AI Agent Enterprise Document Intelligence Example

Retrieval Agent

Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation.

View Core Logic Back to Worker

Parent Worker Enterprise Document Intelligence

Agent ID

retrieval_agent

Portal Nexgile-TradeNexus

Sector Value-Added Distribution (VAD) & IT Wholesale

Status

Illustrative

Problem Statement

The challenge addressed

Finding relevant information across large document corpora requires semantic understanding that goes beyond keyword matching while maintaining precision.

Core Logic

How the agent solves it

Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Generates query embeddings using text-embedding-3-large. Executes hybrid... Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Generates query embeddings using text-embedding-3-large. Executes hybrid search combining vector similarity (cosine) with BM25 lexical matching. Applies cross-encoder reranking for precision. Uses MMR (Maximal Marginal Relevance) for diversity. Assembles optimized context windows within token limits. Reports retrieval metrics (chunks searched, similarity scores, retrieval time).

System Navigation

Explore related components

Portal

Nexgile-TradeNexus

Digital Worker

Enterprise Document Intelligence

Current Agent

Retrieval Agent

Here

Retrieval Agent

Problem Statement

Core Logic

System Navigation

Portal

Digital Worker

Current Agent

Global Headquarters

Global Capability Center