At the heart of Straker's verification infrastructure is our Quality Estimation (QE) system—a sophisticated scoring engine that evaluates AI-generated content in real-time.
How QE Works
Our QE system evaluates content across multiple dimensions:
- Semantic Accuracy: Does the content accurately convey the intended meaning?
- Fluency: Is the content grammatically correct and naturally readable?
- Terminology: Does it use industry-specific and brand-specific terms correctly?
- Style Consistency: Does it match the expected tone and voice?
The Scoring Process
Each piece of content receives a score from 0-100. This score is calculated using a combination of:
- Neural Quality Estimation: Deep learning models trained on millions of human-evaluated content pairs
- Custom Model Alignment: Comparison against your organization's custom-trained Tiri model
- Historical Pattern Analysis: Detection of patterns that have historically required human correction
Threshold Configuration
Organizations can configure score thresholds based on their risk tolerance:
- High Confidence (95+): Auto-publish with no human review
- Medium Confidence (80-94): Spot-check sampling
- Low Confidence (<80): Mandatory human review
This flexibility allows organizations to balance speed, cost, and quality based on content type and audience.