Engineering
Cloud, data and MLOps
Getting a system live is the start. We build the deployment, observability and retraining machinery that keeps it working as data and load change.
Capabilities
What is included
Cloud architecture
Environment design, networking and cost-aware sizing on AWS and comparable platforms.
Deployment automation
Repeatable pipelines with review gates, so releases are routine rather than risky.
Containers
Containerised services orchestrated with Kubernetes where scale warrants it.
Model deployment
Serving infrastructure with versioning and controlled rollout.
Monitoring
Application, data and model monitoring with alerting on drift and failure.
Automated retraining
Scheduled and triggered retraining with evaluation before promotion.
Data pipelines
Orchestrated ingestion and transformation with lineage and recovery.
Reliability and optimisation
Capacity review, performance tuning and infrastructure cost reduction.
Also relevant