Australia · Healthtech & financial services MLOps

Operationalise AI with clarity and control.

Clavenix helps Australian teams take ML beyond the pilot: deploy on AWS or GCP, make model changes traceable and prepare the technical evidence that clinical and financial stakeholders need.

Fixed-scope starting pointMilestone-based deliveryGCP + AWS
Team planning a cloud deployment and operational handover
From pilot to operationCloud delivery, monitored performance and a documented handover.
Digital healthClinical-use evidence support
Financial servicesModel oversight and change control
Cloud engineeringAWS and GCP architecture
Clear ownershipRunbooks and handover
Services for Australian teams

A production path shaped around your use case.

Whether you are deploying clinical decision support or a financial model, we start with intended use, data movement and operating ownership. Regulatory classification and legal obligations remain with your organisation and advisers.

01 / DiscoverRecommended first step

MLOps Readiness Audit

Find the architectural, data and workflow gaps between a working model and a dependable service before starting a build.

  • Model, data-flow and infrastructure review
  • Australian privacy and cross-border questions for your team
  • TGA evidence considerations if the product is a regulated device
  • Prioritised roadmap, scope and acceptance criteria
Best forHealthtech or financial teams planning a first production release.
02 / BuildCore deployment

Cloud model deployment

Turn the model into a managed, reproducible service in your approved cloud environment, with controls that fit your data and operating model.

  • Containerised inference and CI/CD pipeline
  • Access, encryption, secrets and audit logs
  • Data-location choices based on contract and privacy needs
  • Staging, rollback tests and operating runbook
Best forProducts moving from an experiment to customer or clinical use.
03 / ScaleMulti-model project

Governed model portfolio

Set consistent release and monitoring patterns across multiple models while retaining model-specific validation and change evidence.

  • Shared model registry and versioning
  • Review and approval checkpoints
  • Subgroup and drift monitoring design
  • Evidence pack and team handover
Best forTeams with several live or near-live ML use cases.
04 / OperateOngoing retainer

Monitoring & maintenance

Establish the feedback loops to spot performance degradation and manage changes after launch, with named owners and escalation paths.

  • Availability and data-quality alerts
  • Drift, performance and subgroup review
  • Incident response and rollback playbooks
  • Documented improvements and change history
Best forTeams that need stable operations and ongoing model review.
How we work

Practical milestones. A system your team can run.

The aim is not only a live endpoint. It is a dependable service with clear data boundaries, measurable behaviour and a workable support model.

01 / Align

Understand the setting

Agree intended use, hosting and privacy constraints, stakeholder evidence needs and measurable delivery outcomes.

02 / Deliver

Build in your environment

Implement the deployment and controls in reviewable stages, keeping design decisions and test results visible.

03 / Transfer

Make operation routine

Test release and rollback, define monitoring and escalation, then hand over runbooks to your team.

Free resources

Useful reading for the next deployment decision.

Get a maturity guide for your team and a brochure explaining how we engage.

Cover of The 5 Stages of ML Deployment Maturity ebook
Free ebook · PDF

The 5 Stages of ML Deployment Maturity

Identify the next operational capability your team needs. Complete the form to unlock the guide.

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Free brochure · PDF

Download our Service Brochure

Compare the audit, deployment, multi-model and monitoring options. This is a general service brochure, not Australian regulatory guidance.

Download brochure
Free interactive tools

Pressure-test the plan before a project starts.

Both tools are linked here. The HIPAA checker is for U.S. healthcare information; it does not assess Australian Privacy Act, TGA or APRA requirements.

Deployment Timeline Estimator

Answer questions about your model, data and delivery setup for an indicative timeline and a view of likely blockers.

Estimate your timeline
U.S. operations only

HIPAA Compliance Gap Checker

For Australian teams also serving U.S. healthcare customers, review U.S.-focused technical safeguards. It is not a local compliance assessment.

Open the U.S. HIPAA tool

Australian guidance in context

Clavenix supports technical implementation and evidence preparation, not legal advice, TGA approval or APRA assurance. Applicability depends on the product, entity and data flows.

After launch

Ongoing Monitoring & Maintenance Retainer

Keep deployed models observable and supported after handover. We watch for data and model drift, respond to incidents, and handle minor pipeline updates while your team retains ownership of the system. Available from Year 2.

Drift alertsIncident responsePipeline upkeep
Discuss ongoing support
Abstract visualisation of connected machine learning infrastructure

Book a Free Audit Call

Talk through your Australian use case, deployment blockers and the right first step. No commitment.

Book your free call