Glossary term
Confidence Score
A numerical measure of how certain an AI system is about its output.
Last reviewed by the OdysseyGPT team
What it is
A numerical measure of how certain an AI system is about its output. In OdysseyGPT, Confidence Score matters because it turns raw documents into cited outputs you can review. You don't get a black-box answer.
Key Takeaways
- A numerical measure of how certain an AI system is about its output.
- Confidence Score is most useful when accuracy must be verified against source documents.
- OdysseyGPT uses confidence score inside controlled document workflows, not just open-ended prompts.
Why it matters
A confidence score is a numerical value indicating how certain a model is about its prediction or extraction. High confidence suggests reliable output; low confidence indicates uncertainty that may warrant human review. Confidence scores make smart automation possible. High-confidence items are processed automatically, and uncertain cases go to a person. They're essential for production systems where blind trust in AI isn't appropriate.
How OdysseyGPT uses it
OdysseyGPT provides confidence indicators throughout the extraction and analysis process. When extracting data points, we indicate extraction confidence. When answering questions, we're transparent about uncertainty. Workflows can then process high-confidence items automatically and flag low-confidence cases for human review. This strikes the right balance between automation and accuracy.
Evaluation questions
What is Confidence Score?
A confidence score is a numerical value indicating how certain a model is about its prediction or extraction. High confidence suggests reliable output; low confidence indicates uncertainty that may warrant human review. Confidence scores make smart automation possible. High-confidence items are processed automatically, and uncertain cases go to a person. They're essential for production systems where blind trust in AI isn't appropriate.
Why does Confidence Score matter in enterprise document workflows?
Confidence Score matters because high-stakes teams need to find the right text, defend their answers and review the same way across large document sets.
How does OdysseyGPT use Confidence Score?
OdysseyGPT provides confidence indicators throughout the extraction and analysis process. When extracting data points, we indicate extraction confidence. When answering questions, we're transparent about uncertainty. Workflows can then process high-confidence items automatically and flag low-confidence cases for human review. This strikes the right balance between automation and accuracy.
Frequently asked questions
What is a good confidence threshold?
It depends on risk tolerance. High-stakes applications might require 95%+ confidence. Lower stakes might accept 80%. The right threshold balances automation rate against error risk.
Can confidence be miscalibrated?
Yes, models can be overconfident or underconfident. Good systems validate that stated confidence matches actual accuracy through ongoing monitoring.