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Look up the words people use online, add the ones we missed, and help make the internet easier to understand.
5,641 definitions
The RAG Context Run is a execution instance used by AI agents and MCP clients when working with PlatPhorm News. It provides structured context so an agent can discover tools, inspect article listings, read resources, or perform safe platform actions.
The RAG Context Tool is a callable agent function used by AI agents and MCP clients when working with PlatPhorm News. It provides structured context so an agent can discover tools, inspect article listings, read resources, or perform safe platform actions.
RAG Fallback Path is a ai resilience pattern that keeps an AI feature useful when a provider or tool is unavailable for retrieval-augmented generation pipelines. It uses degraded states, deterministic responses, and operator notices so teams can avoid fake AI success while keeping evidence, reliability, and public-safe operational boundaries clear.
RAG Grounding Check is a ai quality control that verifies that generated answers are backed by available sources for retrieval-augmented generation pipelines. It uses citation checks, retrieval evidence, and contradiction detection so teams can reduce unsupported claims while keeping evidence, reliability, and public-safe operational boundaries clear.
RAG Human Approval is a ai control step that requires a person to approve sensitive or high-impact actions for retrieval-augmented generation pipelines. It uses risk scoring, review UI, and audit logs so teams can keep protected decisions accountable while keeping evidence, reliability, and public-safe operational boundaries clear.
RAG Instruction Boundary is a ai policy boundary that separates durable system instructions from user-provided content for retrieval-augmented generation pipelines. It uses role labels, precedence rules, and prompt assembly checks so teams can avoid instruction confusion while keeping evidence, reliability, and public-safe operational boundaries clear.
RAG Memory Scope is a ai state boundary that limits what an assistant may remember or reuse for retrieval-augmented generation pipelines. It uses retention policies, consent checks, and namespace separation so teams can prevent accidental cross-context leakage while keeping evidence, reliability, and public-safe operational boundaries clear.
RAG Model Router is a ai selection service that chooses the best model or provider for a task for retrieval-augmented generation pipelines. It uses cost, latency, capability, policy, and fallback signals so teams can match work to the right model while keeping evidence, reliability, and public-safe operational boundaries clear.
RAG Response Schema is a ai output contract that requires model output to match a known structure for retrieval-augmented generation pipelines. It uses JSON schemas, validators, retries, and error reporting so teams can make responses machine-readable while keeping evidence, reliability, and public-safe operational boundaries clear.
RAG Safety Filter is a ai policy control that detects content that should be blocked, rewritten, or escalated for retrieval-augmented generation pipelines. It uses classifiers, rules, and human review queues so teams can keep outputs public-safe while keeping evidence, reliability, and public-safe operational boundaries clear.