This article provides a complete, practical walkthrough of the Manual Splitinbatches Automate Triggered n8n agent. It connects Manual Trigger 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 Manual Trigger, 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

• Manual Trigger

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 Conditional Workflows in n8n: A Step-by-Step Guide Using SplitInBatches and IF Nodes
   
   Meta Description: Learn how to create a dynamic, conditional loop in n8n using SplitInBatches and IF nodes to perform actions during a loop—perfect for automation tasks requiring precise control flow.
   
   Keywords: n8n workflow, automation, low-code, batch processing, conditional logic, SplitInBatches, IF node, data loop, n8n tutorial, loop control
   
   Third-Party APIs Used: None
   
   Article:
   
   Automating Conditional Logic in n8n Using Loops and the IF Node
   
   As businesses and developers increasingly turn to automation to streamline tasks and reduce human error, n8n has emerged as a powerful open-source workflow automation tool that is both flexible and user-friendly. In this article, we will walk through a basic yet illustrative workflow demonstrating how to combine loops with conditional logic in n8n—specifically using the SplitInBatches node and IF node to inject a conditional step into a controlled loop.
   
   This guide is perfect for those who want to repeat actions over items in a list with added logic for handling specific items at defined intervals or indexes. Let’s explore how it’s implemented, node-by-node.
   
   Overview of the Workflow
   
   The workflow consists of five main nodes:
   
   1. Manual Trigger
   2. Function Node
   3. SplitInBatches
   4. IF Node
   5. Set Node
   
   Let’s break each of these components down.
   
   1. Manual Trigger
   
   First, we kick off the workflow manually using the Manual Trigger node. This is particularly useful during development or testing when you want to run a workflow on-demand, without waiting for an automated trigger like a webhook or a scheduled event.
   
   Node Details:
   
   type: n8n-nodes-base.manualTrigger  
   position: Start of the workflow
   
   2. Function Node: Generating a List of Items
   
   Next, the Function node is used to generate dummy data for iteration. It creates a simple array of 10 items. Each item is an object with a single property, containing a numeric index.
   
   JavaScript code in the Function node:
   
   const newItems = [];
   
   for (let i = 0; i < 10; i++) {
     newItems.push({ json: { i } });
   }
   
   return newItems;
   
   This node essentially prepares an array that serves as our dataset for iteration. In a more realistic scenario, this could be replaced with items retrieved from an external source like an API, database, or form submission.
   
   3. SplitInBatches: Iterating Through Items
   
   The SplitInBatches node is a built-in n8n tool that lets you iterate over an array of items in manageable chunks. In this example, the batch size is set to 1, meaning it will process one item at a time. After each item is processed, the node allows the logic to "loop" through the workflow.
   
   Node Settings:
   
   - batchSize: 1
   
   This setup is particularly useful when you want to perform heavy operations one at a time, or when you want to introduce conditional logic to specific items or indices during iteration.
   
   4. IF Node: Checking Current Index
   
   This is where the conditional logic comes in. Using the IF node, the workflow checks whether the current run index (available via $node["SplitInBatches"].context["currentRunIndex"]) is equal to 5.
   
   Node Settings:
   
   - Condition: If currentRunIndex == 5
   
   If the condition is true, it proceeds to the Set node to mark this specific point in the loop. If false, the workflow loops back into the SplitInBatches node for the next item.
   
   This node is key because it allows workflows to take different paths or trigger distinct actions based on the iteration index or item values. In more advanced scenarios, this could be used to send notifications when reaching a threshold or apply some transformation to specific entries.
   
   5. Set Node: Setting a Message
   
   When the IF condition is met (i.e., at index 5), the workflow enters the Set node. This node creates a new output with a simple message—indicating that a logical event has occurred in the loop.
   
   Set Node Output:
   
   - Message: "Loop Ended"
   
   This technique can be extended to log custom events, trigger alerts, or mark significant points in data processing.
   
   Loop Continuation
   
   After executing the Set node, control flow returns back to the SplitInBatches node for any remaining items. This is achieved via one of the dual connections from the IF node—ensuring the loop continues regardless of whether the condition was met.
   
   Why This Matters
   
   This configuration is a brilliant example of just how much control n8n provides over workflows. By combining iteration (SplitInBatches) with contextual checks (IF node and runIndex), you can achieve advanced automation patterns like:
   
   - Conditional execution at specific data points
   - Dynamically terminating or modifying a loop
   - Logging or signaling events mid-loop
   - Automatically branching logic flows
   
   Conclusion
   
   This n8n workflow stands as a practical blueprint for introducing intelligent, index-based logic within data loops. Even though it processes just ten numbers in this example, the architecture scales effortlessly to real-world use cases—bulk email sending, batch data transformation, or staggered API requests.
   
   By mastering tools like SplitInBatches and IF nodes, you add an element of precision to your automation strategy, one loop at a time.
   
   Whether you're new to n8n or a seasoned low-code developer, this workflow is a foundational building block worth mastering.
   
   Ready to automate smarter?
   
   Explore, experiment, and elevate your workflows within n8n today.

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.