Automated document compliance validation with AI and vector database
## Description
This workflow automates compliance validation between a policy/procedure and a corresponding uploaded document. It leverages an AI agent to determine whether the content of the document aligns with the expectations outlined in the provided procedure or policy.
## How It Works
1. Document Upload
* A document (e.g., PDF) is uploaded via an HTTP Request Webhook.
* The content is processed into vector embeddings using a Qdrant vector store and an embedding model.
2. Procedure Submission
* A policy/procedure text and description are submitted via a second HTTP Request Webhook.
* These serve as the basis for evaluating the uploaded document.
3. AI-Based Validation
The AI agent receives:
* The uploaded document (via vector embeddings)
* The submitted procedure/policy text
* The description/context
It returns a structured compliance analysis including:
* Summary of Compliance (sections that align with policy)
* Summary of Non-Compliance (gaps or missing elements)
* Supporting Text Citations (document evidence)
* Confidence Level (0–100 score based on evidence quality)
## Setup Instructions
Pre-Conditions / Requirements
* An n8n instance running with access to:
* Qdrant (for vector storage)
* An embedding model (e.g., OpenAI, HuggingFace, or local model)
* Optional: Microsoft Graph or another storage system for document retrieval.
## Workflow Setup
1. HTTP Request Node 1: Document Upload
Accepts binary document files (PDF, DOCX, etc.).
Extracts text, generates embeddings, and stores them in Qdrant.
Returns a spDocumentId for reference.
2. HTTP Request Node 2: Procedure Submission
Accepts a JSON payload with:
{
"procedure": "Policy or procedure text",
"description": "Brief context or objective",
"spDocumentId": "ID of the uploaded document"
}
Links the procedure to the previously uploaded document.
3. Order of Operations
Step 1: Upload the document.
Step 2: Submit the procedure referencing the same spDocumentId.
Step 3: AI agent evaluates compliance and returns results.
## Example Input & Output
Example Input: Document Upload (Webhook 1)
* Request: Binary file upload (example_policy.pdf)
* Response:
{
"spDocumentId": "12345"
}
### Example Input: Procedure Submission (Webhook 2)
{
"procedure": "All financial records must be retained for 7 years.",
"description": "Retention policy compliance validation",
"spDocumentId": "12345"
}
### Example Output: AI Compliance Validation
{
"compliance_summary": "The document includes a 7-year retention requirement for invoices and payroll records.",
"non_compliance_summary": "No reference to retention of vendor contracts.",
"citations": [
{
"text": "Invoices will be stored for 7 years.",
"page": 4
}
],
"confidence": 87
}
