Generate AI website legal and accessibility compliance reports with OpenAI, Gmail and Google Drive

Open on n8n.io

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER

Early Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Automated Legal & Accessibility Website Compliance Checker Description Automate website compliance checks in minutes using AI powered analysis. This workflow scans any website for essential legal a...

Best for

Document Extraction automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.webhook, n8n-nodes-base.httprequest, n8n-nodes-base.code, @n8n/n8n-nodes-langchain.openai, n8n-nodes-htmlcsstopdf.htmlcsstopdf, n8n-nodes-base.gmail, n8n-nodes-base.googledrive, n8n-nodes-base.stickynote

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Jitesh Dugar.

Original n8n.io source

1.1 Workflow description

Title: Generate AI website legal and accessibility compliance reports with OpenAI, Gmail and Google Drive
Workflow name: Generate AI website legal and accessibility compliance reports with OpenAI, Gmail and Google Drive

Automated Legal & Accessibility Website Compliance Checker

Description

Automate website compliance checks in minutes using AI-powered analysis. This workflow scans any website for essential legal and accessibility requirements, generates a professional compliance report, delivers it as a PDF, and stores it securely — helping teams identify risks early and stay audit-ready with zero manual effort.

What This Workflow Does

Transforms manual website compliance reviews into a single automated flow:

🌐 Capture Website Details – Accepts website URL, company name, and email via webhook.

📥 Fetch Website Content – Securely downloads and cleans website HTML for analysis.

🧠 AI Compliance Analysis – Uses AI to audit the site against key compliance standards.

📊 Scoring & Insights – Calculates an overall compliance score and highlights gaps.

📄 Generate Visual Report – Builds a detailed, easy-to-read HTML compliance report.

🖨️ Convert to PDF – Converts the report into a downloadable, shareable PDF.

📧 Email Delivery – Sends the compliance report directly to the provided email.

☁️ Secure Storage – Saves the PDF report to Google Drive for records and audits.

Key Features

🤖 AI-Powered Compliance Audits – Automatically checks privacy, cookies, accessibility, SSL, and more.

📊 Compliance Scoring – Clear numerical scores and status indicators for each section.

📄 Professional PDF Reports – Branded, structured reports suitable for clients or audits.

⚙️ End-to-End Automation – From URL submission to email delivery without manual steps.

📧 Instant Email Notifications – Reports delivered automatically to stakeholders.

☁️ Google Drive Backup – Centralized storage for compliance history and documentation.

Compliance Checks Included

✔️ Privacy Policy presence & indicators ✔️ Cookie consent mechanisms ✔️ Terms of Service availability ✔️ Accessibility (WCAG-related indicators) ✔️ Contact information visibility ✔️ SSL / HTTPS verification ✔️ Critical issues & improvement recommendations

Perfect For

🏢 Startups & SaaS Companies – Quickly assess website compliance before launch.

🧾 Agencies & Consultants – Deliver automated compliance audits to clients.

⚖️ Legal & Compliance Teams – Speed up preliminary compliance checks.

💻 Freelancers & Web Developers – Validate client websites post-deployment.

📈 Operations Teams – Maintain ongoing compliance documentation effortlessly.

What You’ll Need

Required Integrations

🌐 Webhook – Receive website URL and user details.

🤖 OpenAI – Analyze website HTML for compliance indicators.

📄 HTMLCSS to PDF – Convert compliance report into a PDF.

📧 Gmail – Send compliance report via email.

☁️ Google Drive – Store generated compliance reports.

🌍 HTTP Request – Fetch website HTML content (no authentication required).

Optional Enhancements

📊 Compliance Dashboard – Connect Google Drive or logs to Looker Studio.

🌍 Multi-Website Scans – Extend webhook to accept bulk URLs.

🕒 Scheduled Scans – Run periodic compliance checks automatically.

📨 Slack Alerts – Send compliance summaries to internal channels.

📝 Custom Branding – Adjust HTML styling, logos, and colors.

Quick Start

1️⃣ Import the workflow JSON into your n8n workspace. 2️⃣ Activate the webhook and copy the endpoint URL. 3️⃣ Connect OpenAI, Gmail, Google Drive, and HTMLCSS to PDF credentials. 4️⃣ Send a POST request with website URL, company name, and email. 5️⃣ Review the emailed PDF compliance report. 6️⃣ Check Google Drive for stored audit copies. 7️⃣ Activate the workflow for production use.

