The Bloom Program: Our Training Philosophy

When we bring a new expert into the Pasiflora AI network, we don't hand them a task queue and wish them luck. We run them through the Bloom Program, a structured onboarding process designed to set every expert up for success and ensure the quality our clients depend on.

Why Onboarding Matters

AI training data work is different from most knowledge work. The output is not a report or a product, it is signal. And signal quality depends not just on expertise, but on how that expertise is applied to a specific kind of task. Even brilliant researchers make common mistakes when they first start: over-explaining where brevity is better, under-specifying where precision is needed, or missing the frame the model will use to interpret the response.

The Bloom Program closes that gap. It takes experts from "smart person with domain knowledge" to "effective contributor to AI training pipelines", and it does it fast.

What the Program Covers

• How AI training data works, what RLHF is, how human feedback shapes model behavior, and why the details of a response matter as much as the substance.
• Task-type training, annotating, ranking, rewriting, and red-teaming, with practice on calibrated examples before going live.
• Quality standards, what excellent looks like in each task type, common failure modes, and how to self-review.
• Platform walkthrough, how to navigate our task system, flag issues, communicate with coordinators, and track your performance.

Quality at Scale

The Bloom Program is also how we maintain quality as we grow. Every expert goes through the same calibration. Every feedback loop uses the same quality rubrics. When a client receives data from Pasiflora AI, they know it was produced by people who were trained to produce it, not just people who happened to have relevant credentials.

Expertise is the prerequisite. The Bloom Program is how we turn expertise into impact.