Managed MLOps Services for Your Business
MLOps consulting services at Omeiro mean we operate the machinery around your models, not just advise on it. We monitor models in production, trigger retraining when performance slips and keep an audit log so every change can be explained later.
How managed mlops works, step by step
A made-up example of one run, from start to finish. Each step is logged so you can see what happened.
- Something happens
A form, an email, a payment or a new row.
- The workflow runs
Steps you agreed, in the right order.
- Errors are caught
Failed steps retry or alert a person.
- You see what ran
A simple log of every run.
Sample Made-up names, data and steps to show how a run is logged. Your steps, tools and rules follow your business.
What you get with managed mlops
Up to 2 models in production: monitoring, retraining, audit log.
Basic Package
Up to 2 models in production: monitoring, retraining, audit log, 48 h response. 24h turnaround, 1 round + 30-day fixes.
Standard Package
Up to 6 models; monthly governance report, 24 h response. 24h turnaround, 1 round + 30-day fixes.
Premium Package
Up to 15 models; 4 h response. 24h turnaround, 1 round + 60-day fixes.
Clear brief first
We confirm what you need before work starts, so the scope is clear on both sides.
Revisions listed
Each package shows its revision rounds. A round is one list of changes sent together.
Yours once paid
Copyright of the final work passes to you once the order is paid in full.
Third-party tools, API usage and hosting are billed to your own accounts, so the setup stays with your business.
How our managed mlops works
Inventory the models
We list each model, its data sources, owners and current checks.
Add monitoring
Performance and drift metrics are tracked with alerts for the people responsible.
Schedule retraining
Retraining runs follow rules you approve, and every run is logged.
Report and review
Higher tiers receive governance reports and evidence packs on a regular cycle.
MLOps consulting: what a production model needs after launch
Launching a model is the beginning of the work. Models drift when customers, prices or data sources change, so MLOps consulting centres on watching live inputs and outputs against what the model saw in training. Before choosing a tier, list your production models, how each makes a decision, what a wrong prediction costs and who currently notices when quality drops. The honest answer is often nobody, which is exactly the gap monitoring fills.
Retraining needs rules, not enthusiasm. Decide what triggers a new run, whether a person approves each release and how you roll back a model that performs worse. Strong MLOps consulting records data versions, code and metrics for every run, so an auditor or colleague can reproduce a result later. Pick the tier by model count and response time, and tell us your cloud, frameworks and data sources so the monitoring plugs into the stack you already have.
In short
- Fixed price, shown before you order.
- Data science teams who build models but have nobody to watch them in production.
- Copyright yours after full payment.
Managed Mlops: common questions
How much does managed mlops cost?
Prices are fixed and shown by package on our Managed Mlops pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does managed MLOps take?
Delivery depends on the package: Basic 24h turnaround; Standard 24h turnaround; Premium 24h turnaround.
What is included in the Basic Package?
The Basic Package includes: Up to 2 models in production: monitoring, retraining, audit log, 48 h response. Higher packages add more scope, revisions and support.
Can I get a custom MLOps governance package?
Yes. If none of the packages fits, use the custom package form on our pricing page to describe what you need, and our team sends you a fixed price.
Do you need to take over our infrastructure?
We work inside your environment with the access you grant. We do not need to move your models.
Which model types are covered?
Models in production that you can describe to us. Tell us the frameworks and hosting before ordering.
What is in the audit log?
A record of changes, retraining runs and approvals, so you can show what happened and who agreed.
Can we start with two models and add more?
Yes, by moving up a tier.
What is model drift?
It is the gradual loss of accuracy when real-world data moves away from the data a model was trained on. Monitoring inputs and results is how teams notice it before customers do.
Who owns the final work?
Copyright of the final work passes to you once the order is paid in full. Paid fonts, stock files or licences, if used, are licensed in your name.
Ready to start your managed mlops?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.