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This glossary explains AI terminology in simple, everyday language, organized by complexity level. We’ve focused on terms you’re most likely to encounter while reading our guides.

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Essential Terms

Essential terms you’ll encounter in our guides
A specialized AI system designed to help with tasks through natural conversation, such as when you chat with Omnifact to get help with writing an email or analyzing a document.
The question, instruction, or request you give to the AI—like when you type “Please help me summarize this report.”
The AI’s answer or output based on your prompt, such as the summary, analysis, or content the AI creates for you.
Background information that helps AI understand your request better, for example, when you explain “This is for a team meeting next week” or attach relevant documents.

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Omnifact-Specific Terms

Terms unique to the Omnifact platform
Omnifact’s automatic system that protects sensitive information by detecting and masking data like personal information, financial details, or company secrets. It also restricts images from being sent to non-EU hosted AI models for compliance. For example, if you paste an email containing employee names, they’re automatically masked before processing. Learn more →
A focused environment in Omnifact for specific topics or projects, including a dedicated knowledge base, customized AI behavior, and team access settings. For example, you might create a “Product Launch” Space with all relevant documents and team access. Learn more →
A collection of documents within a Space that the AI can reference, such as company documents, project materials, or team resources. The AI uses these to answer questions, like when it references your uploaded product documentation. Learn more →
Guidelines that tell the AI how to behave in a specific Space, controlling things like response style, specialized knowledge, and behavior patterns. For example, you might set instructions for the AI to use technical language in an engineering Space.

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Common AI Concepts

Basic AI terms
Technology that enables computers to perform tasks that typically require human intelligence, such as understanding text, answering questions, analyzing information, and generating content. For example, Omnifact understands your request and provides a helpful response.
Another word for your question or request to the AI. For example, asking “What are the sales figures for Q1?” is a query.
A task-focused automation within Omnifact that can perform specific actions, like sending data to another app or executing a workflow.
The collection of text, documents, and examples that the AI learns from in order to generate its responses.
The process where the AI generates an answer based on what it has learned without “retraining” each time you ask a question.
Teaching an AI to perform better on specific tasks by training it further on specialized data, like company-specific documents.
A method where AI combines searching external documents (retrieval) with generating new answers, improving accuracy and relevance.
A mathematical representation of text that captures its meaning, allowing AI to search and relate concepts even if different words are used.
The small delay between when you send a prompt and when the AI responds. Lower latency means faster replies.
When an AI model learns too much from training data, including noise and errors, making it less flexible or accurate with new data.
How AI systems improve their performance through experience by recognizing patterns, processing data, and getting better at tasks over time. For instance, AI gets better at understanding different ways people ask similar questions.
Everyday human language—like English, Spanish, or Mandarin—that people use to communicate. When you type or speak to Omnifact, you’re using natural language, as opposed to computer code or technical commands. AI systems are designed to understand and generate natural language so you can interact with them just like you would with another person.
The ability of AI to understand and generate human language, enabling it to process text, understand questions, generate responses, and maintain conversations. For example, you can ask questions in plain English and get coherent responses.

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Advanced Concepts

Deeper technical terms you might encounter occasionally
The type of AI system that powers Omnifact and similar assistants. These models are trained on vast amounts of text, understand and generate language, and process information contextually—enabling Omnifact to understand and respond to your requests.
How AI identifies similarities and connections in information to find relevant details, understand context, and generate responses. For example, AI recognizes that questions asked in different ways are asking for the same information.
When AI generates incorrect information that sounds plausible. This can produce misleading information, so it needs human verification and fact-checking. For example, AI might confidently state something that sounds reasonable but isn’t factually correct.

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Technical Terms Made Simple

Complex terms explained simply
A set of rules the AI follows to process information—think of it as a recipe the AI uses to complete tasks, like the steps it follows to understand your question and create a response.
A complex system that helps AI process information, similar to the AI’s “brain” for connecting different pieces of information and understanding context.
The small pieces of text that AI processes—these are the building blocks of language that AI understands, breaking down your message into processable pieces.

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Remember

You don’t need to memorize all these terms to use Omnifact effectively. This glossary is here as a reference when you encounter unfamiliar terms.

Keep It Simple

Focus on using Omnifact to help with your work - you don’t need to be an AI expert

Ask Questions

If you encounter terms you don’t understand, feel free to ask Omnifact to explain them

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Next Steps

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