Cloud & MLOps Consulting
We build the CI/CD, monitoring, and scaling infrastructure that keeps AI systems reliable after launch.
Avtrix AI Solutions builds the cloud infrastructure and MLOps practices that keep AI models running reliably in production — CI/CD for machine learning, monitoring, and cost-optimised scaling across AWS, GCP, and Azure.
What Is MLOps?
MLOps (Machine Learning Operations) is the set of practices and infrastructure that takes a machine learning model from a trained artifact to a reliable, monitored production service — covering deployment, scaling, monitoring for accuracy drift, and automated retraining. Without MLOps, most models quietly degrade in accuracy after launch and nobody notices until it's costly.
What We Deliver
CI/CD for Machine Learning
Automated testing and deployment pipelines so model updates ship safely and consistently.
Model Monitoring & Drift Detection
Continuous monitoring that flags accuracy degradation before it affects business outcomes.
Scalable Model Serving
Auto-scaling inference infrastructure that handles traffic spikes without over-provisioning cost.
Cost Optimisation
Right-sizing GPU/compute resources and usage patterns to control the cost of running AI at scale.
Multi-Cloud & Hybrid Architecture
Architecture across AWS, GCP, and Azure, or hybrid on-prem/cloud setups where required.
Containerisation & Orchestration
Docker and Kubernetes-based deployment for portability and reliable scaling.
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Infrastructure Assessment
We assess your current cloud setup, traffic patterns, and cost constraints.
Architecture Design
We design a serving and scaling architecture matched to your latency and cost requirements.
CI/CD & Pipeline Setup
We build automated pipelines for testing, deployment, and rollback of model updates.
Monitoring Setup
Dashboards and alerts for model performance, drift, and infrastructure health.
Ongoing Optimisation
Continuous cost and performance tuning as usage patterns evolve.
Where Cloud & MLOps Pays Off
| Use Case | Business Outcome |
|---|---|
| Scaling a model from prototype to production | Reliable performance under real user load, not just in a demo |
| Reducing GPU/inference costs | Lower cloud bills through right-sizing and auto-scaling |
| Multi-region deployment | Low-latency access for users across different geographies |
| Disaster recovery for AI systems | Minimal downtime if infrastructure fails, with automated failover |
| Continuous model improvement | Safe, automated rollout of retrained models without service disruption |
Model in a Notebook vs. Production-Grade MLOps
Model Without MLOps
- Manually redeployed whenever it needs updating
- No visibility into accuracy drift over time
- Scales poorly or expensively under real traffic
- No rollback plan if a deployment goes wrong
Avtrix MLOps
- Automated, tested deployment pipelines
- Continuous monitoring for drift and degradation
- Auto-scaling infrastructure tuned for cost and load
- Safe rollback and versioning built in
Cloud & MLOps FAQs
What happens if our model's accuracy degrades in production?
Monitoring and drift detection catch degradation early, triggering alerts and, where set up, automated retraining before it affects business outcomes.
How much does it cost to run a model 24/7?
Cost depends on model size and traffic. We design for auto-scaling so you pay for what you use, and can right-size infrastructure to control ongoing spend.
Should we use on-premises infrastructure or the cloud?
It depends on your data sensitivity, existing infrastructure, and budget. We can advise on cloud, on-premises, or hybrid based on your specific constraints.
How fast can infrastructure scale during a traffic spike?
With auto-scaling configured correctly, infrastructure can scale up within seconds to minutes depending on the cloud provider and setup.
Are we locked into one cloud provider?
We design architecture to minimise vendor lock-in where practical, and can build for multi-cloud or hybrid setups when that's a priority.
Do you handle security and compliance for hosted models?
Yes. We implement access controls, encryption, and compliance-appropriate configurations for regulated industries.
Ready to Make Your AI Production-Grade?
Tell us what's breaking or costing too much, and we'll scope an MLOps plan around it.