Automate satellite data analysis and regulatory reporting with GPT-4 and Slack

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Important notice

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

1. Workflow Overview

How It Works This workflow automates satellite data processing by ingesting raw geospatial data, applying AI analysis, and submitting formatted reports to regulatory authorities. Designed for envir...

Best for

Document Extraction automation workflows
AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.scheduletrigger, n8n-nodes-base.webhook, n8n-nodes-base.set, n8n-nodes-base.merge, n8n-nodes-base.httprequest, n8n-nodes-base.code, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.

Original n8n.io source

1.1 Workflow description

Title: Automate satellite data analysis and regulatory reporting with GPT-4 and Slack
Workflow name: Automate satellite data analysis and regulatory reporting with GPT-4 and Slack

How It Works

This workflow automates satellite data processing by ingesting raw geospatial data, applying AI analysis, and submitting formatted reports to regulatory authorities. Designed for environmental agencies, research institutions, and compliance teams, it solves the challenge of manually processing large satellite datasets and preparing standardized submissions for government agencies. The system triggers on scheduled intervals or event webhooks, fetching satellite imagery and sensor data from ECC/climate APIs. Raw data flows through parsing and normalization stages, then routes to AI models for analysis—detecting environmental changes, calculating metrics, and identifying anomalies. Processed results are validated against agency specifications, formatted into SDQAR reports, and automatically stored in designated repositories. The workflow generates submission packages with required metadata, notifies stakeholders via Slack and email, and logs all activities to Google Sheets for audit trails. This eliminates hours of manual data processing, ensures compliance with submission standards, and accelerates environmental monitoring workflows.

Setup Steps

Configure ECC/climate API credentials for satellite data access
Set up webhook endpoints for event-driven data ingestion triggers
Add OpenAI API key for geospatial analysis and anomaly detection
Configure NVIDIA NIM API for specialized environmental modeling
Set Google Sheets credentials for audit logging and tracking
Connect Slack workspace and specify notification channels for submission updates
Configure Gmail OAuth for automated stakeholder notifications

Prerequisites

Active satellite data API access (ECC, NASA, ESA) with authentication credentials.

Use Cases

Automated climate monitoring with monthly regulatory submissions.

Customization

Modify AI analysis prompts for specific environmental parameters.

Benefits

Reduces satellite data processing time by 85% through end-to-end automation.

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 - Schedule Data Ingestion

Type / Role: n8n-nodes-base.scheduleTrigger - scheduleTrigger
Config choices: Version 1.3

Block 2 - Event Webhook Trigger

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

Block 3 - Workflow Configuration

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 4 - Merge Trigger Sources

Type / Role: n8n-nodes-base.merge - merge
Config choices: Version 3.2

Block 5 - Fetch EDC Clinical Data

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

Block 6 - Parse and Normalize Clinical Data

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

Block 7 - Validate Against Study Protocols

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

Block 8 - Adverse Event Detection Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3.1

Block 9 - OpenAI GPT-4 Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 10 - Structured AE Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 11 - Route by Severity

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.4

Block 12 - Enrich SAE Data

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 13 - Store SAE in Validated DB

Type / Role: n8n-nodes-base.postgres - postgres
Config choices: Version 2.6

Block 14 - Generate SUSAR Report

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3.1

Block 15 - OpenAI GPT-4 Model for Reports

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 16 - Structured Report Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 17 - Store Report in Document Repository

Type / Role: n8n-nodes-base.postgres - postgres
Config choices: Version 2.6

Block 18 - Notify Safety Team via Slack

Type / Role: n8n-nodes-base.slack - slack
Config choices: Version 2.4

Block 19 - Email QA Team

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

Block 20 - Check if Authority Submission Required

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.3

Block 21 - Prepare Authority Submission Package

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

Block 22 - Log Audit Trail

Type / Role: n8n-nodes-base.postgres - postgres
Config choices: Version 2.6

Block 23 - Sticky Note

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

Block 24 - Sticky Note1

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

Showing the first 24 of 29 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	Automate satellite data analysis and regulatory reporting with GPT-4 and Slack
Complexity	advanced
Nodes	29
Categories	Document Extraction, AI Summarization
Author	Cheng Siong Chin
Published	15 Jan 2026

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/12733/12733.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 AI Summarization workflows

Frequently asked questions

What does Automate satellite data analysis and regulatory reporting with GPT-4 and Slack 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, AI Summarization use case.

Cheng Siong Chin

203 workflows

Nodes

n8n-nodes-base.scheduletrigger n8n-nodes-base.webhook n8n-nodes-base.set n8n-nodes-base.merge n8n-nodes-base.httprequest n8n-nodes-base.code @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai

Complexity

advanced

Published 15 Jan 2026

Likes 0

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Install path: /data/workflows/12733/12733.json

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Automate satellite data analysis and regulatory reporting with GPT-4 and Slack

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

How It Works

Setup Steps

Prerequisites

Use Cases

Customization

Benefits

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Schedule Data Ingestion

Block 2 - Event Webhook Trigger

Block 3 - Workflow Configuration

Block 4 - Merge Trigger Sources

Block 5 - Fetch EDC Clinical Data

Block 6 - Parse and Normalize Clinical Data

Block 7 - Validate Against Study Protocols

Block 8 - Adverse Event Detection Agent

Block 9 - OpenAI GPT-4 Model

Block 10 - Structured AE Output Parser

Block 11 - Route by Severity

Block 12 - Enrich SAE Data

Block 13 - Store SAE in Validated DB

Block 14 - Generate SUSAR Report

Block 15 - OpenAI GPT-4 Model for Reports

Block 16 - Structured Report Output Parser

Block 17 - Store Report in Document Repository

Block 18 - Notify Safety Team via Slack

Block 19 - Email QA Team

Block 20 - Check if Authority Submission Required

Block 21 - Prepare Authority Submission Package

Block 22 - Log Audit Trail

Block 23 - Sticky Note

Block 24 - Sticky Note1

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