Data Engineering
for MLOps

Optimize price/performance to continuously improve the yield of your ML model training jobs.

CloudGeometry AWS Partner Network SaaS Factory Competency

CloudGeometry CNCF Kubernetes Certified Service Provider

CloudGeometry AI/ML Engineering enables both Gen AI and classical AI/ML techniques. We design and deploy models tailored to specific operational needs, integrating AI to enhance the functionality of your existing systems, with advanced algorithms to foster innovation and improve decision-making. We help you build robust, scalable AI frameworks that adapt to changing business needs.

Metrics and transparency across ML/AI teams

Iterative ML/AI task profiling and
modeling

Spark integration for iterative analytic processing

HOW IT WORKS

GitOps Lifecycle for Data engineering

Build and run key foundation processes for the unique lifecycle requirements at the intersection of changing modeled data and changes to production software code.

Continuous Integration: Expands testing and validating code and components to testing and validating data, data schemas, and models.

Continuous Delivery: Integrates multiple software packages and services configured to align your ML training pipeline for feedback with model prediction and optimization

Continuous Training: Does for ML systems what CI/CD does for applications, automatically retraining and serving models

Enhanced pipeline: With automated data and model validation steps, including pipeline triggers and metadata management.

Pipeline Automation management: Featuring source control, test and build services, deployment services, model registry, features store, ML metadata store, and E2E pipeline orchestration

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Supported platforms

Our platform and cloud-agnostic approach applies systematic, closed-loop automation and monitoring at all steps of ML system construction, including integration, testing, release, deployment and infrastructure management.

Features & Benefits

For customers who prefer an open source approach, CloudGeometry features OptScale. It’s a single platform that provides configuration, automation, data collection, data verification, testing and debugging, resource management, model analysis, process and metadata management, serving infrastructure, and monitoring. Key benefits include: