Quality Indicators
Threader shows you how grounded each output is. These indicators help you know what to trust and what to validate.
Why Transparency Matters
Most AI tools present outputs without context. Threader's quality indicators make data provenance visible so you know where to apply scrutiny.
"These indicators measure process quality, not factual accuracy. A high score means the output is well-grounded in the inputs provided."
The Three Indicators
| Indicator | What It Measures | Where |
|---|---|---|
| Reliability Score | Client-provided vs AI-generated content | All tools |
| Data Reliability Index | Quality of market data underlying analysis | Positioner, Competitor |
| Analysis Confidence | Confidence in specific generated outputs | Positioner |
Reading the Scores
| Badge | Score | What to Do |
|---|---|---|
| 🟢 Strong | 70-100% | Defend it in a pitch |
| 🟡 Mixed | 50-69% | Validate key claims before presenting |
| 🔴 Needs Input | 0-49% | Treat as starting point, add your own data |
How to Improve Your Scores
| Action | Effect |
|---|---|
| Upload client documents | Improves all three indicators |
| Edit AI outputs | Improves Reliability Score (60% → 80%) |
| Complete upstream tools | Improves downstream Analysis Confidence |
| Choose well-known brands | Improves Data Reliability Index |
Low scores don't prevent progress. They inform how much review effort to apply.