Entry Point AI

About Entry Point AI

Entry Point AI is a fine-tuning platform built around the practical bottleneck in task-specific models: not the training run, but assembling enough labelled data to make one worth training. It bundles three tools into a single workflow. Transforms adds an AI column to a dataset — run one prompt across thousands of rows to tag, extract or classify every record, and watch the results fill in. Synthetic Data takes the handful of real examples a team already has and expands them into a full training set, with a human approval step so only rows that pass review are routed into training or validation. Fine-tuning then trains a task-specific model intended to beat a large general model on the narrow job it was built for. Each tool stands on its own, so a team can enter the workflow wherever their data sits — some arrive with raw unlabelled rows, some arrive with a small gold set and a labelling problem, some arrive ready to train. The positioning is aimed at teams who have concluded that prompting a frontier model is too slow, too expensive or too inconsistent for a high-volume classification or extraction task, and who want a smaller model that holds up in production. Plans are priced on row volume and seats, with premium support on the top tier.

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