One of the most powerful features in Aiceberg is the ability to see why a Signal was triggered and why it wasn't. Trace is the feature that powers our Signal detection without relying on generative AI models.
Incoming prompts are semantically chunked to preserve meaning and processed through our patented models to identify the most relevant samples. Those samples are then used to determine Signal results. Probability calculations are made and users can see the likelihood that the content matches specific risk Signals as well as the actual samples that contribute to the result.
Why this matters:
- Every detection can be audited and traced back to specific training examples
- Unpredictable outputs are reduced with verifiably consistent performance
- CPU-only processing means classification is fast
- Scores are based on mathematical proximity, not black box decisions, so scoring is transparent
To view Trace, tap into prompt details from Monitoring and tap the Trace icon at the top.
Aiceberg semantically chunks long inputs, ensuring that each piece contains complete thoughts or concepts to improve retrieval accuracy and reduce noise.
Use the toggle to switch between prompt and response analysis and see any flagged Signals or detected Intent. The numbers in the Signal pills indicate the chunk in which the Signal was found.
Tapping the numbered selector above the chunk text will navigate you to that chunk. Selectors are highlighted to show where Signals occurred. Tap the Explainability chevron to show the five nearest neighbor samples that were used to determine similarity for Signals in that chunk.
