Managing a machine learning data labeling pipeline means juggling annotation queues, reviewer assignments, export schedules, and cross-team coordination - all at once. When Label Studio handles your annotation work and Pipefy manages your operational processes, keeping them in sync requires constant manual effort. Neotask connects both tools so you can orchestrate your entire labeling workflow through conversation. Create Label Studio projects and immediately spin up corresponding Pipefy cards to track progress. Query annotation statistics and automatically update pipe fields with the latest counts. Move cards through phases as datasets reach labeling milestones. Stop switching between dashboards and start managing your ML data pipeline the way it actually flows.
Send completed Label Studio tasks into Pipefy approval pipelines automatically.
Track annotation batch progress across Pipefy workflow stages.
Eliminate manual status updates between labelers and downstream teams.