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Figure Eight Workflows Streamlines Multi-Step Automation for High-Quality AI Training Data

Workflows Empowers Customers to Build and Deploy Complex Annotation Tasks Quickly 

SAN FRANCISCO — Figure Eight, an Appen company, today announced Workflows, a new feature that automates the creation of complex data annotation jobs at scale. Workflows makes it possible for non-technical users to create granular, plug-and-play, multi-step annotation projects, removing bottlenecks and lowering the cost of data annotation across the board. Workflows helps customers employ complex data-annotation tasks at scale to improve their business processes and customer experiences. 

Customers Leverage Workflows to Reduce Bottlenecks, Improve Customer Experience

Creating high-quality data sets often requires completing a complicated maze of multi-step annotation jobs, making it difficult and expensive for companies to navigate setting up annotation tasks. Multi-step annotation projects can develop problems like reliance on expensive, scarce technical resources, latencies, manual error and unpredictable costs.

Workflows makes it easier to break down complex annotation jobs into simpler jobs and connect them dynamically. Workflows can help perform multiple types of annotation jobs in the same workflow on the same initial data set without human intervention, as opposed to running different independent jobs and manually processing the intermediary data. 

Workflows Lessens Annotator Burden, Reduces Costs

Workflows also provides the flexibility to target different contributors for every annotation step, so that only highly skilled contributors handle the most difficult steps.

“Overly complex data-annotation jobs increase the cognitive load on the global crowd tasked with labeling vast quantities of training data,” said Wilson Pang, CTO, Appen. “To help create  high-quality machine learning data more effectively, we’ve developed technology that streamlines the annotation process. Workflows easily connects multiple, more specific jobs within large annotation projects to optimize the process for quality and improve the experience for both AI experts and the annotation crowd. By creating more granular annotation jobs, Workflows also delivers high-quality results faster, leading to fewer wasted resources and reduced costs when compared to large, complex annotation jobs.”

Workflows Feature Set Makes Annotation Simple, Even in Complex Environments

Workflows offers customers routing rules to control when data qualifies to be routed to the next step(s). Other benefits include:

  • Plug-and-play operability: Workflows uses a graphical user interface to enable anyone, regardless of technical skill, to configure operators with routing rules.
  • Automation: Workflows automates data routing and the aggregation of results into a single report, which eliminates bottlenecks of managing the annotation process manually.
  • Improved quality: Workflows enables customers to break complex projects down into smaller tasks, which reduces cognitive load for contributors and optimizes for data-annotation quality.
  • Lower costs at scale: Machine Learning-Assisted Data Labeling (MLADL) combines human annotation with machine learning to deliver annotated data up to 20 times faster at up to a 50% lower cost.

Learn more about Workflows