Expected Results

⚡ Minutes Instead of Hours – Instant compliance assessments.

🤖 AI Accuracy – Consistent, structured compliance analysis.

📈 Risk Visibility – Early detection of legal and accessibility gaps.

📄 Audit-Ready Reports – Clean, shareable documentation.

☁️ Centralized Storage – Every scan archived automatically.

Workflow Structure

🌐 Webhook Trigger ↓ 📥 Fetch Website HTML ↓ 🧹 Clean & Prepare Content ↓ 🧠 AI Compliance Analysis ↓ 📊 Parse Results ↓ 📄 Generate HTML Report ↓ 🖨️ Convert to PDF ↓ 📧 Email Report ↓ ☁️ Save to Google Drive

Ready to Automate Website Compliance?

Import this template and turn any website URL into a complete compliance report — automatically, consistently, and professionally. Perfect for audits, clients, and peace of mind. ✅

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Webhook

Type / Role: n8n-nodes-base.webhook - webhook
Config choices: Version 2.1

Block 2 - Fetch Website HTML

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.3

Block 3 - Extract & Clean HTML

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 4 - Analyze Compliance

Type / Role: @n8n/n8n-nodes-langchain.openAi - openAi
Config choices: Version 2.1

Block 5 - Parse Compliance Results

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 6 - Generate HTML Report

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 7 - HTML to PDF

Type / Role: n8n-nodes-htmlcsstopdf.htmlcsstopdf - htmlcsstopdf
Config choices: Version 1

Block 8 - Send Compliance Report

Type / Role: n8n-nodes-base.gmail - gmail
Config choices: Version 2.2

Block 9 - Save to Google Drive

Type / Role: n8n-nodes-base.googleDrive - googleDrive
Config choices: Version 3

Block 10 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 11 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 12 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 13 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 14 - Sticky Note5

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Generate AI website legal and accessibility compliance reports with OpenAI, Gmail and Google Drive
Complexity	intermediate
Nodes	14
Categories	Document Extraction
Author	Jitesh Dugar
Published	12 Dec 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/11747/11747.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Document Extraction workflows

Frequently asked questions

What does Generate AI website legal and accessibility compliance reports with OpenAI, Gmail and Google Drive do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Document Extraction use case.

Jitesh Dugar

133 workflows

Nodes

n8n-nodes-base.webhook n8n-nodes-base.httprequest n8n-nodes-base.code @n8n/n8n-nodes-langchain.openai n8n-nodes-htmlcsstopdf.htmlcsstopdf n8n-nodes-base.gmail n8n-nodes-base.googledrive n8n-nodes-base.stickynote

Complexity

intermediate

Published 12 Dec 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/11747/11747.json

Share Your Workflow

Have a useful automation to share? Publish it and help the community.

