Observer replaces surveillance with intelligence. By focusing on meaningful data instead of constant, passive monitoring, it delivers more accurate results, faster reviews, and a better experience for everyone.
At the heart of Observer is an AI-powered analytical engine that transforms live testing data into real-time insights. It continuously evaluates information from the test design, test-session data, and standard proctoring inputs to understand what’s happening in every session.
Inside every Observer test session, the AI-powered Risk Analysis Management System (RAMS) continuously interprets data to identify when human review may be needed.
RAMS is the risk-analysis engine within Observer, the component that makes it more than just a monitoring tool. As each exam unfolds, RAMS analyzes risk by interpreting performance patterns across multiple streams of data. It understands how a session is progressing, identifies when behaviors fall outside an organization’s chosen risk threshold, and highlights any aberrant test session and specific behavior for real-time, human review.
This balance of smarter automation and human expertise means test security is always active but never intrusive, protecting integrity without unnecessary oversight.
Every test session produces thousands upon thousands of data points. Observer transforms them into clear, actionable insight.
Observer continuously interprets what is happening in each test session, using real-time risk analysis to detect patterns or anomalies that deserve review. When needed, it flags a clip from a session so a trained human Observer can quickly verify and decide on next steps.
Each program can configure Observer to fit its environment. This means you choose which data streams to use, how sensitive monitoring should be, and whether or not to include certain data feeds (audio, video, session data, etc.). Observer adapts to your systems, policies, and preferences.
The structure and integrity of the test itself
Live test session and interaction data
Contextual environmental data
Important note: At Caveon, we’re continually enhancing the RAMS engine to make it smarter and more adaptive. RAMS is designed to improve over time in accuracy and performance as we expand data sources and as the volume of testing data grows.
Most proctoring systems depend on webcams, shared screens, and human monitoring. These channels are limited, intrusive, and maddeningly inconsistent. Observer takes a fundamentally different approach.
Observer evaluates a broader and more meaningful range of signals, prioritizing data that directly reflects test integrity. Where other systems can only rely on what is visible, Observer can actually look at how the test is being taken.
This evidence-based approach gives testing programs a complete, objective picture of each session, while drastically reducing the need for constant oversight.
Traditional systems report what they can see. Observer starts with what actually matters.
Watching test-takers through webcams and live proctors
Understanding what the data says about how the test is being taken
Misses most real cheating, from hidden notes and phones to proxies or pre-knowledge.
Test design data and real-time testing data, signals that no other system monitors
Starts with visual inputs and treats test-taker behavior as the main indicator of misconduct
Begins with test session and test design data, incorporating video and audio as needed but with far less emphasis
Continuous human or AI review of every session
Automated, selective alerts that draw attention only when the data indicates something unusual
High intrusion; constant observation of every test-taker
Minimal intrusion; video analyzed only when relevant, most test takers are never interrupted
Fixed, one-size-fits-all setup
Fully configurable, choose your data streams, thresholds, and review levels
Reactive, inconsistent, and costly
Proactive, precise, affordable exam security
