VertexLyn uses AI and computer vision to assist dermatology workflows — analyzing skin images, helping identify dermatological conditions, and tracking treatment progress across visits — on a secure, AWS-native backend built for the way medical records actually need to work.
The numbers behind VertexLyn's AI skin-analysis engine, measured against our current model evaluation.
Across the dermatological conditions currently supported by the model.
From image upload to a structured, reviewable result.
Recognised by the current classification model.
Most dermatology practices still document conditions by eye and by hand — scattered photos, verbal comparisons, and notes that don't travel cleanly from one visit to the next.
Patient photos end up on phones, laptops, and email threads instead of the chart — so comparing this visit to the last one means digging through a camera roll.
Every extra minute spent typing notes or sorting images is a minute not spent with the patient — and across a full clinic day, that adds up fast.
Without a consistent measurement, judging whether a treatment is working after six weeks comes down to memory and gut feel — not numbers.
VertexLyn is an AI technology platform starting with dermatology — applying computer vision and structured skin-image analysis to a workflow that has historically depended on visual judgement and scattered documentation.
Founded in July 2026, VertexLyn is early-stage by design: a small, hands-on engineering team building the core AI and cloud infrastructure first, and validating it directly with pilot dermatology clinics.
VertexLyn is building an AI-powered computer vision workflow that turns a skin image into structured clinical insight — five steps, one consistent pipeline every time.
Capture standardized skin images.
AI analyzes the image using computer vision.
The system assists in identifying dermatological conditions.
Compare patient images over time.
Generate structured insights for clinical workflows.
Each image a clinician captures moves through this pipeline: a computer-vision model analyzes the photo, classifies the likely condition, estimates severity, and compares it against the patient's prior visits — turning a single photo into a structured, trackable clinical record.
One workflow — from photo to report — running on AWS from the moment an image is captured.
Clinicians capture the patient's skin directly in the browser. Every image is encrypted in transit and lands in Amazon S3 under per-patient access controls enforced by AWS IAM.
A computer-vision model hosted on Amazon SageMaker classifies the condition, scores severity, and marks the affected region — typically in under 8 seconds.
Results, notes, and patient metadata are written to Amazon RDS, so every visit compares cleanly against the ones that came before it.
One click produces a PDF with the AI findings, annotated images, a progress score, and clinical notes — ready to file or send along with a referral.
VertexLyn is built for teams who need precision and a record they can defend — not another generic practice-management tool with a dermatology label on it.
Multi-provider practices that want every clinician documenting conditions the same way, no matter who's on shift that day.
Solo practitioners who want clinical-grade documentation without buying — or learning — a full hospital-scale system.
Treatment-focused practices that need honest before/after evidence for patient outcomes, not just a flattering photo.
Remote-first services that need consistent pre-screening and structured intake before a clinician ever opens the case.
The VertexLyn workflow, step by step — screenshots will replace these placeholders as the product moves toward general availability.
Standardized in-browser capture of the affected skin area.
Computer-vision analysis runs on the uploaded image.
The model classifies the likely dermatological condition.
A visual severity read-out attached to the result.
Visit-over-visit comparison of a tracked condition.
Structured findings exported into a clinical report.
VertexLyn is built and operated by a small, hands-on engineering team.
Leading VertexLyn's product vision and overall direction, focused on building practical technology products that combine software engineering with emerging AI capabilities.
Responsible for infrastructure, deployment and DevOps engineering, focused on building reliable and scalable cloud infrastructure for the platform.
Works on software development at VertexLyn, focused on building and refining the product's core application features.
VertexLyn is an early-stage technology company building AI-powered solutions for dermatology and intelligent skin-image analysis.
VertexLyn is building intelligent computer vision technology to help transform how dermatology images are analyzed, documented and tracked. We're bringing on a small number of pilot clinics to help shape the product early.
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