What heavy lifting do A2I / Label Studio do?

1. They turn predictions into review tasks

A2I has the concept of a human loop, which is basically one human review job. For custom ML workflows, your application filters predictions using your own criteria, decides whether review is needed, and sends the item to A2I. A2I then sends the task to the configured work team and collects the review result.

In ClaimFlow AI, you are building this yourself:

finalStatus === NEEDS_REVIEW
→ create ReviewTask
→ show in review queue

So your ReviewTask is your version of A2I’s human loop.

2. They manage the reviewer UI

A2I uses worker task templates. These templates define the UI and instructions the worker sees; for custom tasks, you create an HTML template yourself.

Label Studio gives ready-made labeling interfaces.

In ClaimFlow AI, your reviewer UI will be:

original document / email
+ Gemini extracted fields
+ validation issues
+ editable corrected fields
+ approve / edit_and_approve / reject buttons

So the “heavy lifting” you are building is not just a page. It is the review interface + action model.

3. They manage review workflow configuration

A2I’s human review workflow, called a flow definition, specifies review conditions, workforce, worker instructions, task configuration, time limits, number of workers, and output location.

In ClaimFlow AI, this maps to future config like:

review trigger rules
priority
assigned reviewer
review task status
review instructions
review timeout

For Week 2, keep it simple:

PENDING
IN_REVIEW
APPROVED
EDITED_AND_APPROVED
REJECTED
NEEDS_MORE_INFO