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AI and machine learning model management and operations for enterprise data science teams
Verta Overview
Verta is a complete MLOps (ML Operations) platform focused on operationalization of ML models, i.e., integrating ML development and delivery into regular software in a way that allows data scientists to continue focus on machine learning and data science, while providing ML and DevOps Engineers the means to safely and reliably integrate ML into the broader software ecosystem in any organization.

Verta is an open-core platform; i.e., the platform is based on core open-source technology developed by the Verta team that is freely available. Verta provides MLOps functionality in three key areas: model versioning and metadata, model deployment and release, and real-time model monitoring.
  • System-wide Features:
  • Teamwork and Collaboration
  • Enterprise Security
  • Governance
  • Enterprise Support
  • MLOps Features:
  • Data Acquisition
  • Data Versioning
  • Data Visualization
  • Data Preparation
  • Data Pipelines
  • Data Labeling
  • AutoML
  • Featurization
  • Feature Store
  • ML Pipelines or Workflows
  • Model Registry
  • Model Marketplace
  • Model Training
  • Distributed Model Training
  • Model Debugging
  • Experiment Management
  • Deep Learning Support
  • Reinforcement Learning Support
  • Bias Detection and Mitigation
  • Model Explainability
  • Hyperparameter Optimization
  • Model Packaging
  • Model Deployment and Serving
  • Edge ML Support
  • Model Monitoring
  • Cost Management
  • ML Infrastructure Orchestration
  • Accelerator Support
  • Kubernetes Support
  • Experiment Management Sub-features:
  • Log: Data
  • Log: Code
  • Log: Parameters
  • Log: Metrics and Losses
  • Log: Descriptions
  • Log: Rich Media
  • Log: Hardware Consumption
  • Log: System Information
  • Log: Environment Configuration
  • Log: Files
  • Tracking: Organize Experiments
  • Tracking: Live Monitoring
  • Tracking: Can Track Thousands of Experiments
  • Visualize: Compare and Evaluate Experiments
  • Collaboration: Role Based Access Controls
  • Collaboration: Customizable Experiment Reporting
  • Model Deployment Sub-features:
  • Model serving
  • Integrates with CI/CD pipeline
  • Roll-back options
  • Optimizes Infrastructure Dynamically
  • Auto-scales Infrastructure
  • Supports Batch Inference
  • Supports Streaming Inference

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Additional Product Information
Deploys On
  • Amazon Web Services
  • Google Cloud Platform
  • Microsoft Azure
  • Other Public Cloud
  • Kubernetes
  • Private Cloud or Datacenter
  • SaaS
Free Version
Paid Version
Verta Vendor Information
Vendor Overview
Verta builds software infrastructure to help enterprise data science and machine learning teams develop and deploy ML models.
Vendor Details
Year Founded
HQ Location
Palo Alto, California, United States
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