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January 22, 2026

GoHighLevel + OpenAI: SMS replies from your website

GoHighLevel + OpenAI: SMS replies from your website - n8n workflow automation template
Lisa Granqvist Partner Workflow Automation Expert
GoHighLevel + OpenAI: SMS replies from your website - n8n workflow automation template
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Your website already answers most customer questions. The problem is that those answers don’t show up inside your inbox when someone texts you, so your team ends up re-typing the same explanations all day.

Agency owners feel it when clients expect “instant” replies. A marketing manager feels it when leads go cold after business hours. And a small support team just gets buried. This GoHighLevel SMS AI automation turns your site into a knowledgebase that replies consistently via SMS.

You’ll learn what the workflow does, what you need to run it, and how the pieces fit together so you can trust the answers your contacts receive.

How This Automation Works

Here’s the complete workflow you’ll be setting up:

n8n Workflow Template: GoHighLevel + OpenAI: SMS replies from your website

Why This Matters: SMS Support Gets Repetitive Fast

SMS support sounds simple until you’re living in it. Someone asks about pricing, your guarantee, how scheduling works, what “included” really means, or whether you serve their area. You answer, then you answer it again, then again. Meanwhile your website updates quietly (new offers, new policies, a changed onboarding process), and your replies lag behind because nobody has time to re-train a team or rewrite canned responses every week. Honestly, the worst part is the mental load. You’re always second-guessing if your last reply still matches what the website says.

It adds up fast. Here’s where it usually breaks down.

  • Support reps end up searching your own site mid-conversation, which makes texts slow and awkward.
  • Canned snippets drift out of date, so you accidentally promise things you no longer offer.
  • After-hours messages pile up, and by morning the lead’s momentum is gone.
  • As volume grows, consistency disappears because everyone writes answers in their own style.

What You’ll Build: Website-Sourced SMS Replies in GoHighLevel

This workflow connects GoHighLevel SMS to an AI agent that “studies” your website on a schedule, then uses that content to answer questions as they come in. First, it fetches your site content (including sitemap links when available), cleans and splits the text into usable chunks, and stores it in an in-memory vector store so the AI can quickly find the right passage later. When a contact texts your GoHighLevel number, the workflow grabs the message, looks up the contact, and passes the question to the AI agent along with the most relevant website context. Finally, it sends a clear, on-brand reply back through GoHighLevel SMS. The result is support that stays aligned with live pages instead of a dusty FAQ doc.

The workflow starts with scheduled website scraping to keep the knowledgebase fresh. Next, it builds searchable embeddings so the AI can retrieve the right parts of your site. Then inbound SMS triggers a question-answer cycle, and GoHighLevel delivers the response back to the same conversation.

What You’re Building

Expected Results

Say you get 25 SMS questions a day. Manually, it’s common to spend about 5 minutes reading, searching the site, and writing a clean reply, so that’s roughly 2 hours daily. With this workflow, your “work” becomes quick oversight: maybe 10 minutes to spot-check conversations, while scraping and response generation run in the background. That’s about 1.5 hours back each day, without letting your answers go stale.

Before You Start

  • n8n instance (try n8n Cloud free)
  • Self-hosting option if you prefer (Hostinger works well)
  • GoHighLevel to receive and send SMS messages.
  • OpenAI API to generate answers from your website content.
  • Bright Data for reliable website scraping (especially on protected sites).
  • OpenAI API key (get it from your OpenAI dashboard)

Skill level: Intermediate. You’ll connect OAuth, add API keys, and test a few real SMS conversations.

Want someone to build this for you? Talk to an automation expert (free 15-minute consultation).

Step by Step

Your site gets pulled in on a schedule. A scheduled trigger runs, sets the website URL you want to use, and fetches pages via Bright Data (or HTTP requests if you adapt it for simpler sites).

Content becomes searchable knowledge. The workflow extracts the HTML body, splits long pages into smaller chunks, and builds embeddings so your content can be searched by meaning, not just keywords.

