Machine Learning Infrastructure

The Provectus Machine Learning Infrastructure is a cloud-native solution that serves as a foundation for AI. It improves the velocity of data science teams, adds visibility and audibility to the machine learning process, allowing to rapidly launch AI projects.

Overview

Companies looking to adopt AI have to aggressively hire data scientists and ML engineers capable of using a wide variety of ML platforms, tools, and cloud products. They have to invest a massive amount of resources to come up with tangible solutions to achieve their business goals.

The Provectus Infrastructure for Machine Learning solution allows organizations to avoid these issues, offering a readily available ML infrastructure platform that is built using the best practices and processes of AI adoption.

The solution ensures ML experimentation productivity & reproducibility, transparency & auditability, and better collaboration, thereby significantly reducing the number of AI/ML’s infrastructure challenges.

ML Experimentation Productivity

Transparency & Auditability

Experimentation Reproducibility

Better Collaboration

High Customization vs. Ready to Go? Get Both

80%

Machine Learning experimentation environment designed for reproducibility
Versioned, scalable and metadata-aware Feature Store
Reference architecture for immutable and reusable machine learning pipelines
Machine Learning training augmentation with advanced instrumentation and monitoring
Integration with cloud services, such as AWS SageMaker
Integration with data enrichment platforms, such as Figure Eight and AWS Ground Truth
Production deployment and re-training infrastructure

20%

customizable for a
competitive edge

Machine Learning Pipelines architecture, implementation, and optimization
Migration of legacy cumbersome machine learning processes to a newly selected platform
Training and coaching for client’s engineers and managers

Benefits