This article provides a complete, practical walkthrough of the Manual Markdown Automation Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   Automated Insights: Scraping & Summarizing Indeed Company Reviews with Bright Data and Google Gemini in n8n
   
   Meta Description:
   Discover how to automate the extraction and summarization of company data from Indeed using Bright Data’s Web Unlocker and Google Gemini, all integrated through a powerful n8n workflow.
   
   Keywords:
   n8n automation, Bright Data Web Unlocker, Google Gemini, company reviews scraping, AI summarization, Indeed data extraction, LLM summarization, generative AI, HR tech automation, AI agents, Google PaLM, web scraping workflow
   
   Third-Party APIs Used:
   
   1. Bright Data Web Unlocker API
   2. Google Gemini API (PaLM large language model)
   3. Webhook.site (for testing and receiving responses)
   
   Article:
   
   Unlocking Company Insights: Automating Indeed Data Extraction & Summarization with n8n, Bright Data, and Google Gemini
   
   In today’s fast-paced digital landscape, HR professionals, recruiters, and competitive analysts often need quick, accurate, and actionable insights into company reputations and employee reviews. Platforms like Indeed are treasure troves of such data—but manually mining, cleaning, and summarizing that information is both time-consuming and inefficient.
   
   Enter the power combo of n8n, Bright Data, and Google Gemini, transforming tedious scraping and summarization processes into a single automated workflow.
   
   In this article, we explore a unique n8n workflow designed to extract employer information from Indeed using Bright Data’s Web Unlocker and generate insightful summaries powered by Google’s latest large language model (LLM)—Gemini 2.0 Flash.
   
   Overview: What This Workflow Does
   
   This n8n-based architecture performs the following key actions:
   
   - Takes a predefined company name (e.g., Starbucks) as a search query.
   - Uses Bright Data to bypass anti-bot protections and retrieve real-time Indeed content.
   - Converts raw markdown data into clean text using a custom markdown-to-text chain.
   - Employs Google Gemini for summarization and advanced formatting.
   - Sends out results via webhook for downstream consumption or alerts.
   
   Let’s break it down.
   
   Step 1: Define the Search Parameters
   
   The operation begins when the user manually triggers the workflow. An n8n Set node initializes two key variables:
   
   - search_query: The company name to search on Indeed, set to “Starbucks” by default.
   - zone: Specifies the Bright Data Web Unlocker zone used for the request.
   
   Step 2: Extract Company Data via Web Unlocker
   
   Indeed pages often employ aggressive anti-bot measures, making them challenging targets for scraping. This workflow leverages Bright Data’s Web Unlocker product/API to simulate real user access. It posts a request to Indeed’s company page and specifies that the response should return as raw markdown with a formatted layout.
   
   Step 3: Transform the Markdown into Structured Text
   
   Once received, the markdown-formatted data is sent to a “Markdown to Textual Data Extractor” node—a custom n8n LangChain integration. Backed by Google Gemini, the process converts markdown into clean, structured natural language text suitable for further processing.
   
   This step exemplifies how LLMs can dramatically simplify preprocessing tasks, replacing complex text parsers and regex-based solutions with flexible AI logic.
   
   Step 4: Summarize with Generative AI (Google Gemini)
   
   The cleaned data flows into a summarization chain powered by Google Gemini (PaLM 2.0 Flash model). The AI distills the reviews and descriptions into a concise, insightful summary that captures the essence of employee sentiment and company values.
   
   Additionally, the raw markdown is converted to HTML and sent to a predefined webhook, offering a formatted report for end-user consumption or UI rendering.
   
   Step 5: AI Expert Agent Finalizes Output
   
   Next, the data is passed to a domain-specific AI agent configured to act as an "Indeed Expert." This agent enriches and reformats the data using another instance of Google Gemini, making it presentation-ready.
   
   Once formatted, this AI-generated summary and result set gets automatically pushed to a destination webhook like Webhook.site, enabling integration with dashboards, alerting platforms, or databases.
   
   Workflow Customization & Use Cases
   
   By switching the search_query, this automation can be easily tailored to any organization listed on Indeed. The modular structure makes it a highly extensible solution for:
   
   - Recruitment teams comparing company cultures.
   - Marketing & employer branding analytics.
   - HR departments monitoring employee satisfaction trends.
   - Competitive benchmarking for business intelligence.
   
   What Makes This Workflow Powerful
   
   1. Fully Code-Free AI Integration: The integration of Google Gemini within n8n enables even non-developers to take advantage of LLM capabilities for summarization and formatting.
   
   2. Intelligent Web Scraping: Bright Data’s Web Unlocker ensures reliable access to web data from real-world sources, overcoming CAPTCHA and bot detection hurdles.
   
   3. Modular Automation: Each step—scraping, cleansing, summarizing, formatting—is modular and reusable, making workflow maintenance and upgrades easy.
   
   4. Real-Time Notifications: Targeted webhook integrations facilitate proactive pushing of results to third-party systems or frontend applications.
   
   Conclusion
   
   This n8n-based system exemplifies next-gen automation: elegant, intelligent, and driven by AI-first components. By incorporating Bright Data’s robust scraping capabilities and Google Gemini’s generative AI, this workflow drastically reduces the complexity and time required to extract, process, and utilize valuable company insights from public platforms like Indeed.
   
   It's a tangible example of how AI and automation can level up operational efficiency across HR, recruitment, and data analysis domains—no manual copy-pasting required.
   
   Feeling inspired? Fork the workflow, plug in a new company name, and start mining actionable intelligence today.
   
   — The AI Assistant for the Future of Work Automation

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.