Inbound SMS triggers the AI agent. A GoHighLevel webhook receives the text, checks it’s a real inbound message, retrieves the contact, and passes the question plus relevant site context into the question-answer chain and chat model.

The reply goes back to the same conversation. The AI agent formats the final answer and the workflow sends it through GoHighLevel SMS so it lands where your team already works.

You can easily modify the scraping targets to focus on specific pages, or adjust the reply format to match your brand voice based on your needs. See the full implementation guide below for customization options.

Step-by-Step Implementation Guide

Step 1: Configure the Scheduled Trigger

Set the workflow schedule to refresh website knowledge on a recurring basis.

  1. Open Scheduled Run Trigger and set the schedule rule to run every 4 days with triggerAtHour set to {{ 12 }}.
  2. Confirm the trigger outputs to Assign Website URL as shown in the execution flow.

Step 2: Connect Website Input and Initial Crawl

Set the target website and pull the homepage HTML to extract text and links.

  1. In Assign Website URL, set website_url to https://yourwebsite.com.
  2. Open BrightData Fetcher and set url to {{ $json.website_url }}.
  3. Credential Required: Connect your brightdataApi credentials in BrightData Fetcher.
  4. In HTML Content Parser, keep operation as extractHtmlContent and ensure dataPropertyName is body.
  5. Confirm the parallel fan-out: HTML Content Parser outputs to both In-Memory Vector Store and Fetch Sitemap File and Separate Link Items in parallel.

Tip: The parallel branch ensures you both ingest homepage text and discover links at the same time.

Step 3: Build and Normalize Link Sources

Collect links from the homepage and sitemap, then normalize and de-duplicate them.

  1. In Fetch Sitemap File, set url to {{ $('Assign Website URL').item.json.website_url }}/post-sitemap.xml.
  2. From Fetch Sitemap File, ensure the XML is parsed through Parse XML File and then split with Split Sitemap Links using fieldToSplitOut set to urlset.url.
  3. In Map Link Field, set link to {{ $json.loc }} to align sitemap URLs.
  4. From Separate Link Items, ensure fieldToSplitOut is links and it outputs to Filter Link Paths.
  5. In Filter Link Paths, keep the condition to allow links that start with / or with {{ $('Assign Website URL').item.json.website_url }}.
  6. In Normalize Link URLs, set link to {{ $json.link.startsWith("/") ? $('Assign Website URL').item.json.website_url + $json.link : $json.link }}.
  7. Combine both sources in Combine Link Sources, then remove duplicates using Remove Duplicate Links.

Step 4: Crawl Pages and Insert Knowledge into the Vector Store

Iterate through unique links, fetch page HTML, and insert page text into the vector store.

  1. In Iterate Link Batches, keep the default batching options to process links sequentially.
  2. In BrightData Page Fetch, set url to {{ $json.link }} and keep format as json.
  3. Credential Required: Connect your brightdataApi credentials in BrightData Page Fetch.
  4. In HTML Body Extractor, keep operation as extractHtmlContent to capture the page body.
  5. Ensure Vector Store Inserter receives page text and is set to mode insert with memoryKey vector_db.
  6. Leave Pause Workflow connected after Vector Store Inserter so batches can resume through Iterate Link Batches.

Tip: Direct API HTTP Request and Direct API HTTP Request 2 exist for alternate BrightData API calls and can be used for debugging or future expansion.

Step 5: Set Up AI Knowledge Ingestion and Retrieval

Configure embeddings, document ingestion, and the vector store tool used by the AI agent.

