ApexMLOps

We build production-grade machine learning systems with clean architecture, reliable pipelines, and scalable infrastructure.

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What We Do

End-to-end MLOps services designed for teams building AI products at scale.

MLOps Audit

We evaluate your ML lifecycle, architecture, CI/CD, and deployment strategy, and deliver an actionable blueprint.

Pipeline & Infrastructure

We build training, validation, deployment, and monitoring pipelines using GCP, AWS, or Azure.

Managed Model Operations

We maintain your production ML systems, monitor drift, automate retraining, and ensure uptime.

Capabilities

We help you move from notebooks to fully-operational AI systems.

CI/CD for ML

Automated model testing, packaging, and deployment pipelines.

Model Serving

Scale models using Cloud Run, Vertex AI, SageMaker, or Kubernetes.

Monitoring + Drift Detection

Production metrics, data quality, drift alarms, dashboards.

Data Pipelines

Ingestion, preprocessing, feature stores, and ETL/ELT workflows.

Infra-as-Code

Terraform, Cloud Build, GitHub Actions, GKE, distributed training.

Cost Optimization

Improve training and inference efficiency across cloud platforms.

Leadership

The team behind ApexMLOps.

Markos Muche

Founder & CTO
Expert in MLOps, production ML, cloud architecture, and pipelines. 3× Google Cloud Professional.

Ex-Microsoft Co-Founder

COO & Business Strategy
Enterprise-grade engineering leadership and delivery experience.

Ready to Scale Your AI into Production?

Get a free 30-minute strategy call with an MLOps expert.

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