Clavenix operationalises Deep Learning and Machine Learning Engineering for healthcare and fintech teams — from notebooks to HIPAA-grade production on GCP and AWS.
A practical 18-page field guide for engineering leaders who need to turn an ML prototype into a dependable, compliant production capability.
HIPAA Technical Safeguards, DICOM pipelines, delayed ground truth monitoring, and clinical compliance implications are not covered in standard Machine Learning Engineering playbooks. We work exclusively in healthcare and fintech.
Every Deep Learning deployment ends with a CI/CD pipeline, monitoring setup, and documentation your team can run without us. We close capability gaps — not open retainer dependencies.
Deliverable, timeline, and structure are defined before you commit. The Readiness Audit exists to make that scoping evidence-based rather than estimated.
Fixed scope. Milestone-based. Every MLOps engagement ends with infrastructure your team owns outright.
We audit your models, infrastructure, and team workflows over 3–5 days. Written report. No obligation to continue. We prioritise blockers in model versioning, cloud readiness, and compliance. You leave with a deployment roadmap your team can use regardless of who builds it.
Your Deep Learning model is ready. We build the Machine Learning Engineering infrastructure to run it reliably in production. That includes a repeatable CI/CD pipeline, drift monitoring, and HIPAA-aware inference on GCP or AWS. We document the system and hand it over with 30 days of post-deployment support.
Multiple Deep Learning models, complex data pipelines, strict compliance. Custom orchestration and full HIPAA or SOC2 architecture. We design shared infrastructure, automated retraining, and orchestration with tools such as Vertex AI or Airflow. The engagement includes team training and handover documentation so your team can operate the system.
Answer a few questions about your model, infrastructure, data, and compliance needs. The Deployment Timeline Estimator gives you an immediate planning range and explains the factors behind it.
Want more detail? Fill in the optional form after your estimate to unlock tailored scoping notes.
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Clavenix is a specialist MLOps and Machine Learning Engineering firm. The founder has deployed Deep Learning models in live clinical environments — brain tumour detection in radiology, COVID classification at clinical load. The work reflects what’s been built, not read about.
Our story →The Readiness Audit is the fastest way to understand exactly what’s blocking your MLOps deployment — and what it will take to fix it.
No commitment. We’ll confirm the right fit before you book.
Download a concise overview of our three engagement options, typical deliverables, and how a project moves from Readiness Audit to a production system your team owns.