chatbot-style assistance.
The before-and-after is pretty simple. Before Triomics, staff manually read charts for hours. They extract evidence by hand and repeat the same review process across every trial, visit, or reporting obligation. After Triomics, the software does the first pass in minutes and surfaces evidence-backed summaries inside the tools clinicians already use. In published results highlighted by the company, PRISM achieved more than 95% accuracy in placing the correct trial within its top 3 recommendations.
Who founded Triomics, and why does this oncology AI startup have investor backing?
The founding story
Triomics was founded in 2021 by Sarim Khan and Hrituraj Singh. The pairing makes sense on paper and, honestly, that’s rare. Khan came from chemical engineering and research experience in tissue engineering and neuroscience, while Singh had worked at Adobe Research on language models and reinforcement learning. They were also college friends, which usually helps when you’re trying to build a company in a category where the sales cycles are long and the consequences of errors are brutal.
Their original wedge was clinical trial matching. And that wasn’t random. They saw that a lot of hospital software could already work with the tidy 20% of health data stored in structured fields, but the harder 80% sat in free text and document chaos. Oncology was an extreme version of that problem. So Triomics went after the specialty first and then widened the product as LLMs became capable enough to handle more than trial screening.
Why the founders fit this category
Khan brings the biomedical lens. Singh brings the model-building depth. That’s a useful mix when your customer doesn’t want a flashy copilot — they want software that can survive review by oncologists, trial coordinators, and compliance teams.
Triomics also didn’t build in isolation. The company worked with Medical College of Wisconsin researchers on OncoLLM. It has also leaned hard into consortium-style validation around safety and benchmarking. Its leadership has pointed to COLT, a collaboration involving more than 20 NCI-designated cancer centers and Ci4CC, as part of that effort. In a field like oncology, that kind of institutional co-development matters a lot more than a polished demo.
Traction and the funding
Triomics’ enterprise customer base expanded 4x over the past year, helping push annualized recurring revenue up 10x. The customer list is getting serious. Memorial Sloan Kettering and Yale Cancer Center already use Triomics, while Y Combinator says the company is trusted by 4 of the top 10 Best Hospitals for Cancer ranked by U.S. News. Mount Sinai also rolled out PRISM systemwide in early 2026, becoming the first NCI-designated Comprehensive Cancer Center in New York City to deploy the tool for enterprise clinical trial matching.
The new money follows Triomics’ $15 million Series A in May 2024. That earlier round included Lightspeed, Nexus Venture Partners, General Catalyst, and Y Combinator. Now Battery Ventures is stepping in to lead the Series B. Investors see something bigger here than a single workflow feature.
How does Triomics compare with Abridge, Nuance, and legacy workflows?
Triomics’ closest overlap with Abridge and Microsoft’s Nuance products is chart summarization, but the products aren’t really the same thing. Abridge turns clinical conversations into documentation and billable outputs. Microsoft Dragon Copilot combines dictation, ambient listening, and workflow support across general clinical documentation. Triomics is aiming at a narrower but thornier problem: making sense of longitudinal oncology records for tasks like trial eligibility, pre-charting, quality programs, and tumor registry submission.
The real incumbent still isn’t software. It’s manual labor. Nurses, coordinators, and admin staff are still reviewing huge charts by hand because generic AI tools don’t reliably understand oncology nuance. That’s the company’s core pitch, and it’s why Khan argues cancer centers such as MSK and Yale have chosen Triomics over broader-purpose assistants. The bet is that domain specificity beats generality when the workflow is specialized, highly regulated, and expensive to get wrong.
Why this oncology AI startup’s $22M round matters
The obvious read is that Triomics now has the capital to keep broadening from trial matching into a fuller oncology operations stack. That’s where the company has been heading for a while — first matching, then patient summaries, then registry and quality workflows. If that works, Triomics stops being a point tool and starts becoming infrastructure for cancer centers.
That matters for customers because oncology admin work doesn’t sit neatly in one place. A patient’s case can stretch over years, bounce across sites of care, and generate a chart that’s too dense for generic summarizers to handle well. A tool that can shrink appointment prep time and automate mandatory reporting buys back something rare in cancer care: staff attention. That’s valuable even before you get to trial enrollment.
There’s also a harsher reason this round matters. Healthcare AI is crowded now. Ambient scribes are everywhere. EHR vendors are shipping their own copilots. So for a startup to raise a Series B here, it usually needs more than a cool model — it needs evidence, workflow fit, and customers that will stick. Triomics understands that. Its emphasis on oncology-specific training, published validation work, and deployment inside real cancer centers suggests a company trying to build defensibility the boring way.
How big is the market for oncology AI software?
The most relevant adjacent market here is oncology information systems. That market was worth about $2.94 billion in 2024 and is projected to reach roughly $4.69 billion by 2030, with an 8.1% CAGR from 2025 through 2030. North America accounted for 39.7% of the market in 2024, which helps explain why startups like Triomics are targeting U.S. cancer centers first.
The timing also makes sense at the workflow level. Fewer than 10% of adult oncology patients enroll in clinical trials, and one reason is painfully simple: matching is still labor-intensive, fragmented, and easy to miss in day-to-day care. When records include free-text notes, pathology, imaging, genomic reports, and faxed documents, software that can actually reason across all of it has a much bigger opening than another generic AI note tool.
The broader healthcare AI market is sending a mixed signal. On one hand, ambient scribes became a $600 million category in 2025 after 2.4x year-over-year growth. On the other, Menlo Ventures says switching costs are low, pricing pressure is rising, and customers increasingly expect scribes to expand beyond documentation into more durable workflows. That’s relevant for Triomics because it suggests vertical, workflow-deep products may have a better shot at lasting value than standalone summarization tools.
Conclusion
Triomics looks like the kind of oncology AI startup investors want right now: focused, evidence-heavy, and pointed at work that hospitals already pay people to do manually.
But the next phase is harder than the last one. It’s one thing to prove an oncology model can read a chart. It’s another to become the default workflow layer across trial matching, pre-charting, and registry operations at major cancer centers. The company just raised $22 million to make that case.
Read how Tiea Connectors raised ₹77 Cr in Series A funding to build high-performance electrical connectors and interconnect systems for EV, aerospace, defence, and avionics manufacturers in India.
FAQ
– What funding did Triomics raise in 2026?
Triomics raised a $22 million Series B round announced on May 27, 2026. Battery Ventures led the financing, and returning investors included Nexus Venture Partners, Lightspeed, and Y Combinator.
– How does Triomics work for cancer centers?
Triomics uses an oncology-specific AI framework called OncoLLM to process both structured and unstructured patient records. It then powers workflow tools such as PRISM for clinical trial matching. Instead of only summarizing a note, it evaluates longitudinal charts, checks eligibility against trial criteria, and produces evidence-backed summaries for coordinators and physicians inside existing clinical workflows.
– Who founded Triomics?
Triomics was founded in 2021 by Sarim Khan and Hrituraj Singh. Khan’s background spans chemical engineering plus tissue engineering and neuroscience research, while Singh previously worked at Adobe Research on language models and reinforcement learning before becoming Triomics’ CTO.
– Is Triomics an ambient scribe company or an oncology software company?
It’s closer to an oncology software company than a pure ambient scribe vendor. Abridge and Microsoft Dragon Copilot mainly focus on turning clinician-patient conversations into documentation, while Triomics is built around oncology-specific chart review, trial enrollment, pre-charting, quality workflows, and registry reporting inside a market adjacent to oncology information systems.
