MLOps

Models drift, data sources change and costs creep. MLOps is the engineering that keeps a live model trustworthy — versioned, observable and repeatable.

What we build

• Training and deployment pipelines that run the same way every time
• Model and data versioning, so any prediction can be traced to what produced it
• Monitoring for accuracy, drift, latency and inference cost
• Automated retraining and safe rollout: shadow runs, canaries and quick rollback

How we deliver it

• Infrastructure as code on your cloud of choice
• CI/CD for models alongside the application release process
• Access control and audit trails over data sets, models and prompts
• Runbooks and alerting so an on-call engineer knows what to do at 2am

Where it fits

• Models trained in notebooks that nobody can reproduce
• No one notices when quality degrades until a customer complains
• Several models in production and no consistent way to run them