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Enterprise AI Architecture Glossary

What is Agentic RAG?

Definition

Agentic RAG is an intelligent retrieval setup where autonomous AI agents manage the search query step, evaluate retrieved text relevance, iterate on missing search terms, and self-correct data inputs dynamically.

How Memora Leverages Agentic RAG

Memora drives multi-source searches using Agentic RAG. If the initial database lookup returns incomplete information, the system agent automatically rewrites search queries and interrogates alternate historical channels to complete the context.

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Agentic AI represents an advanced operational paradigm where artificial intelligence models operate as semi-autonomous or fully autonomous software agents. These systems feature intrinsic planning capabilities, dynamic goal optimization, loop self-correction, and structural tool orchestration, allowing them to independently manage multi-step, complex corporate workflows over long horizons without requiring continuous human oversight or iterative instructions.

An AI Agent is an autonomous operational software entity driven by large cognitive reasoning models that can perceive its corporate environment, maintain memory states, make logical decisions, design step-by-step action paths, and invoke external APIs or software tools to execute specific business goals with minimal human intervention.

AI Alignment is the technical discipline of configuring, tuning, and structuring machine learning models to ensure their generated answers, reasoning processes, and behavioral outputs closely match intended human values, safety definitions, and strict corporate execution rules.

An AI Assistant is a context-aware conversational software interface designed to help enterprise workforces discover information, summarize data, configure administrative tasks, and manage day-to-day software operations using standard, natural human language.

AI Automation refers to the end-to-end replacement or optimization of highly repetitive, human-intensive administrative tasks, document management routines, and knowledge cataloging workflows through the deployment of autonomous cognitive algorithms and model tools.