Insurance claim assessment report generation from documents

Introduction

Insurance claim assessment is a critical but time-consuming process. Your team receives documents, extracts information manually, analyses policies, writes assessments, and generates reports. Each step involves a different person, different tool, and multiple handoffs where things go wrong.

The real cost isn't just the software subscriptions; it's the friction between tools. A claims handler finishes their part, waits for the next person, who then waits for the next. Documents sit in inboxes. Context gets lost. Reports get sent back for corrections because someone misunderstood the policy details. For a medium-sized insurer processing 50 to 100 claims weekly, this inefficiency adds up to thousands of pounds in wasted time.

This workflow solves that problem. You'll connect three specialised AI tools with an orchestration platform so that documents automatically flow through assessment and into a finished report, with no manual handoffs. Upload a claim file, and within minutes, you get a structured assessment ready for human review.

The Automated Workflow

The workflow has four steps: ingest the claim documents, extract and verify policy details, analyse claim content against policy terms, and generate a formal assessment report. We'll build this using Caseguard Studio AI for document intake and policy analysis, Chat-with-PDF by Copilotus for extracting detailed information from documents, and Wordsmith AI for writing the final assessment report. The orchestration happens in n8n, which is open-source, self-hosted, and gives you full control over the process.

Why n8n over Zapier or Make?

Zapier charges per task, and at scale this gets expensive fast. Make has decent pricing but less flexibility for complex data transformations. n8n is free to self-host, so once you deploy it on your own server, your only costs are the underlying AI tools. For a company running hundreds of workflows monthly, this matters.

Architecture Overview

The workflow listens for new documents uploaded to a folder (via webhook or polling). It then:

1. Sends the document to Chat-with-PDF to extract claim details, injury descriptions, and damage assessments.
2. Sends the extracted data to Caseguard Studio AI to cross-reference against the insurance policy and flag any coverage gaps or exclusions.
3. Takes the combined output and passes it to Wordsmith AI to generate a professional assessment report.
4. Stores the final report and notifies the claims handler via email.

Step 1:

Triggering the Workflow

Most organisations want this triggered when a document lands in a specific folder. You can use cloud storage webhooks (Google Drive, Dropbox, OneDrive) or a simple file upload endpoint.

For n8n, create a webhook node that listens for POST requests:

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POST /webhook/claim-upload HTTP/1.1
Content-Type: application/json

{
  "file_url": "https://storage.example.com/claim-12345.pdf",
  "claim_id": "CLM-2024-001",
  "claimant_name": "John Smith"
}

Or use n8n's Google Drive trigger to poll every 5 minutes for new files in a designated folder. The webhook approach is faster and more efficient.

Step 2:

Extract Information with Chat-with-PDF

Once the document arrives, send it to Chat-with-PDF. This tool connects directly to PDFs and lets you ask structured questions.

In n8n, add an HTTP request node targeting the Chat-with-PDF API:

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POST https://api.chat-with-pdf.copilotus.ai/v1/documents/process
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

{
  "document_url": "https://storage.example.com/claim-12345.pdf",
  "queries": [
    "What is the nature of the claim?",
    "What date did the incident occur?",
    "What is the claimed amount?",
    "What injuries or damage are described?",
    "Are there any witness statements?"
  ]
}

The response will be structured JSON with answers to each query. Map these into variables for use in the next step:

Copy{
  "claim_nature": "Motor accident, third-party liability",
  "incident_date": "2024-01-15",
  "claimed_amount": "£8,500",
  "damage_description": "Rear-end collision, vehicle requires replacement bumper, door, and wheel arch repair",
  "witnesses": "Police report filed, witness contact details available"
}

Chat-with-PDF has rate limits (typically 100 requests per month on free tier, 1000 on paid). For production, use the paid plan at £29/month.

Step 3:

Cross-Reference with Caseguard Studio AI

Now you have the claim details. You need to match them against the policyholder's insurance policy to identify coverage limits, exclusions, and deductibles.

Caseguard Studio AI specialises in this. It ingests policy documents and claim information, then outputs a structured risk assessment.

Add another HTTP request in n8n:

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POST https://api.caseguard-studio.ai/v1/assessments/create
Authorization: Bearer YOUR_CASEGUARD_KEY
Content-Type: application/json

{
  "policy_id": "POL-2023-087654",
  "claim_id": "CLM-2024-001",
  "claim_type": "motor",
  "incident_details": {
    "date": "2024-01-15",
    "description": "Rear-end collision, third-party fault",
    "claimed_amount": 8500
  },
  "extracted_info": {
    "nature": "Motor accident, third-party liability",
    "damage": "Rear-end collision, vehicle requires replacement bumper, door, and wheel arch repair"
  }
}

Caseguard returns:

Copy{
  "assessment_id": "ASS-2024-001",
  "policy_coverage": "Comprehensive, £10,000 limit for third-party damage",
  "deductible": "£250",
  "coverage_gaps": [],
  "exclusions_flagged": [],
  "liability_status": "Third-party at fault, full coverage applies",
  "approved_claim_amount": 8250,
  "risk_score": 0.15,
  "recommendation": "Approve with standard review"
}

This assessment forms the core of your report. Caseguard charges £99/month for the starter plan (up to 500 assessments).

Step 4:

Generate the Report with Wordsmith AI

Finally, take all the structured data and generate a professional narrative report. Wordsmith AI is built for this; it takes structured inputs and writes coherent, formatted documents.

