This article provides a complete, practical walkthrough of the Schedule Manual Update 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:**  
   Automating Company Enrichment with AI and Web Scraping Using n8n
   
   **Meta Description:**  
   Discover how to build an AI-powered company enrichment workflow using n8n, OpenAI, SerpAPI, and Google Sheets. Learn how it automates lead intelligence by scraping the web and updating your CRM or spreadsheet in real time.
   
   **Keywords:**  
   n8n workflow, AI enrichment, OpenAI GPT-4o, SerpAPI, Google Sheets automation, company intelligence, web scraping, B2B research, AI agents, lead enrichment, automation tools
   
   **Third-Party APIs Used:**  
   - OpenAI API (GPT-4o via LangChain)
   - SerpAPI (Google Search)
   - ScrapingBee API (alternative to SerpAPI for Google scraping)
   - Google Sheets API
   
   ---
   
   ## Automating Lead Enrichment in Real-Time with AI Web Research and n8n
   
   Lead enrichment is a cornerstone of modern sales and marketing operations, especially in the B2B space. Manually researching company details like pricing, market category, and integrations is time-consuming and error-prone. n8n, a powerful low-code automation platform, makes it possible to automate this tedious task using AI and web scraping tools.
   
   In this article, we explore a sophisticated n8n workflow that performs advanced company enrichment using GPT-4o, SerpAPI, ScrapingBee, and Google Sheets. From simply entering a company name, this workflow uncovers valuable details including pricing tiers, API availability, target market (B2B or B2C), LinkedIn URLs, and even the latest case study using AI agents.
   
   ### How the Workflow Works
   
   This automated workflow kicks off either on a schedule (every 2 hours) or manually via n8n's manual trigger node. Its primary function is to take an unstructured input—usually a company name—and return a structured, enriched dataset covering several key details.
   
   #### Step 1: Retrieve Rows to Enrich
   It starts by querying a Google Sheet containing a list of companies. It filters for rows where the "enrichment_status" field is blank or indicates that data hasn’t been populated yet.
   
   #### Step 2: AI Agent with OpenAI + Tools
   Here’s where the magic begins. An AI agent powered by OpenAI's GPT-4o is prompted with detailed instructions to research each company. The prompt guides the model to return the following:
   
   - Company LinkedIn URL
   - Domain name
   - B2B or B2C classification
   - Cheapest paid plan
   - Presence of an enterprise plan
   - Whether an API is offered
   - Free trial availability
   - The latest case study URL
   - Up to 5 integration partners
   
   The AI agent is supercharged with access to external tools:
   
   - **SerpAPI**: Runs Google queries like `"site:[company].com case study"` or `"site:[company].com pricing"` to return relevant pages.
   - **ScrapingBee**: Serves as an alternative to SerpAPI for budget-conscious teams, offering another method to Google-search websites affordably.
   - **Website Crawler Tool**: Pulls and parses the content of the company's homepage to detect mentions of APIs, product features, or pricing.
   
   #### Step 3: Structured Output Parsing
   To ensure consistency, the AI's free-form responses are parsed using a manual schema via n8n’s Structured Output Parser. This guarantees outputs are structured into standard JSON, including fields like `domain`, `market`, `cheapest_plan`, and arrays such as `integrations`.
   
   #### Step 4: Mapping and Updating Google Sheets
   Once enriched, the data is unified using a merge node and pushed back into the original Google Sheets spreadsheet. The row’s enrichment status is updated to “done” to avoid redundant processing.
   
   #### Step 5: Looping for Batch Mode
   To handle multiple records, the workflow processes companies in batches through a loop, enriching them one by one and updating the corresponding row in the spreadsheet.
   
   ### Customization and Scalability
   
   One of the biggest strengths of this workflow is its flexibility. Want to find tech stack information or CEO names instead? You can simply modify the AI prompt and update the schema inside the output parser to reflect the new structure.
   
   Furthermore, the modular design means you can swap the data storage from Google Sheets to your preferred CRM, database, or email campaign tool—making it incredibly versatile.
   
   ### Real-World Applications
   
   For founders, marketers, and sales ops professionals, this workflow becomes an automated researcher. Here are a few use cases:
   
   - Enrich cold leads with critical decision-making data (pricing, integrations, market fit).
   - Maintain a real-time feed of competitive intelligence.
   - Auto-generate property tags for segmentation in CRMs or email sequences.
   
   ### Conclusion
   
   AI-powered automation is no longer a distant dream—it’s accessible to startups and solo operators today. With n8n as the backbone, this workflow transforms company names into actionable business intelligence, combining the best of GPT-4o, Google search APIs, and real-time data entry.
   
   And the best part? You can either adapt the existing workflow for your specific needs or copy the provided Google Sheets template and plug it in instantly.
   
   🔗 Want to try it yourself? [Here’s a full guide with video walkthrough](https://lempire.notion.site/AI-Web-research-with-n8n-a25aae3258d0423481a08bd102f16906).
   
   ---
   
   This automated n8n workflow transforms mundane lead research into a scalable, intelligent system—driven by powerful AI, real-time web scraping, and seamless integrations.

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.