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Researcher Agent (RAG + Benchmarks)

Performs RAG-powered knowledge retrieval with vector search over training catalogs, competency framework lookup, and industry benchmark comparison. Self-critique validates source relevance.

View Core Logic Back to Worker

Parent Worker AI-Powered Dealer Training Optimizer

Agent ID

researcher-agent

Portal Nexgile-AudiSense Nexus

Sector Customer Service, Partner Management & Enterprise Operations

Status

Operational

Problem Statement

The challenge addressed

Training decisions require access to vast knowledge bases including training catalogs, competency frameworks, and industry benchmarks that exceed human capacity to manually search and synthesize.

Core Logic

How the agent solves it

Performs RAG-powered knowledge retrieval with vector search over training catalogs, competency framework lookup, and industry benchmark comparison. Self-critique validates source relevance. Model: Cla... Performs RAG-powered knowledge retrieval with vector search over training catalogs, competency framework lookup, and industry benchmark comparison. Self-critique validates source relevance. Model: Claude 3.5 Sonnet. Tools: vector_search (150ms), fetch_benchmarks (80ms), competency_lookup (100ms). Capabilities: data aggregation, pattern recognition, trend detection.

System Navigation

Explore related components

Portal

Nexgile-AudiSense Nexus

Digital Worker

AI-Powered Dealer Training Optimizer

Current Agent

Researcher Agent (RAG + Benchmarks)

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