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  • 🏠Introduction
    • Vectice overview
      • Autolog
      • Next-Gen Autolog [BETA]
      • AskAI
      • Vectice for financial services
  • 🏁Quickstart
    • Getting started
    • Quickstart project
    • Tutorial project
    • FAQ
  • ▶️Demo Center
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  • 📊Manage AI/ML projects
    • Organize workspaces
      • Create a workspace
      • Workspace Dashboard
    • Organize projects
      • Create a project
      • Project templates best practices
    • Invite colleagues
    • Define phase requirements
    • Collaborate with your team
  • 🚀Log and Manage Assets with Vectice API
    • API cheatsheets
      • Vectice Python API cheatsheet
      • Vectice R API cheatsheet
    • Connect to API
    • Log assets to Vectice
      • Autolog your assets
      • Log datasets
      • Log models
      • Log attachments and notes
      • Log code
      • Log a custom data source
      • Log assets using Vectice IDs
      • Log dataset structure and statistics
      • Log custom metadata in a table format
      • Log MLFLow runs
    • Retrieve assets from app
    • Manage your assets
    • Manage your iteration
    • Preserve your code and asset lineage
  • 🤝Create Model documentation and reports
    • Create model documentation with Vectice Reports
    • Streamline documentation with Macros
    • Auto-document Models and Datasets with AskAI Prompts
    • Document phase outcomes
  • 🗂️Admin Guides
    • Organization management
    • Workspace management
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    • User management
      • User roles and permissions
      • Update a user role in your organization
      • Activate and deactivate users
      • Reset a user's password
    • Manage report templates
  • 🔗Integrations
    • Integrations Overview
    • Integrate Vectice with your data platform
  • 💻IT & Security
    • IT & Security Overview
    • Secure Evaluation Environment Overview
    • Deployment
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      • Kubernetes self-hosted offering
        • General Architecture & Infrastructure
        • Kubernetes on GCP
          • Appendices
        • Kubernetes on AWS
          • Appendices
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          • Appendices
        • GCP Marketplace deployment
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        • Configuration
      • Bring Your Own LLM Guide
    • Data privacy
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      • Generic SAML integration
      • Okta SSO integration
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      • Best practices
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    • Monitoring
      • Installation guide
      • Customizing the deployments
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    • Integrating Vectice Securely
  • ⭐Glossary
    • Concepts
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        • Setup a project
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        • Iterative development
      • Datasets
        • Dataset resources
        • Dataset properties
        • Dataset lineage and versions
      • Models
      • Reports
  • 🎯Release notes
    • Release notes
  • ↗️References
    • Vectice Python API Reference
    • Vectice R API Cheatsheet
    • Notebooks and code samples
    • Vectice website
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  • Platform, framework, and tool agnostic:
  • Why Vectice?
  • What's next?

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  1. Introduction

Vectice overview

Auto-document with Vectice

NextAutolog

Last updated 5 months ago

Was this helpful?

Vectice is the go-to Auto-Documentation software for machine learning projects and their governance. Use to log your data science assets using one line of code. For financial institutions, you can use to streamline model reporting and validation.

Watch our Product Overview video to learn more!

We enable organizations to:

Auto-Generate Documentation from your Existing AI Tools

Compatible with AI tools and platforms supporting Python and R, Vectice generates ongoing and comprehensive documentation of your data science projects in an intuitive user interface.

Cross-functional collaboration and transparency

At a glance, data scientists, product managers, compliance officers, and other stakeholders can review project progress, share their business insights, and access activities of all existing, ongoing, and new projects.

Enforce best practices and governance

Accelerate the value delivery of your organization by standardizing AI projects, establishing best practices, and preparing for the upcoming AI regulations.

Platform, framework, and tool agnostic:

Why Vectice?

Vectice is a powerful tool that helps data science and machine learning teams streamline workflows, boost collaboration, ensure reproducibility, and make better decisions based on tracked experiments and versioned metadata.

Data science and machine learning teams utilize Vectice to:

  • Automate documentation of important artifacts in the data science and machine learning workflow. Vectice automatically logs and organizes metadata related to datasets, models, and associated code.

  • Enhance teamwork with Vectice, a centralized platform enabling team members to share and access pivotal milestones and artifacts. This fosters transparency, minimizes the potential for errors, and facilitates effective building upon one another's work.

  • Effortlessly search and locate previous work for reusability or to find subject matter experts.

What's next?

Integrates with your favorite tools and platforms

Auto-document important artifacts

Streamline collaboration and reproducibility

Discoverability and search ability

Discover how you can log all data science work with one line of code with Vectice's !

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