Operate
Infrastructure that keeps AI fast, observable and affordable.
Cloud architecture, deployment pipelines and monitoring for machine learning and LLM workloads, built for reliability and cost control.
Overview
Cloud & MLOps
Getting a model to work once is the easy part. Keeping dozens of models and AI services reliable, secure and cost-effective is an engineering discipline.
We build the platform, automation and observability that let your teams ship AI changes safely and often.
Problems we solve
- Manual, risky deployments of models and prompts
- GPU and API bills that are hard to predict or attribute
- No monitoring of model quality once in production
- Each team reinventing infrastructure for every project
What’s included
A complete engagement, end to end.
Platform design
A reference architecture for training, serving and evaluation.
CI/CD for ML
Automated testing and promotion of models, prompts and pipelines.
Infrastructure as code
Reproducible environments with security baked in.
Observability
Latency, cost, quality and drift dashboards with alerting.
Cost governance
GPU scheduling, autoscaling, caching and chargeback reporting.
Managed operations
Optional 24/7 monitoring and incident response.
Process
How the work unfolds.
Phase 1
Review
Assess current infrastructure, workflows and spend.
Phase 2
Design
Agree a platform blueprint and migration plan.
Phase 3
Implement
Build the platform alongside your engineers.
Phase 4
Run
Operate, optimise and hand over at your pace.
Technology
Tools we use, chosen on merit
Cloud
- AWS
- Microsoft Azure
- Google Cloud
- On-premises
Platform
- Kubernetes
- Terraform
- MLflow
- Ray
Observability
- OpenTelemetry
- Prometheus
- Grafana
Sample outcomes
What clients typically see
- Daily
- Model release cadence, up from quarterly
- −40%
- GPU spend after autoscaling and scheduling
- <15 min
- Mean time to detect model quality issues
Illustrative results from past engagements. Outcomes vary by context.
FAQ
Common questions
Which cloud provider do you recommend?
The one that fits your existing contracts, team skills and compliance needs. Our designs are portable where it matters.
Can you work within our security policies?
Yes. We work inside your accounts, follow your change management and pass your security reviews.
Do you offer managed hosting?
We offer managed operations of infrastructure in your own cloud account, so you retain ownership and control.
Is MLOps worth it for a small team?
A lightweight version is. We right-size the platform to the number of models and people you have.
Let’s discuss your project.
Tell us what you want to achieve with cloud & MLOps. A senior consultant will reply within one business day.