This article provides a complete, practical walkthrough of the Schedule Manual Automation Scheduled 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 Company Research Workflow Using n8n and AI Agents
   
   **Meta Description**  
   Build a powerful, fully-automated B2B company enrichment system with n8n, OpenAI, SerpAPI, Google Sheets, and website parsing tools. Learn how to gather data like domain info, pricing plans, and LinkedIn links using AI.
   
   **Keywords**  
   company data enrichment, AI researcher, n8n workflow, OpenAI GPT-4o, SerpAPI, ScrapingBee, B2B prospecting, automation, Google Sheets integration, website scraping, AI agents, lead enrichment
   
   **Third-Party APIs Used**  
   
   - OpenAI (GPT-4o language model)
   - SerpAPI (Google Search results)
   - ScrapingBee (Google Search via web scraping)
   - Google Sheets API (retrieve and update spreadsheet rows)
   
   ---
   
   ## Automating B2B Account Research with AI and n8n
   
   B2B sales and marketing teams know that the quality of research done on potential leads often determines conversion success. Gathering insights like company domains, LinkedIn pages, pricing plans, or whether a tool offers an API can be time-consuming when done manually.
   
   Luckily, tools like n8n—an open-source workflow automation platform—make it possible to combine the power of AI and web automation with third-party services to enrich company information effortlessly and at scale.
   
   This article walks through an n8n workflow designed to enrich company data from a Google Sheet using GPT-4-powered AI agents, web scraping tools, and dynamic search APIs—all without a line of code.
   
   ---
   
   ### 🧠 What This Workflow Does
   
   This n8n workflow automates the research process by ingesting company names or domains and returning structured company information:
   
   - Domain name  
   - LinkedIn URL  
   - B2B or B2C categorization  
   - Cheapest pricing plan  
   - Enterprise plan availability  
   - API support  
   - Existence of a free trial  
   - Top 5 integrations  
   - Most recent case study link  
   
   All this information is fed back into a Google Sheet, updating each row with the enriched data.
   
   ---
   
   ### 🔧 How the Workflow Works
   
   Below is an overview of the core steps involved:
   
   #### 1. Fetching Rows to Process  
   The workflow starts by retrieving rows from a connected Google Sheet where the enrichment status is empty or incomplete. This ensures only unprocessed rows are handled. You can trigger this manually or set it to run automatically every two hours using the Schedule Trigger.
   
   #### 2. Iterating Through Each Row  
   Rows are processed one by one using the "Loop Over Items" node to ensure each entry is handled individually and reliably.
   
   #### 3. AI-Powered Company Research  
   A key component is the OpenAI GPT-4o-powered “AI Company Researcher” agent. This is where the magic happens. The prompt provided instructs the AI to:
   
   - Locate the company's LinkedIn URL and domain  
   - Determine whether it serves B2B or B2C markets  
   - Identify pricing tiers (especially the lowest one)  
   - Confirm the existence of a free trial or enterprise plan  
   - Fetch recent case studies published by the company  
   - List up to 5 software tools the company integrates with  
   
   #### 4. Supporting Tools and Knowledge Sources  
   To boost the AI researcher’s capabilities, two additional tools are provided:
   
   - 🔎 SerpAPI – for precise Google search access  
   - 🌍 Website Scraper – a sub-workflow that visits the site, extracts the HTML content (excluding the head tag), and provides it to the AI  
   
   Alternatively, ScrapingBee can be used as a more cost-efficient method for Google search tasks.
   
   These tools act as assistants to feed structured context into the AI's reasoning process, helping it form more accurate outputs.
   
   #### 5. Parsing and Structuring Results  
   The AI’s verbose response is parsed using a Structured Output Parser that enforces a predefined JSON schema. This ensures the data fits the required Google Sheets format and remains machine-readable.
   
   #### 6. Merging & Writing Back to Google Sheets  
   Once the research data is parsed and cleaned, it’s merged with the original row data and written back into the Google Sheet. The enrichment status is also updated to “done” to prevent repeat processing.
   
   ---
   
   ### ✅ Customizable By Design
   
   One of the biggest strengths of n8n is flexibility. With just a few edits, you can modify:
   
   - The AI prompt to extract different fields  
   - The schema to accept additional values (like funding info or team size)  
   - The data destination (e.g., switch Sheets to Airtable or a CRM)
   
   Even non-technical teams can iterate on the research logic, letting them test strategies quickly and adjust based on evolving needs.
   
   ---
   
   ### 🚀 Why This Matters
   
   Most B2B companies rely on outdated, bulk-purchased datasets or slow manual research to qualify leads. This DIY enrichment engine gives you:
   
   - Up-to-date real-time data from actual web and API sources  
   - Improved targeting for outbound campaigns  
   - 10x faster research with fewer human resources  
   - Insights tailored to your specific market and business criteria  
   
   ---
   
   ### ⚙️ TL;DR — Key Features of the Workflow
   
   - Connects to Google Sheets and processes company rows
   - Uses GPT-4o to perform web research via natural language
   - Employs SerpAPI and web scraping tools to gather content for the AI agent
   - Parses results into structured JSON
   - Updates your spreadsheet with clean, enriched company data
   
   ---
   
   If you're looking for a scalable, accurate, and intelligent way to enrich company data, this n8n-based automation offers a robust starting point. Whether you're a founder doing outbound sales or a data analyst automating lead scoring, this setup can save hours of work while improving the depth of your company profiles.
   
   To get started quickly, use the pre-built Google Sheets template and integrate your own OpenAI, SerpAPI, or ScrapingBee credentials. Happy automating!
   
   ---
   
   🌐 Learn more with the official guide by Lempire: [AI Web Research with n8n](https://lempire.notion.site/AI-Web-research-with-n8n-a25aae3258d0423481a08bd102f16906)

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.