Automate legal brief generation and client cost estimates from case documents

A partner at a mid-sized law firm receives a stack of discovery documents Monday morning. By Friday, the same partner is still manually extracting facts, summarising witness statements, and drafting cost estimates to send to clients. Each brief takes three to four hours. If that firm processes twenty cases monthly, that's 60 to 80 hours of billable time spent on work that doesn't require legal judgment, just careful reading and organisation. The solution exists. You can wire together PDF analysis, cost estimation, and text refinement into a single workflow that processes case documents in minutes instead of days. Once configured, the system extracts key information, generates preliminary cost estimates based on case complexity, and produces a polished brief ready for review. No manual copying between tools. No reformatting. Just documents in, finished briefs out. This workflow combines four tools that most law firms already have or can access: a PDF dialogue system to extract facts, an estimation engine to calculate client costs, a paraphrasing tool to refine language, and an orchestration platform to connect them all. The result reduces administrative overhead by roughly 70 percent on routine documentation tasks.

The Automated Workflow

Choose n8n or Make as your orchestration platform. Both support webhook triggers, file uploads, and sequential task execution without coding. Zapier works but introduces slight delays between steps due to its task-queue architecture; n8n and Make execute steps almost simultaneously, which matters when processing large case files.

Step 1: Trigger via webhook or scheduled job

Set up a webhook in n8n or Make that accepts POST requests containing a PDF file path or direct file upload. Alternatively, schedule the workflow to run on a fixed interval (e.g. every morning) and pull case files from a designated folder in your document management system.

CopyPOST /webhook/case-processor
Content-Type: application/json { "case_id": "CASE-2025-0142", "pdf_url": "https://your-storage.s3.amazonaws.com/case_0142.pdf", "client_name": "Acme Manufacturing Inc.", "case_type": "contract_dispute"
}

Step 2: Extract content from PDF using Chat With PDF

Chat With PDF by Copilot.us accepts PDF files and queries via API. Send the case document to this service with a carefully crafted prompt that extracts key facts, dates, parties involved, and disputed claims. The system reads the entire PDF and returns structured information. Configure your n8n or Make node to call the Chat With PDF API endpoint:

CopyPOST https://api.copilot.us/chat-with-pdf/analyse
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json { "pdf_url": "https://your-storage.s3.amazonaws.com/case_0142.pdf", "query": "Extract the following in JSON format: case_parties, key_dates, disputed_claims, estimated_case_duration_months, complexity_score_1_to_10. Be precise and include only facts stated in the document."
}

The response will contain structured JSON with extracted information. Parse this output and feed it into the next steps.

Step 3: Calculate client cost estimate

With extracted case data in hand, pass the case complexity score and estimated duration to Estimatic AI. This tool generates cost estimates based on input parameters. Configure it to accept case complexity, anticipated hours, and hourly rate, then return a formatted cost breakdown. Create a Make or n8n HTTP node that posts to Estimatic:

CopyPOST https://api.estimatic.io/v1/estimates
Authorization: Bearer YOUR_ESTIMATIC_KEY
Content-Type: application/json { "project_name": "Case CASE-2025-0142 - Acme Manufacturing", "estimated_hours": 120, "hourly_rate": 250, "complexity_multiplier": 1.4, "description": "Contract dispute resolution"
}

Estimatic returns a structured estimate with labour costs, potential contingencies, and a client-ready summary. Store this as a variable in your workflow.

Step 4: Generate the initial brief

Use Claude Opus 4.6 or GPT-4.1 via their respective APIs to draft the brief. Send the extracted facts, cost estimate, and a template prompt that structures the output. This step synthesises raw information into coherent narrative and legal structure.

CopyPOST https://api.anthropic.com/v1/messages
Authorization: x-api-key YOUR_ANTHROPIC_KEY
Content-Type: application/json { "model": "claude-opus-4.6", "max_tokens": 2000, "messages": [ { "role": "user", "content": "Using the following case facts, draft a professional legal brief for client presentation. Include: Executive Summary (150 words), Facts and Background, Legal Issues, Preliminary Assessment, and Recommended Next Steps. Facts: [INSERT EXTRACTED FACTS]. Estimated cost: $[INSERT COST]. Keep language clear and avoid jargon where possible." } ]
}

Step 5: Polish with QuillBot

The draft from Claude may contain repetition or verbose passages. Pass it through QuillBot's paraphrasing API to refine tone and conciseness. Set QuillBot to "Professional" or "Formal" mode depending on your audience.

CopyPOST https://api.quillbot.com/v2/paraphrase
Authorization: Bearer YOUR_QUILLBOT_TOKEN
Content-Type: application/json { "text": "[INSERT CLAUDE BRIEF OUTPUT]", "intensity": "high", "mode": "formal"
}

Step 6: Export and notify

Save the final brief as a PDF using a PDF generation node (n8n has built-in PDF creation, or use a service like PDFKit). Store the file in your document management system and send a notification email to the handling attorney with a link to the completed brief and cost estimate. Set up a final Make or n8n node to email the output:

CopyPOST /email-send
To: attorney@yourfirm.com
Subject: Brief Ready: Case CASE-2025-0142
Body: Your case brief and client cost estimate are ready for review. [Download link]. Total processing time: 8 minutes.

The entire workflow runs in approximately 8 to 12 minutes for a typical 50-page case file.

The Manual Alternative

If your firm prefers tighter human oversight at each stage, you can break the workflow into checkpoints. After Chat With PDF extracts facts, pause and notify the handling attorney to review and approve extracted information before cost calculation proceeds. This introduces manual gates but reduces the risk of incorrect facts propagating through the brief. Use Make or n8n's "Pause and Approve" node after Step 2, requiring attorney sign-off before continuing. This increases total processing time to 2 to 4 hours but gives you control over quality at critical junctures.

Pro Tips

Prompt engineering matters most.

The quality of your Chat With PDF prompt directly determines the accuracy of extracted information.

Specify the exact JSON structure you need, list all fields explicitly, and include an instruction like "Include only facts stated in the document; do not infer." Test your prompt against five different case files before deploying to production.

Handle missing data gracefully.

If Chat With PDF cannot extract a field (e.g. estimated duration is blank), set a fallback value in your n8n or Make workflow. For instance, if complexity_score is missing, default to 5 out of 10 and alert the attorney to review manually. This prevents downstream errors in cost calculation.

Rate limits on Claude and GPT.

Anthropic and OpenAI impose rate limits depending on your account tier. If processing multiple cases simultaneously, queue requests rather than sending them in parallel. Use n8n's delay node to space requests by 2 to 3 seconds, or configure exponential backoff for failed requests.

Version your prompts.

Store your Claude and QuillBot prompts in a database or configuration file rather than hard-coding them in your workflow. This allows you to iterate on prompt quality without modifying the workflow itself. Tag versions so you can compare results over time (e.g. "Brief Prompt v2.1", "Extraction Prompt v1.3").

Validate cost estimates manually.

Estimatic AI generates estimates based on your inputs; it doesn't know your firm's actual cost structure. Review the first ten estimates generated by the workflow and adjust the hourly_rate, complexity_multiplier, or contingency factors accordingly. This calibration ensures client estimates align with your billing practices.

Cost Breakdown