About
We built Neurmorph because we watched radiologists spend their expertise on measurement, not medicine.
Founded in Santa Clara in 2021. One product. Chest CT annotation. We do it well.
Why we built this.
Andrei Volkov spent three years building computer vision infrastructure at a medical device company. During that time he worked closely with radiologists — people who spent a decade training to interpret disease patterns — and watched them spend roughly 30% of each read session on tasks that required no diagnostic judgment: opening prior studies, placing calipers, measuring in two planes because the software made three-plane measurement cumbersome, filling in structured report fields from scratch for findings they'd already described verbally.
The existing AI tooling wasn't the answer. Single-disease alert models that generated pop-ups and triage notifications added cognitive interruption without removing mechanical work. Complex platform integrations required months of IT engagement and custom model training before anything reached the radiologist.
Neurmorph is the direct answer to a specific question: what if the measurements were already there when you opened the scan? DICOM in. Annotated DICOM SR out. Under one second. Nothing else changes.
Three people, one problem.
Computer vision and medical imaging background. Spent three years leading imaging AI infrastructure at a medical device company before founding Neurmorph in 2021. Focused on the annotation workflow problem specifically — not diagnosis, not triage, not population screening.
Radiomics and DICOM protocol specialist. PhD in biomedical engineering. Built PACS integration frameworks for 4 years before Neurmorph.
Board-certified radiologist with subspecialty in thoracic imaging. Joined Neurmorph to close the gap between what engineers build and what radiologists actually do. Responsible for clinical validation methodology, annotation accuracy benchmarking, and Fleischner Society guideline adherence in the model's classification output.
Angel-funded. Intentionally focused.
We raised $100K in angel funding in early 2026 to accelerate PACS integration work and expand our chest CT training dataset. We're not trying to boil the ocean — we're trying to get one thing right: the radiologist opens the scan and the finding is already marked.
Work with us or talk to us.
We're onboarding imaging centers one at a time. We move carefully because accuracy matters more than scale right now.