Submit Your Template How to Submit

Related Workflows

Detect semantic duplicate website pages with Google Drive, Postgres and Ollama

## Quick overview This workflow scans HTML files in a Google Drive folder, extracts and stores page text in Postgres, generates local vector embeddings with Ollama, and uses PGVector similarity searches to produce CSV reports that flag semantically duplicate website pages. ## How it works 1. Starts manually and clears the existing PGVector embeddings table and the scraped page text table in Postgres. 2. Lists files in a specified Google Drive folder, filters to the target documents, and processes them in batches. 3. Downloads each HTML file from Google Drive, extracts the main body text, cleans it, and upserts the results into a Postgres table for scraped pages. 4. Reads the scraped page text back from Postgres in batches, splits it into overlapping chunks, and attaches page metadata (sheet_id, file_name, file_url) to each chunk. 5. Generates embeddings locally with Ollama and inserts the chunk vectors and metadata into Postgres (PGVector), deduplicating already-processed pages. 6. Builds an HNSW index in Postgres, computes chunk-to-chunk similarity matches and a pairwise page report, and exports the results as a CSV file. 7. Computes page-level centroid embeddings, finds highly similar page pairs, and exports a page-level duplicate report as a CSV file. ## Setup 1. Add Google Drive OAuth2 credentials and set the Google Drive folder URL/ID used to scan for your HTML files. 2. Add Postgres credentials for a database with the pgvector extension enabled and permissions to create/alter tables and indexes (including HNSW indexes). 3. Add an Ollama credential and ensure the embedding model mxbai-embed-large:latest is available on your Ollama instance. 4. Confirm your source files are HTML documents and that the workflow’s text extraction and similarity thresholds match your content and desired duplicate sensitivity. ## Requirements - Working instance of n8n, either self-hosted or on the cloud. Remember, this workflow can be computationally expensive. - Google Drive API (with OAuth setup in n8n credentials section) - Ollama (for open source models) or any Embedding model API - PostgreSQL with PGVector or any other vector database - PgAdmin (for PostgreSQL) or your interface to access database tables via SQL for troubleshooting (optional). ## Additional info Limitations and Enhancements: Physical system memory mxbai-embed-large Running through Ollama is free and private, but the embedding generation speed depends entirely on your hardware. The more system memory you have, the more data you can process in batches in the loop node. Similarity threshold and boilerplate content The cosine distance used in this workflow is 0.15 for chunk-level matching. And 0.05 (similarity above 95%) of the threshold is used for page-level centroid matching. This is only the starting point. Once you have the data, and especially if your data has more noise, you might need to tweak these thresholds for better matching. This workflow needs HTML files to extract text This workflow doesn't crawl a website or fetch pages by entering a URL. You need to download HTML files (rendered or source) for consumption. Use parallel processing and Cloud APIs Two sub-processes take the most time: Downloading HTML files from Google Drive Creating vector embeddings If you can use parallel processing in n8n and execute these sub-processes in parallel, the process will be done much faster. Additionally, if you can use cloud APIs for embedding, it may save some you some processing time as well. Use efficient SQL queries Since I am from a non-tech background and not a coder, I used a mix of Gemini, Perplexity and Claude to create SQL codes for this workflow. If you're better at it, you can run computationally efficient queries that would help you achieve better results with less computation expense and time.

View

Generate monthly BigQuery KPI PDF reports with Claude, Google Docs, Outlook and Teams

## Quick overview This workflow runs monthly to query KPI data from Google BigQuery, generates a narrative with Anthropic Claude, fills a Google Docs report template, exports it as a PDF, archives it to OneDrive, emails it via Microsoft Outlook, and posts a summary to Microsoft Teams. ## How it works 1. A schedule trigger fires on the 1st of every month at 07:00 and calculates the start and end dates of the previous full calendar month. 2. Four parallel BigQuery queries fetch revenue KPIs, top product categories, weekly sales trend, and top customers for that period. Each result set is tagged with a source label before merging. 3. All tagged rows are combined and aggregated into a single structured report payload containing KPI summaries, ranked tables, and company metadata. 4. The payload is split across two concurrent branches: one sends it to a Claude Sonnet LLM chain to generate an executive narrative with five sections (summary, revenue analysis, category insights, customer insights, and recommendation), and the other creates a named copy of a Google Docs template in your reports folder. 5. Once both branches complete, the narrative is merged into the report payload and the replacement requests for all template placeholders are constructed. 6. The Google Docs node applies all replacements in a single batchUpdate call, then the file is exported as a PDF via Google Drive. 7. The finished PDF is archived to OneDrive, emailed via Outlook with the report attached, and a formatted KPI summary card is posted to a Microsoft Teams channel. ## Setup 1. Set the following n8n environment variables before activating: GCP_PROJECT_ID, BQ_DATASET, GDOCS_TEMPLATE_FILE_ID, GDRIVE_REPORTS_FOLDER_ID, ONEDRIVE_REPORTS_FOLDER_ID, REPORT_RECIPIENTS, TEAMS_TEAM_ID, and TEAMS_CHANNEL_ID. 2. Connect a Google BigQuery credential and update the four SQL queries to match your dataset, table name, and column names. 3. Connect an Anthropic API credential to the Claude Chat Model sub-node, then manually wire its output to the ai_languageModel input (bottom connector) of the Create AI Narrative with Claude node on the canvas. 4. Connect Google Drive and Google Docs OAuth2 credentials. In Google Drive, create a master report template Doc containing the placeholder strings listed in the Customization section, note its file ID from the URL, and set GDOCS_TEMPLATE_FILE_ID accordingly. 5. Connect Microsoft OneDrive, Outlook, and Teams OAuth2 credentials. Retrieve your Teams team ID and channel ID using the Microsoft Graph Explorer and set the corresponding environment variables. ## Requirements - Google Cloud project with BigQuery enabled and an orders table matching the SQL schema in the workflow - Google Workspace account (Drive and Docs OAuth2 access) - Anthropic API key - Microsoft 365 account with OneDrive, Outlook, and Teams access ## Customization - To change the reporting cadence, update the cron expression in the schedule trigger: 0 7 * * 1 for weekly or 0 7 * * * for daily. - To adapt the SQL queries to your schema, replace orders, order_total, customer_id, is_new_customer, created_at, and product_category with your actual column names. - To change the AI model, update the model field in the Claude Chat Model sub-node. - To add more KPI sections, extend the SQL queries, the aggregation code in Consolidate BigQuery Data, and the replacements array in Construct Replacement Requests.