In n8n, create an HTTP request to Wordsmith:

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POST https://api.wordsmith-ai.com/v1/documents/generate
Authorization: Bearer YOUR_WORDSMITH_KEY
Content-Type: application/json

{
  "document_type": "insurance_assessment",
  "template": "claim_assessment_report",
  "variables": {
    "claim_id": "CLM-2024-001",
    "claimant_name": "John Smith",
    "incident_date": "2024-01-15",
    "policy_id": "POL-2023-087654",
    "claim_type": "motor",
    "damage_description": "Rear-end collision, vehicle requires replacement bumper, door, and wheel arch repair",
    "claimed_amount": 8500,
    "policy_coverage": "Comprehensive, £10,000 limit for third-party damage",
    "deductible": 250,
    "approved_amount": 8250,
    "liability_assessment": "Third-party at fault, full coverage applies",
    "risk_score": 0.15,
    "recommendation": "Approve with standard review",
    "assessment_date": "2024-01-16"
  },
  "output_format": "pdf"
}

Wordsmith returns a URL to the generated PDF:

Copy{
  "document_id": "DOC-2024-001",
  "document_url": "https://output.wordsmith-ai.com/documents/doc-2024-001.pdf",
  "status": "ready",
  "generated_at": "2024-01-16T10:23:45Z"
}

Download this PDF and store it in your claims management system. Wordsmith's standard plan is £49/month for up to 1000 documents.

Completing the Workflow in n8n

Your full n8n workflow looks like this:

1. Webhook trigger (waits for document upload).
2. HTTP request to Chat-with-PDF (extract claim details).
3. HTTP request to Caseguard Studio AI (assess against policy).
4. HTTP request to Wordsmith AI (generate report).
5. Move generated PDF to storage folder.
6. Send email notification to claims handler with report link.

Use n8n's "Set" nodes to map data between steps. For example, after Chat-with-PDF returns data, use a Set node to extract the key fields:

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{
  "claim_nature": "{{ $json.responses[0] }}",
  "incident_date": "{{ $json.responses[1] }}",
  "claimed_amount": "{{ $json.responses[2] }}",
  "damage_description": "{{ $json.responses[3] }}",
  "witnesses": "{{ $json.responses[4] }}"
}

Then pass these variables to Caseguard and Wordsmith.

Error handling is important. Add a Try/Catch node to handle API failures. If Chat-with-PDF times out, retry after 30 seconds. If Caseguard can't find the policy, send an alert to the claims manager instead of blocking. This keeps the workflow resilient.

Finally, add a final notification step. Use n8n's email node to send the claims handler a message:

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To: claims-handler@insurer.com
Subject: Claim Assessment Complete: CLM-2024-001
Body: 

Your claim assessment report for {{ $json.claim_id }} is ready.

Claimant: {{ $json.claimant_name }}
Claimed Amount: {{ $json.claimed_amount }}
Approved Amount: {{ $json.approved_amount }}
Risk Score: {{ $json.risk_score }}
Recommendation: {{ $json.recommendation }}

Report: {{ $json.document_url }}

Action required by: [date]

The Manual Alternative

If you prefer more granular control or want to train staff on each tool individually before automating, you can run these steps manually:

1. Open the claim document in Chat-with-PDF's web interface, ask the extraction questions, and copy the results.
2. Log into Caseguard Studio AI, upload the policy, paste the claim details, and review the assessment.
3. Copy the assessment output into Wordsmith AI, select the report template, populate fields, and generate the PDF.
4. Download the PDF, review it, and send it to the claimant.

This takes 20 to 30 minutes per claim. With automation, the same workflow completes in 2 to 3 minutes, requiring only final human sign-off. The manual approach is useful for high-value claims where human judgment is critical, but it defeats the purpose of using these tools at scale.

Pro Tips

1. Handle API Rate Limits Gracefully

Chat-with-PDF and Caseguard both have monthly quotas. Don't assume they'll accept every request. In n8n, add a conditional node that checks the response status. If you hit a rate limit, log the claim for manual processing and alert your supervisor rather than failing silently.

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IF response.status === 429
  THEN send email alert, move to manual queue
  ELSE continue to next step

2. Validate Extracted Data

Chat-with-PDF sometimes misreads dates or amounts, especially if the document is poorly scanned. After extraction, add a validation step that flags suspicious values. For example, if the claimed amount is zero or the incident date is in the future, pause and ask for human verification.

3. Cache Policy Documents

If you process multiple claims from the same policyholder on the same day, don't re-upload the policy to Caseguard each time. Store the policy ID and assessment template locally, then reuse it. This saves API calls and reduces latency.

4. Monitor Costs in Real-Time

Set up a simple spreadsheet that tracks your API usage daily. Wordsmith charges per document generated, Chat-with-PDF per query, and Caseguard per assessment. If usage spikes unexpectedly, you'll catch overruns before they hit your budget. Use n8n's built-in logging to export metrics.

5. Test with Edge Cases

Before going live, run test workflows with unusual documents: hand-written forms, images instead of PDFs, claims in multiple currencies, or policies with complex exclusion clauses. See where the tools fail and build fallback logic. This prevents surprises in production.

Cost Breakdown

At this cost, you're processing claims at roughly 40-50 pence per claim once tools are configured. Labour savings alone typically justify this investment within the first month for teams handling more than 50 claims weekly.

If you scale to 1000 claims monthly, you'll need to upgrade Chat-with-PDF to the Enterprise tier (£99/month instead of £29) and Caseguard to the Professional plan (£199/month instead of £99). Total cost would then be £346/month, roughly 35 pence per claim. Still profitable for most insurers.