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AI Pipeline

What Is an AI Pipeline?

It typically includes the tools needed to extract, transform, and load data from various sources into a target system, along with the workflow structure that connects each stage of getting a model into production.

Key Stages

  1. Data cleaning and preprocessing
  2. Model training
  3. Testing and deployment
  4. Monitoring and updating

‍

A simple horizontal flow diagram of the 4 stages (Data cleaning → Model training → Testing/deployment → Monitoring) as connected boxes.

FAQ

Largely synonymous in practice, "AI pipeline" is the more current, broader term, but both describe the same structured flow from raw data to a running model.

Mainly at the data stage (what's being fed in, and whether it's sensitive or manipulated) and the monitoring stage (whether the deployed model's behavior is actually being watched once it's live).


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Related Terms


AI Inventory

An AI inventory is the complete, actively maintained record of every AI tool, model, and agent in use across an organization, including the ones IT never approved.

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