  1. In Default Data Ingest, set jsonData to {{ $json.raw_text }} and keep jsonMode as expressionData.
  2. In Recursive Text Splitter, set chunkSize to 300.
  3. In In-Memory Vector Store, set mode to insert, memoryKey to vector_db, and clearStore to true.
  4. Credential Required: Connect your openAiApi credentials in OpenAI Embedding Builder (this powers embeddings for In-Memory Vector Store and Vector Store Inserter).
  5. In Vector Store Tool, set toolName to vector_db and confirm toolDescription describes your knowledge base.
  6. Credential Required: Connect your openAiApi credentials in OpenAI Embedding Builder 2 (this powers embeddings for Vector Store Tool).

⚠️ Common Pitfall: AI tool nodes like Vector Store Tool use embeddings from their connected embedding nodes—add credentials to OpenAI Embedding Builder and OpenAI Embedding Builder 2, not the tool nodes.

Step 6: Configure the SMS Webhook and Contact Lookup

Accept inbound SMS messages and retrieve the sender’s contact details.

  1. In GHL SMS Reply Webhook, keep the path set to 54259c33-52c0-4a19-97fe-3414a153f4d6 and enable POST methods.
  2. In Inbound Message Check, keep the condition leftValue {{ $json.body.type }} equals InboundMessage.
  3. In Retrieve GHL Contact, set contactId to {{ $json.body.contactId }} and operation to get.
  4. Credential Required: Connect your highLevelOAuth2Api credentials in Retrieve GHL Contact.
  5. In Apply Website URL, set website_url to https://yourwebsite.com to pass it into the AI agent.

Step 7: Configure the AI Response and SMS Dispatch

Wire the AI agent to the knowledge base and send the response back via SMS.

  1. In Conversational AI Agent, set text to {{ $('GHL SMS Reply Webhook').item.body.body }} and keep promptType as define.
  2. Ensure OpenAI Chat Engine is connected as the language model for Conversational AI Agent.
  3. Credential Required: Connect your openAiApi credentials in OpenAI Chat Engine.
  4. Confirm Redis Conversation Memory is connected to Conversational AI Agent with sessionKey set to {{ $item("0").$node["GHL SMS Reply Webhook"].json["body"]["contactId"] }}.
  5. Open Dispatch SMS via GHL and keep url as https://services.leadconnectorhq.com/conversations/messages and method as POST.
  6. In Dispatch SMS via GHL, map contactId to {{ $('GHL SMS Reply Webhook').item.json.body.contactId }}, message to {{ $json.output }}, and toNumber to {{ $('Retrieve GHL Contact').item.json.phone }}.
  7. Credential Required: Connect your highLevelOAuth2Api credentials in Dispatch SMS via GHL.

⚠️ Common Pitfall: If OpenAI Chat Engine credentials are missing, Conversational AI Agent will fail to generate a response and no SMS will be sent.

Step 8: Test and Activate Your Workflow

Validate both the scheduled crawl and inbound SMS response paths before enabling production.

  1. Use Execute Workflow to run from Scheduled Run Trigger and confirm HTML Content Parser produces raw_text and links.
  2. Check that Combine Link Sources and Remove Duplicate Links output unique URLs and that Vector Store Inserter receives page content.
  3. Send a test SMS to the GHL SMS Reply Webhook endpoint and verify Inbound Message Check passes with InboundMessage.
  4. Confirm Dispatch SMS via GHL returns a successful response and the SMS is delivered to the contact’s phone number.
  5. Activate the workflow using the Active toggle to enable the scheduled crawl and inbound SMS automation.
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Troubleshooting Tips

  • GoHighLevel OAuth credentials can expire or be missing required scopes. If replies suddenly stop, check the credential status in n8n and confirm the “conversations/message” scopes are still granted.
  • If you’re using Wait nodes or external rendering, processing times vary. Bump up the wait duration if downstream nodes fail on empty responses.
  • Bright Data scraping can fail on bot-protected pages unless Web Unlocker is configured correctly. Check your Bright Data dashboard logs first, then confirm the Authorization header is still valid in your HTTP/Bright Data credentials.
  • Default prompts in AI nodes are generic. Add your brand voice early or you’ll be editing outputs forever.

