The Challenge:

Building AI systems requires systematic human evaluation at scale. Teams need domain experts to execute custom evaluations, label preference data for fine-tuning, monitor production systems for drift, and annotate training datasets. Executing these workflows in-house is time-consuming and expensive.

Our Approach:

Trained experts who execute your AI workflows while we handle the HR and quality control:

Evaluation & Testing

• Execute reviews against your custom rubrics

• Label evaluation datasets and identify failure modes

• Run regression testing on model updates

Preference Data Labeling

• Rank model outputs for RLHF/DPO pipelines

• Label chosen/rejected response pairs at scale

• Apply your alignment guidelines consistently

Production Monitoring

• Continuous review of production outputs

• Flag anomalies and quality degradation

• Document failure patterns for engineering teams

Training Data Annotation

• Label training data per your specifications

• Create benchmark and test datasets

• Execute complex annotation tasks with domain expertise
  
  
  

How It Works:

1. Onboarding: Learn your frameworks and quality standards

2. Training: Align teams to your requirements

3. Execution: Systematic workflow execution at scale

4. Delivery: Structured outputs for your ML pipelines

Why Choose Us:

Cost-effective, reliable execution from our network of experts across Africa and globally.