This article provides a complete, practical walkthrough of the Wait Datetime Send 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 Monthly Business Performance Reports with n8n and AI: A Fully Integrated Workflow for Financial Analysis
   
   Meta Description:  
   Learn how a powerful n8n workflow combines SQL data extraction, HTML generation, and Google Gemini AI analysis to create and email automated financial performance reports for business units.
   
   Keywords:  
   n8n workflow, financial automation, budget vs actual, Google Gemini AI, MySQL reporting, business intelligence, monthly report automation, syncbricks, financial dashboard, email reporting, project WIP analysis, ERPNext automation, AI in finance, business performance analysis
   
   Third-Party APIs and Tools Used:
   
   1. Microsoft Outlook – Used to send the final HTML report via email.
   2. Google Gemini 2.5 Pro (via Langchain) – Processes HTML financial data and generates executive summary, P&L analysis, and insights using AI.
   3. LangChain ToolKit:
      - LangChain Tool Calculator – Provides precise arithmetic calculations for financial data.
      - LangChain Tool Think – Simulates deeper reasoning processes for richer AI-generated insights.
   4. MySQL – Used as a database to pull real-time financial, project, and employee data (likely from ERPNext).
   5. ERPNext (optional / inferred) – Source of the financial and HR data via MySQL tables.
   
   Article:
   
   In today's fast-paced business environment, financial decision-makers rely on timely, accurate, and actionable insights. While ERP systems can collect vast amounts of data, the challenge lies in transforming that data into useful intelligence—regularly and automatically. That's exactly what this n8n-powered automation workflow achieves—a seamless monthly email report analyzing financial performance across cost centers, powered by AI-driven analysis and real-time data extraction.
   
   Built by automation expert Amjid Ali, this n8n workflow is a brilliant example of how open-source tools, SQL logic, and artificial intelligence can come together to replace manual reporting, save time, and improve decision-making.
   
   🕐 Triggered Every Month, Automatically  
   The whole process begins with a Schedule Trigger set to run on the 5th of each month. This ensures the full prior month’s financial and operational data is available for reporting.
   
   📅 Dynamic Date Calculations  
   To ensure the data reflects the correct month and year, the “Date & Time” and “PreviousMonth” nodes dynamically calculate the previous month—even adjusting automatically for year transitions (e.g., from January to December).
   
   💼 Multi-Division Financial Intelligence  
   The system next fetches a list of cost centers (business units) that have relevant budget and accounting entries through a MySQL query. Each cost center is then individually looped over using the “SplitInBatches” node, allowing reports to be generated and sent independently for each unit.
   
   🔍 Targeted Filtering and Conditional Analysis  
   A key design feature is the “Filter” node that allows analysts to narrow the scope to a particular department, such as “AI DEPARTMENT.” This is ideal for testing, previews, or generating group-specific reports.
   
   📊 SQL-Powered Financial Analytics  
   MySQL nodes are used to extract data across four main areas:
   
   1. YTD vs Previous Month Comparison  
      This query calculates cumulative revenues and expenses year-to-date, compares them with the previous month, and shows budget vs actual variance.
   
   2. Financial Performance by Verticals  
      Within each cost center, sub-business units (called “verticals”) are analyzed for their specific income, expense, and profit figures.
   
   3. Project Status and WIP  
      Detailed project data reveals key KPIs such as contract value, actual revenue, costs, invoice percentage, and WIP (Work In Progress). These figures are important for revenue recognition in services or consulting businesses.
   
   4. Employee Headcount and HR Metrics  
      HR analytics aren't left behind—data pulled from the employee database tracks active employee count, new hires this month and year, and is later used for per-employee revenue/profit analysis.
   
   📄 Consolidated HTML Report  
   Using several code nodes (JavaScript), the data tables are converted into neat and responsive HTML reports. Four tables are merged:
   
   - Financial Overview – YTD & PM Summary  
   - Financial Overview – Vertical P&L  
   - Financial Overview – WIP Summary  
   - Employees Summary
   
   These tables are visually formatted with headings, borders, and alignment to ensure clarity and readability when emailed.
   
   🧠 AI That Thinks Like an Analyst  
   At this stage, the real magic happens. The full HTML report is passed to the “Business Performance AI Agent” powered by Google Gemini 2.5 Pro. The prompt assigned to it is structured to simulate the thinking of a seasoned financial analyst and includes specific performance metrics to calculate—such as Gross Profit, Net Profit, Profit % to Revenue, and per-employee profitability.
   
   To ensure precision, two LangChain tools—Think and Calculator—are embedded:
   
   - Calculator handles all numerical computations like gross margin percentages or variance calculations.
   - Think supports inference and reasoning to create executive summaries and contextual narratives.
   
   📩 Final Touch: Automated Email Delivery  
   Once complete, the AI-generated HTML report is cleaned, verified, and sent out via Microsoft Outlook. The subject line, recipients, and content are pre-filled using data from the workflow. This ensures stakeholders receive a polished report directly in their inbox at the same time every month—without lifting a finger.
   
   ⏳ Efficient Resource Management  
   The “Wait” node is used particularly for loop control—ensuring emails are spaced out and not sent in rapid succession when analyzing multiple divisions or departments.
   
   💡 Use Cases and Flexibility  
   Although customized for Syncbricks LLC—an AI and automation company—this workflow is adaptable for:
   
   - Startups tracking cost center performance
   - Agencies managing multiple clients or business units
   - Service companies needing project and WIP insights
   - HR leaders calculating per-employee KPIs
   - Financial controllers producing monthly board packs
   
   You can also switch data sources from MySQL to Google Sheets, CSVs, Airtable, or REST APIs by modifying the SQL query nodes.
   
   🎯 Final Thoughts  
   This automation is more than just a report generator—it’s a full-fledged business analyst in digital form. It’s a shining example of what modern no-code/low-code platforms like n8n can achieve when combined with structured data and generative AI. Companies can stop guessing and start executing based on sound, real-time financial intelligence—delivered automatically every single month.
   
   Want to build one like this or customize it to your framework? Visit Syncbricks.com or explore the tutorials and templates by Amjid Ali to get started.

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.