Image Generation Requests

Leap converts a text prompt into an image through its API, using a base model or one a team has tuned themselves. A Beam agent submits a prompt built from an approved template, such as a product description pulled from a record, and attaches the returned image to that record once it comes back. It does not write new prompts on its own. Images that come back blank, flagged, or clearly off from what the record describes are held back rather than attached, and a person checks the result before it goes anywhere customer-facing.

Custom Model Fine-Tuning

Leap lets a team fine-tune a model on their own images so outputs reflect a specific style or subject. A Beam agent watches for a batch of approved training images tagged ready in storage and starts a fine-tuning job through Leap's API once the batch hits the size the team requires. It does not decide which images belong in a training set. If a fine-tuning job fails or returns a model that scores poorly on a test set, the agent leaves the previous model in place and flags the job for a person to look into.

API Usage Alerts

Every image generation or fine-tuning job through Leap draws on a usage quota tied to the account. A Beam agent checks usage against the threshold a team has set and notifies a lead when the account is approaching its limit, before jobs start failing outright. It does not raise the limit or change the plan itself. Where usage jumps sharply in a short window, which can point to a misconfigured job firing repeatedly, the agent flags the spike for a person to check rather than letting it continue unexamined.