Medical AI you can actually ship.
We build AI/ML into your diagnostic and medical-device software, and build it to be certifiable. Signal and imaging models, clinical validation, and DICOM/HL7 integration, engineered for IEC 62304 and SaMD from the first commit. You own the model and the weights.
Where clinical software meets
shippable AI.
healthcare systems
systems shipped
software lifecycle
stays with you
AI built into medical software,
not bolted on.
Every model ships with clinical validation, human-in-the-loop controls, and the lifecycle documentation a regulated product needs.
Biosignal AI (ECG, Holter, EEG)
Arrhythmia and event detection on 12-lead and single-lead ECG, Holter and patch data. Denoising, beat classification, and false-alarm reduction.
Medical Imaging & DICOM AI
Automated measurements, view and lesion classification, and segmentation across echo, CT, MRI and pathology, on native DICOM pipelines.
Clinical NLP & Ambient Documentation
Speech-to-structured-notes, coding, and summarization tuned to medical vocabulary and multilingual input, so clinicians document less and care more.
Predictive & Clinical Risk Models
Deterioration, readmission and triage scoring from EHR and device data, with the explainability clinicians need to act on a prediction.
On-Device & Edge Inference
Models that run on the device or at the bedside for latency, privacy and offline reliability, not only in the cloud.
MLOps for Regulated Systems
Versioning, drift monitoring, audit trails and re-validation workflows that keep a deployed model compliant long after launch.
From idea to audit-ready, in five steps.
A model that cannot pass IEC 62304 review is a dead end. We build the evidence trail as we build the model, never after.
Feasibility & Data Audit
We assess your clinical goal, your data quality and volume, the target claim, and the regulatory market, then tell you honestly what is buildable before you spend on a full engagement.
Data Pipeline & Annotation
De-identified data pipelines, clinician-in-the-loop annotation, and rigorous patient-level train, validation and test splits that prevent the leakage which inflates lab metrics.
Model Development & Clinical Validation
Architecture selection, training, and evaluation against held-out patients with sensitivity, specificity and subgroup analysis, not a single headline accuracy number.
Integration
We wire the model into your product through DICOM, HL7/FHIR or your device SDK, with the human-in-the-loop controls and fail-safes clinical use demands.
Deploy, Monitor & Document
Edge or cloud deployment, drift monitoring, and the IEC 62304 lifecycle and ISO 14971 risk documentation your regulatory submission needs.
Most AI shops can't ship into a regulated device. We can.
Research labs can't ship it, and generic dev shops can't certify it. We do both, which is the entire reason a medical-AI feature makes it to market.
Built to IEC 62304, not retrofitted
Regulatory readiness is a property of how the software is built, so we build for it from the first commit rather than reverse-engineering documentation at the end.
Clinical validation, not vibes
A demo that works on cherry-picked cases is worthless in a clinic. We validate the way reviewers and clinicians expect, on data that reflects real patients.
Your data and IP stay yours
Patient data and the model you fund are among your most valuable and most sensitive assets. They never become leverage against you.
We integrate with your stack
You should not have to rebuild a product that already works to add one AI feature. We fit into what you ship today.
Medical AI, answered.
The questions medical-device and diagnostic-software teams ask us first.
Do you work on cardiac AI (Holter, ECG, echo)?
Yes. Cardiac diagnostics is our lead focus. We build arrhythmia and AFib detection, false-alarm reduction, and automated echocardiography measurements. See our dedicated page at levitation.in/ai-cardiac-diagnostics.
Can you build AI that will pass FDA, CE or CDSCO review?
We build to the IEC 62304 software lifecycle and ISO 14971 risk management, and we produce the validation evidence and documentation a submission needs. Clearance is granted by the regulator, but we engineer so it is achievable rather than a dead end.
We already have software. Can you add AI without a rebuild?
Yes. We integrate through DICOM, HL7/FHIR or your device SDK and embed the model into your existing product, with the human-in-the-loop controls clinical use demands.
Who owns the model and the data?
You do. We use de-identified data, offer on-premise and VPC-isolated deployment, and you own the trained model and its weights outright.
What data do we need to get started?
It depends on the problem. In the feasibility assessment we review the data you have, its quality and volume, and whether public datasets can bootstrap development, then give you an honest read on what is buildable.
How do we start?
Book a free 30-minute feasibility assessment. We scope your clinical goal, your data and your regulatory market, and outline a path to a validated, shippable model.
Have a diagnostic idea that needs AI?
Let's pressure-test it, free.
Book a 30-minute feasibility assessment. We'll review your data, your target claim, and your regulatory market, and tell you honestly what's buildable.