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Responsible AI

Responsible AI in RAG and agentic systems refers to the implementation of technical guardrails and evaluation frameworks to ensure LLM outputs are factually grounded, unbiased, and secure. It involves a trade-off between safety and latency, as additional moderation layers (like guardrails or hallucination checks) increase the time-to-first-token.

Definition

Responsible AI in RAG and agentic systems refers to the implementation of technical guardrails and evaluation frameworks to ensure LLM outputs are factually grounded, unbiased, and secure. It involves a trade-off between safety and latency, as additional moderation layers (like guardrails or hallucination checks) increase the time-to-first-token.

Disambiguation

Focuses on technical safety layers and grounding rather than general corporate ethics.

Visual Metaphor

"A transparent security checkpoint that validates the 'passport' (source attribution) of every outgoing response and scans incoming requests for contraband."

Key Tools
NeMo GuardrailsGuardrails AITruLensRagasGiskardLangKit
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Conceptual Overview

Responsible AI in RAG and agentic systems refers to the implementation of technical guardrails and evaluation frameworks to ensure LLM outputs are factually grounded, unbiased, and secure. It involves a trade-off between safety and latency, as additional moderation layers (like guardrails or hallucination checks) increase the time-to-first-token.

Disambiguation

Focuses on technical safety layers and grounding rather than general corporate ethics.

Visual Analog

A transparent security checkpoint that validates the 'passport' (source attribution) of every outgoing response and scans incoming requests for contraband.

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