Streamlines Data Science
Processes

Quick setup, standardized process, reproduce outcomes easily.

Create an Audit Trail for
Data Science Projects

Show why results were produced, every step of the project, metadata generated by artifacts.

Ensure Repeatability and Transparency

Re-create predictions, detailed lineage, explain outcomes and root causes.

Vectice Streamlines Data Science Process with Templated Methodologies

Vectice allows managers to quickly set up a data science process by using widely accepted standards such as TDSP, CRISP-DM, and Agile Data Science. This standardized process will enable teams to reproduce outcomes more easily and accurately.

Quickly set up a data science process with templated methodologies

Widely accepted standards for managing analytics projects

Standardized process allows teams to reproduce outcomes more easily and accurately

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Create an Audit Trail for Data Science Projects

If your team ever gets audited, showing why some results were produced is incredibly important. When Vectice is integrated into your workflow, it creates an audit trail that includes every step of the project. This lineage is based on metadata generated by the artifacts of your project.

Vectice creates an audit trail of every step of the project

Lineage is based on metadata generated by the artifacts of your project

Helps to show why certain results were produced

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Vectice Ensures Repeatability and Transparency In data Science

Vectice’s autoversioning and lineage make re-creating predictions smooth and easy by linking all artifacts to each process step. This detailed lineage allows companies to repeat ML experiments, detect the root cause of bias or malfunctioning, and drive consistent results and outcomes before models are deployed.

Confirm repeatability by auto-versioning and linking artifacts

Detailed lineage allows companies to repeat ML experiments

Detect the root cause of bias or malfunctioning

How easy is Vectice? Give it a try!

The Vectice Software - Core Benefits

Vectice Ensures Repeatability and Transparency in Machine Learning

Repeatability in machine learning is the ability to recreate predictions that were generated in the past using the same dataset and codebase.

Vectice's autoversioning and lineage feature makes this process smooth and easy by linking all artifacts to each step of the process. With a detailed lineage, companies have the ability to repeat ML experiments which helps show that results are consistent and repeatable, and detect the root cause of bias or malfunctioning. A lineage automatically tracks which models and datasets were used for which iterations.

Since ML models act as black boxes, teams have a responsibility to show why a particular outcome was produced, being able to explain these outcomes is essential before models are deployed. With best practices, teams can drive consistent results and outcomes, or at least show why a surprising result was produced by the model.