Document retrieval-augmented generation (RAG) agent

Purpose

Document retrieval-augmented generation (RAG) agent helps pull data from sustainability reports, internal databases, and legal documents to provide context-aware suggestions for populating specific ESRS fields.

Primary users

The primary user is not specified in the provided information. The agent is associated with the RES Team/BU and has Elsa Tossé listed as owner.

Where it fits (process/stage/trigger)

The agent fits into the ESRS field population process, especially when users need to identify relevant information from sustainability reports, internal databases, or legal documents before completing specific ESRS fields.

Key capabilities / workflow

The agent searches provided sustainability reports, internal databases, and legal documents, retrieves relevant context, checks whether sufficient context is available, and generates context-aware suggestions for specific ESRS fields.

Inputs

Inputs are not specified in detail. The provided information indicates that the agent uses sustainability reports, internal databases, and legal documents as source material.

Outputs / Deliverables

Outputs are not specified in detail. The provided use case indicates that the agent delivers context-aware suggestions for populating specific ESRS fields.

Value

The agent supports ESRS reporting work by helping users locate relevant source information and transform it into context-aware suggestions, reducing manual search effort and improving consistency when populating ESRS fields.