Real-Time ESG Risk Monitoring Workflow: Automating with n8n and Bright Data

This is a submission for the AI Agents Challenge powered by n8n and Bright Data

What I Built

I built an AI-powered ESG Risk Monitoring workflow that helps companies safeguard against environmental, social, and governance (ESG) risks in real-time. Instead of waiting for quarterly reports or outdated assessments, the agent continuously gathers fresh signals from Bright Data's browser API for news, public disclosures, and online sources. These insights are analyzed, prioritized by severity, and automatically delivered to decision-makers via email and Jira, ensuring leadership acts before risks escalate.

Demo

n8n Workflow

Workflow Gist

Technical Implementation

System Prompt
The system instructions were carefully designed for two AI agent roles:
Risk Management Agent – Prompted to produce structured ESG risk reports.

• Extracts severity levels, identifies root causes (e.g., human rights, emissions, governance issues), and suggests next steps for compliance and mitigation.
• Ensures consistency by always outputting in JSON format, making it easier to parse and feed into reporting dashboards.

Error Management Agent – Prompted to detect workflow or parsing errors.

• If JSON output is missing or malformed, this agent summarizes the issue, creates a Jira ticket automatically, and alerts the team.
• This ensures resilience and reliability of the monitoring pipeline.

Model
OpenAI GPT-based chat model, optimized for structured outputs and concise reporting.

Memory
Stateless execution per monitoring cycle, ensuring each ESG assessment remains unbiased and not influenced by past runs.

Tools
Bright Data: Provides real-time ESG-related news and disclosures from multiple verified sources.
n8n: Orchestrates the full workflow (data extraction, AI parsing, error handling, reporting).
Gmail Node: Delivers final ESG risk summaries and alerts to stakeholders.
Jira Node: Automatically creates tickets when errors or risks exceed severity thresholds.

Bright Data Verified Node

I used Bright Data’s Browser API with the Google News resource to stream real-time ESG data directly into n8n. This ensures the pipeline captures only relevant, trusted signals — no manual curation needed. For example, in the Tesla workflow, governance controversies and emissions compliance alerts were filtered and fed into the AI model instantly.

By cutting through information overload and guaranteeing accuracy + timeliness, Bright Data solves the biggest challenge in ESG monitoring: enabling companies to act on risks as they happen.

Journey

The biggest challenge was translating noisy real-world ESG data into actionable intelligence. By experimenting with prompt design, JSON restructuring, and multi-node orchestration in n8n, I created a flow where every risk item is parsed, scored, and sent in a boardroom-ready format.

THANK YOU