You’ve probably heard the phrase used before, in technical meetings. But what does it mean, really?  What’s an “AI Pipeline?”

An AI Pipeline is an end-to-end construct that orchestrates data flow into, and output from, a machine learning model (or set of multiple models).

The pipeline includes the raw data input from the source, features, outputs, the machine learning model and model parameters, and other prediction outputs. It also includes the underlying hardware to run and scale ML models and tools for data cleaning & preparation, feature engineering & selection, and understanding, interpreting, and integrating the ML model’s results.

Data science teams, often with the support of IT or DevOps, create and manage these pipelines.  Ad-hoc maintenance is expensive to do, difficult, and time-consuming. Entire disciplines, like Machine Learning Operations (MLOps) have been created to help manage, support, and audit AI pipelines.

At Squark, we’ve simplified the AI pipeline creation process so it’s automatic, fast, easy, affordable, and powerful. Connect to your sources and the AI Pipeline is built for you in seconds, in clicks, with no code.  Servers are created to scale to your data.  Complex AI operations are performed on your data.  Results are shown to you in human-readable and understandable text and visualizations. Send the results to any system you want. Or simply view/download them in your browser.

See the power of Squark’s codeless AI in action, as simple to use as a spreadsheet.  Click here to talk with an expert and see Squark’s automatic AI.