Core AI
What are AI Agents?
AI agents are systems that can decide and take actions toward a goal using tools and data.
Read morePlain-language definitions for the AI terms buyers ask about, with practical technical detail for implementation teams.
Core AI (10) · Workflows & Ops (8) · Buyer & Trust (7)
Core AI
AI agents are systems that can decide and take actions toward a goal using tools and data.
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Guardrails are controls that keep AI outputs and actions safe, compliant, and useful.
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Embeddings are numeric representations of meaning used for similarity search.
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A hallucination is a model output that sounds confident but is not grounded in facts.
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An LLM is a model trained on large text data to predict and generate language.
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Agentic commerce is when AI systems help complete real buying and selling tasks, not just answer questions.
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AI inference is when a trained model produces an output in production.
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Fine-tuning retrains a base model on your examples for more consistent behavior.
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Prompt engineering is designing instructions so models return useful, reliable outputs.
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RAG is a method where AI retrieves relevant documents before generating an answer.
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Webhooks are real-time event callbacks sent from one system to another.
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A KPI snapshot is a regular summary of key workflow outcomes and bottlenecks.
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An audit trail is a timestamped record of what happened, who did it, and why.
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API integration is how systems exchange data and trigger actions programmatically.
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Human-in-the-loop means people review or approve key AI decisions before final action.
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Lead routing assigns new leads to the right owner or queue based on defined rules.
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RBAC controls what users and systems can do based on assigned roles.
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Workflow automation routes tasks through defined triggers, rules, and actions.
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An A/B test compares two variants to see which performs better on a defined metric.
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Customer churn is when customers stop buying, renewing, or actively using your product.
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Data privacy protects personal information and defines how it is collected, used, and shared.
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Data retention defines how long data is stored and when it is deleted or archived.
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Model evaluation measures output quality, reliability, and business fitness before and after launch.
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AI ROI measures whether AI work creates more value than it costs.
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SOC 2 is an audit framework for controls related to security, availability, and data handling.
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