Clavata.ai Glossary of Terms
Overview
This glossary provides a list of key terms used within Clavata.ai's platform. Whether you're new to the platform or need a quick reference, this guide will help you understand the essential terminology for navigating and using Clavata.ai effectively.
Accuracy: The percentage of items that were analyzed correctly by the AI. This value ranges from 0% (not accurate) to 100% (perfect Accuracy).
AI Agent: An advanced AI component within Clavata.ai that reviews and evaluates content based on your platform's Policies.
Clavata.ai: Clavata.ai is a platform designed to enhance safety in online spaces and generative AI environments. It leverages advanced AI Agents to review content with high Accuracy, helping platforms ensure secure and trustworthy interactions. Learn more.
Connecting Conditions: Used to link different Signals and Signal Lists in Policy Sections using logical operators like NOT, AND, OR, ALL, ANY, and NONE. Learn more.
Context Conditions: Define relationships between objects or concepts in specific contexts to create Rules, such as "threats" [CONCERNING] "real-world violence." Learn more.
Exact Match Conditions: Identify specific words or phrases in content, ignoring case differences (e.g., =(“cat”) identifies “cAt,” “CAT,” and “CAt”). Learn more.
EXCEPT WHEN Condition: Specifies exceptions to the Rules within a Section of your Policy. These exceptions only apply to that specific Section without affecting the overall Policy. Learn more.
False: Indicates that the content did not match any Rule in your Policy.
False Negative: Occurs when the AI fails to identify a relevant result, missing something that should have been flagged.
False Positive: Occurs when the AI incorrectly flags something as relevant when it is not.
Fuzzy Match Conditions: Used to detect variations of words or phrases, including leetspeak (e.g., ~(“hate”) detects “h4t3”). Learn more.
Label: Also referred to as a Section. A defined part of a Policy that contains one or more Rules. All Rules within a Section or Label must be met for the content to align with the Section’s or Label's logic.
Match Conditions: Specify one or more words or phrases to look for within the text. Matches can be Exact, Fuzzy, or Sentiment-based. Learn more.
Operator: Predefined functions used in Context Conditions to define relationships between Signals or objects in Rules. Operators guide how Conditions are evaluated, enabling complex Rule creation.
Policy: A Policy defines the guidelines the system follows to analyze and classify content. Policies are customizable, human-readable, and used to classify various content types.
Precision: Measures how many of the AI's predicted positive results are correct. High Precision ensures that most of the flagged results are accurate, but it may miss some relevant ones (low Recall).
Recall: Measures how many actual relevant results the AI identified. High Recall ensures that the AI captures most or all relevant results, though it may occasionally include incorrect ones.
Rule: A core logical statement in your Policy that guides how the system evaluates content. Rules set conditions that the content must either pass or fail.
Section: Also referred to as a Label. A defined part of a Policy that contains one or more Rules. All Rules within a Section or Label must be met for the content to align with the Section’s or Label's logic.
Sentiment Conditions: Analyze the overall sentiment of content to identify language such as threats (e.g., Sentiment("threatening") detects “I am going to kill you.”). Learn more.
Signal: A Signal or Signal List is a set of words, phrases, or sentiments the system searches for within your content.
Syntax: The set of rules that define how Operators, Conditions, and Signals must be structured when creating Rules. Correct Syntax allows Clavata.ai to interpret and execute Rules effectively. Learn more.
True: Indicates that the content matched a Rule in your Policy.
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