Glossary
Real-Time Scoring
Calculating and updating AI agent trust scores immediately after each interaction rather than in periodic batch processes.
What is Real-Time Scoring?
Real-time scoring provides up-to-the-moment trust assessments that reflect an agent's current behavior. As soon as an interaction completes and generates signal data, the scoring system processes it and updates relevant trust metrics. This immediacy enables rapid response to both improvements and degradations in agent performance, making trust scores more actionable for live decision-making.
Implementing real-time scoring requires efficient data pipelines, optimized scoring algorithms, and infrastructure capable of handling high-velocity updates. The system must balance update frequency with computational cost while maintaining score stability and avoiding excessive volatility from individual interactions.
Example
A customer service agent completes a support interaction at 2:15 PM. Within seconds, the customer's satisfaction rating is processed, the agent's Quality dimension score updates from 782 to 784, and the overall trust score increases from 745 to 746, immediately visible in the system dashboard.
How Signet addresses this
Signet employs real-time scoring to ensure trust scores accurately reflect current agent state. The EMA-based scoring system weights recent interactions more heavily, and real-time processing means significant events like security incidents or quality improvements immediately impact scores.
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