As AI models become more sophisticated, so does the need for precise, consistent, and diverse training data. The challenge? Scaling human-in-the-loop (HITL) operations without drowning in bottlenecks, inconsistent outputs, or costly rework.

For many fast-growing AI teams, internal resources simply can’t keep up with the pace of model iteration. That’s where an operational partner becomes critical.

The Challenge: High Complexity Meets High Velocity

AI teams within companies must produce massive volumes of logic-based tasks, annotations, judgments, and quality checks in rapid cycles. When workflows aren’t standardized, quality becomes unpredictable and downstream model performance suffers.

The NeoWork Advantage: End-to-End HITL Staffing Built for Precision

NeoWork builds and manages specialized data operations teams, from task writers to annotators to dedicated QA evaluators who embed directly into your training pipeline.

Our pod-model ensures:

• Consistency across every task delivered
• Multi-layer replication that ensures validity
• QA checks that maintain accuracy, fairness, and diversity
• A workforce that scales with your training needs

The Impact on AI Performance

When data is produced cleanly and consistently, models learn faster and with fewer blind spots.

NeoWork clients see >98% QA accuracy, like Zitti (acquired by Block), a company that makes software to help restaurants get optimal prices on food. They hit a 99.9% Service Level Agreement rate of sharing pricing insights on 2,950 items before 7AM daily.

Human precision is still essential to building strong AI. NeoWork makes it scalable.