Next Steps

If your team also needs a lightweight way to respond to incoming form messages (without building a full helpdesk), Google Sheets + Gmail: smart triage for form replies pairs nicely with SMS automation, since it keeps email follow-ups organized.

For teams doing support over email and internal chat at the same time, Gmail + Slack: tickets routed fast, nothing missed helps you surface urgent issues instantly while GoHighLevel handles the quick SMS questions.

When bookings are part of the conversation and you want fewer “Did you get my confirmation?” messages, Google Calendar + Gmail confirmations, hands free is a clean add-on to keep appointments and confirmations flowing automatically.

Need your team to send consistent answers with the right attachments and files, not just text? Gmail + Google Drive: faster, consistent support replies complements this workflow by standardizing what gets sent out when people ask for docs.

Finally, if SMS conversations are also generating new opportunities, Google Sheets + Telegram: leads captured from chats is useful for logging leads from side channels so nothing gets lost outside GoHighLevel.


Quick reference:

Quick Answers

What’s the setup time for this GoHighLevel SMS AI automation?

About 1–2 hours if your GoHighLevel app and OpenAI key are ready.

Is coding required for this GoHighLevel SMS AI automation?

No. You will connect accounts, paste in API keys, and tweak a few settings in n8n.

Is n8n free to use for this GoHighLevel SMS AI workflow?

Yes. n8n has a free self-hosted option and a free trial on n8n Cloud. Cloud plans start at $20/month for higher volume. You’ll also need to factor in OpenAI API costs, which are usually a few cents per conversation depending on message length.

Where can I host n8n to run this automation?

Two options: n8n Cloud (managed, easiest setup) or self-hosting on a VPS. For self-hosting, Hostinger VPS is affordable and handles n8n well. Self-hosting gives you unlimited executions but requires basic server management.

Can I modify this GoHighLevel SMS AI workflow for different use cases?

Yes, and you probably should. You can change the Assign Website URL (Set) node to target a subdomain or a specific help center, then adjust the sitemap parsing branch to include or exclude certain paths. Many teams also edit the AI Agent instructions to enforce a shorter SMS style, add a compliance disclaimer, or route “pricing” questions to a human. If you’d rather store knowledge long-term, swap the in-memory vector store nodes for a hosted vector database like Pinecone or Supabase.

Why is my GoHighLevel connection failing in this workflow?

Usually it’s expired OAuth credentials or missing scopes on your GoHighLevel Marketplace App. Re-authenticate the HighLevel credential in n8n and confirm your app still has “conversations/message.readonly” and “conversations/message.write”. If the webhook is firing but replies aren’t sending, also check the direct HTTP request nodes for a changed endpoint or a location/sub-account mismatch.

What volume can this GoHighLevel SMS AI workflow process?

On n8n Cloud, it depends on your plan’s monthly executions; self-hosting has no execution cap beyond your server. In practice, most teams can handle dozens to a few hundred SMS conversations a day as long as your OpenAI and scraping limits are set responsibly.

Is this GoHighLevel SMS AI automation better than using Zapier or Make?

Often, yes, because this isn’t just “new SMS in, send SMS out.” You’re maintaining a living knowledgebase, scraping pages, splitting text, embedding content, and using retrieval so answers are grounded in your website. n8n handles that kind of branching logic without turning every extra step into a pricing problem. Zapier or Make can be fine if you only need a simple autoresponder, but they get clunky once you add crawling, deduping links, batching, and memory. The other big factor is control: with n8n you can self-host and keep data where you want it. If you’re on the fence, Talk to an automation expert and we’ll sanity-check your use case.

Set it up once, then let your website do the explaining in GoHighLevel. Your team can focus on the conversations that actually need a human.

Need Help Setting This Up?

Our automation experts can build and customize this workflow for your specific needs. Free 15-minute consultation—no commitment required.

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Lisa Granqvist

Workflow Automation Expert

Expert in workflow automation and no-code tools.

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