This article provides a complete, practical walkthrough of the Manual Stickynote 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:
   Automating AI Research with n8n: Comparing n8n and Make Using Perplexity AI
   
   Meta Description:
   Explore how to build an automated research workflow in n8n that leverages Perplexity AI. This tutorial shows you how to compare platforms like n8n and Make using real-time AI responses via the Perplexity API.
   
   Keywords:
   n8n automation, Perplexity AI workflow, compare n8n vs Make, no-code tools comparison, AI in n8n, generative AI tools, Perplexity API setup, workflow automation, low-code platforms, AI chatbot integration
   
   Third-Party APIs Used:
   - Perplexity.ai API
   
   ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯
   
   Article:
   
   Automating AI Research with n8n: Comparing n8n and Make Using Perplexity AI
   
   No-code and low-code automation tools have dramatically reshaped how individuals and teams build digital workflows. Among the leaders in this space are n8n and Make (formerly Integromat), both of which allow users to design automation pipelines with little to no traditional programming. But if you're curious about how these platforms stack up against each other and want to harness AI to gain insights, this article will show you how to use n8n and the Perplexity AI API to automate that research process.
   
   In this tutorial, we walk through a streamlined n8n workflow that sends a natural language query to Perplexity.ai’s powerful AI engine and retrieves summarized insights directly comparing the two tools—n8n and Make.
   
   🛠️ Workflow Overview
   
   This n8n workflow is set up to answer one central question: “What are the differences between n8n and Make?”
   
   Here’s how it works step by step:
   
   1. Manual Trigger Node:
      The workflow begins with a manual trigger. This is your starting point whenever you want to test or execute the flow without automation scheduling.
   
   2. Set Parameters Node:
      This node defines three key input parameters:
      - system_prompt: Sets the tone of the AI ("You are an n8n fanboy.")
      - user_prompt: The research question (Differences between n8n and Make)
      - domains: Restricts AI search sources to "n8n.io" and "make.com" to ensure content relevance and accuracy.
   
   3. Perplexity Request Node:
      This is the heart of the workflow. Here, we send a POST request to:
      https://api.perplexity.ai/chat/completions
   
      It uses the following settings:
      - Model: sonar (Perplexity’s Sonar Pro model, known for high-quality answers)
      - Temperature: 0.2 for accurate and less creative responses
      - Recency filter: Limits results to content from the past month
      - Domain filtering: Ensures output is based on trusted domains relevant to the query
      - Authenticated using API keys via HTTP Header authentication
   
      For anyone implementing this workflow, credentials must be properly configured in the n8n UI using the "Generic Credentials" option. The API key from Perplexity must be prefixed with "Bearer" as per their documentation.
   
   4. Clean Output Node:
      After receiving the raw response from Perplexity, this Set node isolates the useful output. It parses:
      - The AI-generated content from the choices[0].message.content path
      - Any citations (like supporting URLs) returned in the API response
   
   5. Sticky Notes (Documentation Tips):
      Two sticky notes are embedded in the workflow to guide setup:
      - The first provides step-by-step instructions to retrieve and insert the Perplexity API key into your credentials.
      - The second explains more about the "Sonar Pro" model with a link to Perplexity’s model documentation.
   
   🎯 Why Use Perplexity AI in Your Workflows?
   
   Perplexity AI is a leading generative AI tool designed to provide reliable and referenced responses to complex questions. Unlike standard language models that generate opinions or plausible-sounding but incorrect information, Perplexity uses actual search data verified against trustworthy sources. This makes it ideal for comparisons, product research, customer service bots, and even personalized recommendations.
   
   When integrated into n8n, it grants users:
   - Real-time, research-backed content generation
   - Control over model behavior (via system prompts and domain filtering)
   - A way to build auto-responders or knowledge bots
   
   ✨ Practical Use Cases for This Workflow
   
   - Creating a dynamic FAQ chatbot that fetches answers from curated sources
   - Comparing any two tools or services by changing the “user_prompt” and “domains”
   - Automating competitor analysis
   - Generating blog post content ideas based on authoritative sources
   
   🔒 Credentials & Security
   
   If you're new to using APIs in workflows:
   - First, visit https://www.perplexity.ai/settings/api to purchase credits and generate your API key.
   - In n8n, create a new HTTP Header Auth credential set.
     - Name: Authorization
     - Value: Bearer your_api_key_here
   
   Make sure to keep your API key safe and rotate it regularly as per best practices.
   
   🔚 Final Thoughts
   
   Using n8n as your base and integrating with an intelligent service like Perplexity AI allows you to construct sophisticated, AI-powered automation workflows without writing a single line of backend code. Whether it's comparing tools, researching trends, or analyzing product reviews, the power of automation and AI is literally at your fingertips.
   
   Try expanding this template with additional nodes—send the comparison via email, archive results in a Google Sheet, or even notify yourself on Slack when new insights are generated. The possibilities are endless, and so is the productivity boost.
   
   —
   
   Build smart, build fast—n8n and Perplexity AI are here to supercharge your workflows.

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.