Nucleo GTM brain

Nucleo develops automated CT analysis for oncology teams to quantify body composition and tumor lesions.

category

Oncology imaging AI

market profile

  • text: Oncology and radiology teams extract tumor measurements and body composition information from CT imaging, much of it manually.
  • text: Quantitative imaging tools address repeatable lesion measurements and treatment-response assessment across scans.

personas

  • title: Oncology radiologist
    pains:
    • Manual lesion sizing and segmentation take time
    • Measurements and classifications need consistency across studies
  • title: Medical oncologist
    pains:
    • Needs interpretable imaging measurements to support treatment assessment
    • Body composition and muscle loss are difficult to quantify consistently from routine scans
  • title: Hospital imaging or oncology service line leader
    pains:
    • Specialists spend time extracting quantitative imaging measures
    • Any new clinical tool must fit review, validation and integration requirements

icp

  • text: Hospitals and cancer centers with oncology and radiology teams using CT scans; company reports work with major US academic centers.
  • text: Clinical research and pharma imaging groups requiring quantitative tumor and body composition data are adjacent targets described in hiring copy.

message pillars

  • text: Automate oncology CT analysis.
  • text: Quantify muscle and fat for body composition assessment.
  • text: Measure tumor lesions consistently.
  • text: Support RECIST lesion classification.

objections

  • objection: Is the software validated and cleared for our intended clinical use?
    response: Request relevant validation studies, intended-use documentation and regulatory status for the specific jurisdiction and workflow.
  • objection: Will measurements be reliable across our scanners and patient population?
    response: Evaluate performance on a representative local dataset with expert review before deployment.
  • objection: Can it fit our imaging and security infrastructure?
    response: Confirm PACS integration, deployment architecture, privacy and IT requirements directly; the public homepage does not specify them.

competitors

  • name: Infervision
    website: https://global.infervision.com/products/infercare-recist
    why: InferCare RECIST supports CT lesion measurement, tracking and oncology response assessment.
  • name: Fraunhofer MEVIS
    website: https://www.mevis.fraunhofer.de/en/portfolio/solutions/oncochange.html
    why: OncoChange automates CT lesion tracking and measurement for follow-up.
  • name: Voiant Clinical
    website: https://www.voiantclinical.com/therapeutic-areas/oncology/
    why: Provides oncology trial imaging and semi-automated RECIST assessment.

influencers

  • name: Angelica Iacovelli
    url: https://www.ycombinator.com/companies/nucleo
    why: Co-founder and CEO with medical imaging research background.

keywords

  • oncology CT AI
  • automated tumor lesion measurement
  • RECIST lesion classification software
  • CT body composition analysis
  • sarcopenia CT segmentation
  • automated oncology imaging

voice

  • Clinical and concise
  • Outcome-oriented
  • Focused on measurable imaging workflows

signals

  • text: A cancer center is seeking to standardize RECIST tumor measurements across follow-up scans.
  • text: An oncology imaging or research group is studying sarcopenia or quantifying body composition from CT.

hiring

  • AI Engineer

pricing

model: unknown

motion

sales_led

channels

  • hospital partnerships
  • website demos
  • LinkedIn
  • YC launch

confidence

medium

Founders

  • name: Angelica Iacovelli
    title: Founder/CEO
    role: CEO
    bio: Angelica Iacovelli is the CEO and co-founder of Nucleo. Previously, she was a researcher at Stanford University, where she worked on cardiovascular modeling, simulating blood flow dynamics using GNNs, LSTMs, and Transformers. The models are now part of NVIDIA’s scientific libraries. She holds BS+MS in Mathematical Engineering from Politecnico di Milano and completed a research exchange at IIT Madras.
  • name: Luca Pegolotti
    title: Founder/CTO
    role: CTO
    bio: I am a researcher in Applied Mathematics and AI for healthcare by training. I hold degrees from Politecnico di Milano, Italy (BSc) and EPFL, Switzerland (MSc and PhD), and have conducted research at the Stanford School of Medicine during my PhD and as a Postdoc. Before founding Nucleo, I was part of Apple Health AI, where I worked on physics-informed machine learning. I've published papers on computational methods, cardiovascular system modeling, and AI for medical images and optical sensors.

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