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Enterprise AI Architecture Glossary

What is Hybrid RAG?

Definition

Hybrid RAG is a sophisticated retrieval architecture that combines vector database semantic lookups with traditional structured metadata and structural graph mapping to feed the most accurate context to the LLM reasoning core.

How Memora Leverages Hybrid RAG

Memora deploys Hybrid RAG across diverse enterprise data formats, matching relational graph links with vector properties to map a complete picture of active engineering projects and team updates simultaneously, maximizing retrieval recall.

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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.

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.

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.