View

Ingest and search Cloudflare R2 media with Gemini, Groq Whisper, and Supabase

## Quick overview This workflow ingests images, PDFs, and videos from a Cloudflare R2 folder, uses Google Gemini to view pdfs, images and videos, Groq stt (Whisper) for video transcriptst - to generate searchable descriptions and tags, stores embeddings in a Supabase pgvector table. ## How it works 1. Receives a webhook request containing a Cloudflare R2 bucket and folder URL, then lists the objects in that folder. 2. Filters to supported file types, builds public CDN URLs and timestamps, and routes each item as an image, PDF, or video. 3. For images, calls Google Gemini with the image URL to generate structured metadata (summary, detailed description, tags, and scores). 4. For PDFs, calls Google Gemini to analyze the document URL and return the same structured metadata. 5. For videos, downloads each file locally, extracts representative frames with FFmpeg for Google Gemini visual analysis, extracts audio, transcribes it with Groq Whisper, and tags transcript chunks with Groq Llama. 6. Normalizes results into a single text “content” field plus JSON metadata, generates Google Gemini embeddings, and inserts the vectors into Supabase (pgvector). 7. Receives a separate webhook query, retrieves the most similar items from Supabase using embeddings, and returns ranked matches in the webhook response. ## Setup 1. Create a Cloudflare R2 bucket with publicly accessible object URLs, and add Cloudflare R2 credentials in n8n. 2. Set up a Supabase project with pgvector enabled and a table named `vec10`, then add Supabase credentials in n8n. 3. Add Google Gemini credentials (Google PaLM/Gemini API) for embeddings and provide an HTTP Header Auth credential for the Gemini HTTP requests. 4. Set the `GROQ_API_KEY` environment variable for the Groq Whisper transcription and Llama tag extraction calls. 5. If you enable video processing, install `curl`, `ffmpeg`, and `ffprobe` on the n8n host and update the local directory paths (temp root, frames directory, and video directory) in the workflow inputs. 6. Copy the ingest webhook (`/vector-ingest`) and query webhook (`/vector-query`) URLs and configure your upstream app to send the expected JSON payloads. ## Additional info Video: FFmpeg code nodes cut videos smartly into "video_frames" items and "video_transcripts" for easy handling and pgvector storage. Exposed webhook to vector query flow allows Voice Agent to find and display the full video, pulled from Cloudflare bucket, by the referenced matching video_frames or video_transcripts returned from vector query.

View

Need Custom Automation?

Get help designing a custom n8n workflow that connects your stack and fits your process.

Generate AI website legal and accessibility compliance reports with OpenAI, Gmail and Google Drive

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Automated Legal & Accessibility Website Compliance Checker

Description

What This Workflow Does

Key Features

Compliance Checks Included

Perfect For

What You’ll Need

Required Integrations

Optional Enhancements

Quick Start

Expected Results

Workflow Structure

Ready to Automate Website Compliance?

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Webhook

Block 2 - Fetch Website HTML

Block 3 - Extract & Clean HTML

Block 4 - Analyze Compliance

Block 5 - Parse Compliance Results

Block 6 - Generate HTML Report

Block 7 - HTML to PDF

Block 8 - Send Compliance Report

Block 9 - Save to Google Drive

Block 10 - Sticky Note

Block 11 - Sticky Note2

Block 12 - Sticky Note3

Block 13 - Sticky Note4

Block 14 - Sticky Note5

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions