ML Infrastructure

Machine Learning Infrastructure (ML Infrastructure)

We provide services for building and deploying your ML models in a scalable and secure way. We leverage the best MLOps tools, containerization technologies, and cloud-native solutions

Cloud-Based ML Infrastructure

• Cloud Providers: AWS, GCP, Azure
• GPU Workloads: Deploying and managing autoscaling NVIDIA GPU nodes for AI model training and inference
• FinOps Optimization: Cost-efficient AI infrastructure monitoring

ML Workflow Orchestration

• Karpenter & K8s Cluster Autoscaler: Dynamic provisioning of AI training resources
• Argo Workflows: Automated ML pipelines and training workflows

MLOps & Model Deployment

• CI/CD for ML Models: GitHub Actions, GitLab CI/CD, Bitbucket, Jenkins
• Model Deployment: Fast API inference using Ollama
• Monitoring & Logging: Prometheus, Grafana, New Relic, and Opik for AI performance tracking and evaluation

On-Prem & Edge AI Infrastructure

• Local LLM Execution: Ollama for on-prem AI model deployment
• Hybrid AI Solutions: AI model execution across on-prem, edge, and cloud