MLOps Setup Services
MLOps Setup Services for Startups
CI/CD and operational practices applied to model deployment, for startups building ML-powered products. Delivered by our in-house team.
When model deployment needs real DevOps discipline
- Deploying a new model version is manual and ad hoc.
- There's no way to know which model version is running in production.
- Rolling back a bad model deployment is stressful, not routine.
- Nobody's monitoring model performance once it's deployed.
Model deployment still needs the fundamentals, versioning, automation, and monitoring.
What we do
Model deployment pipelines
CI/CD applied to model deployment, not just application code.
Model registry & versioning
Track which model version is running where, and roll back cleanly if needed.
Monitoring for model performance
Visibility into model behaviour and drift, not just application uptime.
Data pipeline integration
Connect data pipelines to the deployment process reliably.
Ways to work with us
Not sure which fits? Tell us the problem on a free call and we'll recommend one.
Fixed-scope project
A defined setup with a clear deliverable and timeline.
Managed support (retainer)
We keep your infrastructure healthy month to month.
Hourly / as-needed
Short, specific tasks without a long commitment.
Dedicated engineer
An engineer from our team focused on your account.
White-label for agencies
We deliver DevOps under your brand for your clients.
What you actually receive
- Model deployment pipeline
- Model registry / versioning setup
- Monitoring for model performance
- Documentation
Exactly which of these you get depends on the engagement, we scope it on the call.
What changes for your business
- A repeatable model deployment process
- Faster iteration on model updates
- Better visibility into model performance in production
- The same DevOps discipline applied to ML workloads as the rest of your stack
What clients say
Case studies coming soon.
Real client testimonial goes here once we have permission to publish it.
Name, role, Company
Real client testimonial goes here once we have permission to publish it.
Name, role, Company
Real client testimonial goes here once we have permission to publish it.
Name, role, Company
Questions about MLOps setup
This is an emerging area of our work, the underlying DevOps practices (CI/CD, infrastructure as code, monitoring) are the same disciplines we apply elsewhere, adapted to ML workloads.
Specific MLOps project history and credentials are confirmed on request, we don't claim case studies that aren't real.
Whichever your team already uses, we build around your existing stack rather than pushing a specific framework.
Related, but distinct, this page focuses on the model deployment pipeline itself; our AI/LLM page covers the broader infrastructure picture.
Yes. We sign an NDA before any work starts, and you own everything we build for you.