Model Tracking

What is MLflow, and How to Deploy It in an Enterprise Data Stack?

Last updated on
April 10, 2025
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What is MLflow?

MLflow is an open-source platform for managing the entire machine learning lifecycle, including experiment tracking, model packaging and deployment, and model management. It is flexible and scalable, and particularly useful for data scientists and organizations wanting to deploy machine learning models in a consistent and reliable way.

Use cases for MLflow

Assess Investment Thesis Fit and Drift Efficiently

Optimize Ticket Pricing with Dynamic Demand Modeling

Predict Property Values with AI Market Analysis

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Why is MLflow better on Shakudo?

Why is MLflow better on Shakudo?

Core Shakudo Features

Own Your AI

Keep data sovereign, protect IP, and avoid vendor lock-in with infra-agnostic deployments.

Faster Time-to-Value

Pre-built templates and automated DevOps accelerate time-to-value.
integrate

Flexible with Experts

Operating system and dedicated support ensure seamless adoption of the latest and greatest tools.

See Shakudo in Action

Neal Gilmore
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