Quality
Catch fabricated facts
before users see them
Detect uncertain or fabricated outputs automatically. Flag hallucinations before they cause problems.
Hallucinations
Interactive preview
QualityQuality
Documentation →Automatic detection
ML models identify outputs that are likely fabricated. No manual review required.
Confidence scoring
Every output gets a confidence score. Know which responses to trust.
Human-in-the-loop
Route uncertain outputs for human review. Combine automation with judgment.
Hallucination detection
Multiple detection methods—factual verification, consistency checking, and uncertainty quantification.
- Fact checking
- Consistency analysis
- Uncertainty scoring
DETAILS
StatusActive
Last updated2 minutes ago
OwnerPipeline Agent
Duration1.2s
Tokens used2,847
Detection analytics
Track hallucination rates over time. See which agents or prompts produce more hallucinations.
- Rate tracking
- Pattern analysis
- Improvement metrics
TREND
12h agoNow
How it works
1
Analyze
Every output is analyzed for potential hallucinations
2
Score
Outputs receive confidence and hallucination risk scores
3
Route
High-risk outputs are flagged or routed for review
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