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RFGP Form Generation Agent

Multi-agent AI workflow that extracts information from scattered documents and generates structured RFGP forms—reducing 20 hours of manual work to under 10 minutes.

GmailLLM
Walkthrough

Video

End-to-end view of how the workflow behaves in practice.

GitHub

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Architecture

How pieces connect

RFGP Form Generation Agent: architecture diagram — Source documents flow through intelligent extraction and multi-agent orchestration into structured RFGP forms ready for human review.

Source documents flow through intelligent extraction and multi-agent orchestration into structured RFGP forms ready for human review.

Problem

What it helps with

RFGP form generation is a tedious, document-heavy process. Teams spend up to 20 hours manually extracting information from scattered documents, organizing data, and filling out structured forms. Details get missed, formatting varies, and the process doesn't scale.

Behaviors

  • Processes source documents to extract relevant information for RFGP forms
  • Orchestrates specialized AI agents across multiple extraction and structuring steps
  • Generates detailed, structured RFGP forms from extracted data
  • Keeps humans in the loop for reviewing and approving generated outputs
  • Reduces form generation time from 20 hours to under 10 minutes
  • The same approach adapts to other document-heavy workflows: healthcare intake, loan applications, insurance claims, and compliance forms
Flow

How it works

  1. 01Source documents are ingested and prepared for processing
  2. 02Document processing agents extract relevant information from scattered source materials
  3. 03AI agent orchestration coordinates specialized agents across multiple steps to structure and organize data
  4. 04Extracted information is compiled into detailed, structured RFGP forms
  5. 05Generated forms are surfaced for human review and approval before finalization

Want this for your team?

We adapt triggers, approvals, and integrations to your environment — then ship for production discipline, not demos.

Next step

Something similar in your stack?

Tell us what systems and policies matter—we'll map a pragmatic path to a pilot.

    RFGP Form Generation Agent | Agent series | Kwanso