## What we design

### Review Interfaces

AI output shown alongside source material. Uncertainty highlighted. Correction effortless with inline editing and one-click approvals. Designed for 5-second approval when the AI is right.

### Confidence-Based Routing

High-confidence outputs proceed automatically. Medium gets lightweight review. Low gets full review or specialist routing. Thresholds calibrated to error tolerance.

### Batch Review Workflows

For high-volume use cases. Scan many items quickly, filter by confidence, spot-check rather than review everything. Quality oversight at scale without creating a bottleneck.

### Correction & Feedback Loops

Every correction captured as structured data. Feeds prompt improvement, fine-tuning datasets, and systematic quality analysis.

### Escalation Paths

When the AI can’t handle a case. Routes to the right person with full context. Nothing falls through the cracks.

### Audit Trails

Every AI decision and human review logged. Who reviewed, when, what changed, what was the final result. Required for regulated environments.

## What you get

- Review interface designed for the specific use case
- Confidence calibration and routing logic
- Feedback capture and correction pipeline
- Audit trail infrastructure
- Quality dashboards
- Reviewer training materials

## Deploying AI where accuracy actually matters?

The review interface is often the most important part of an AI system. It determines whether the organisation can actually use AI in production. We design it accordingly.