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HighLevel Public API v3 is officially released. HighLevel has officially released v3 of its Public APIs, announced by co-founder Shaun Clark. v3 builds on the existing API versioning foundation with a more consistent endpoint architecture, better performance, and advanced capabilities for complex workflows, while your existing integrations keep running exactly as they do today. What's new in HighLevel API v3? * v3 API endpoints: a new generation of endpoints designed for performance, long-term scalability, and richer data functionality. * Unified structure: a more predictable, standardized endpoint and payload schema that simplifies building advanced, data-heavy workflows. * Dedicated v3 documentation: full schemas, reference guides, and a v3-specific changelog are live. * Seamless version switcher: select v3 directly from the version dropdown in the developer portal to view the updated documentation. Is v3 backward compatible? Yes. HighLevel emphasizes zero disruption to live apps: your existing date-based API configurations remain fully functional, completely accessible, and fully documented. Nothing changes for current implementations, so your team can explore and adopt v3 on its own timeline. How to use HighLevel API v3. * Open the Public API Documentation. * Locate the Version Switcher dropdown at the top of the interface. * Select v3 to view the new endpoints, schemas, and technical references. * Build, test, and deploy. What this means going forward. HighLevel says all new feature endpoints and non-breaking API enhancements will be added exclusively to the v3 framework as it expands core coverage. If you build or maintain GHL integrations, plan new work against v3, while existing date-based apps need no immediate change. Frequently asked questions. Does HighLevel API v3 break existing integrations? How do I switch to HighLevel API v3? Where will new HighLevel endpoints be added? Is there documentation for API v3?

SimpleTalk AI agent + GoHighLevel: complete setup guide for Voice AI calls. SimpleTalk is one of the leading AI voice agent platforms, and it integrates directly with GoHighLevel to power both inbound and outbound AI calling that qualifies leads, books appointments, and handles follow-ups automatically. At GHL Prime, Ghlprime has deployed SimpleTalk AI agents across home services, real estate, and healthcare clients - and the results have been hard to ignore. This guide walks you through everything: connecting SimpleTalk to GoHighLevel, building your first agent, writing a conversation script that actually converts, and triggering outbound calls straight from your GHL workflows. What is simpletalk and how does it work with GHL? SimpleTalk is an AI voice platform that makes and receives phone calls using natural, human-sounding voices. Instead of a clunky IVR menu, your contacts have a real conversation - and the AI knows how to qualify, book, and route based on what they say. The integration loop with GoHighLevel is straightforward: * A GHL workflow triggers SimpleTalk - either through the native action or a webhook. * SimpleTalk calls the contact using your scripted agent. * The call produces outcome data - answered, voicemail, qualified, or booked - which is sent back to GHL. * GHL continues the automation based on that outcome: applying a tag, moving the contact in a pipeline, or firing an SMS. That closed loop is what makes SimpleTalk GoHighLevel deployments so powerful - the AI does the talking, and GHL handles everything before and after. SimpleTalk vs GHL Native Voice AI - which should you use? GoHighLevel now ships with its own Voice AI, so the obvious question is whether you even need SimpleTalk. Here is the honest breakdown. | Feature | GHL Native Voice AI | SimpleTalk | | Setup | Built in, simple | Separate platform via integration/webhook | | Inbound answering | Yes (basic) | Yes (full) | | Outbound from workflows | No | Yes | | Conversation flow control | Limited customisation | Full flow builder | | Outcome data back to GHL | Minimal | Rich (qualified, booked, voicemail, etc.) | | Best for | Small/simple after-hours answering | Agencies, high volume, complex flows | Its verdict: use SimpleTalk for serious agency deployments where you need outbound calling, branching conversation logic, and detailed outcome tracking. Stick with GHL native Voice AI if all you need is simple after-hours call answering for a single small business. Step 1 - create your SimpleTalk account and connect to GHL. * Sign up at simpletalk.ai and verify your account. * Go to Integrations > GoHighLevel. * Click connect and complete the OAuth authorize flow when GHL prompts you. * Select the sub-account (location) you want SimpleTalk to operate in. * Run a test connection to confirm the link is live before building anything. Always connect at the sub-account level so each client stays isolated - a habit every GHL agency should keep. Step 2 - create your first AI agent in simpletalk. Inside SimpleTalk, click New Agent and configure the basics: * Name the agent (e.g. "Sarah - Inbound Receptionist"). * Choose a natural voice - pick one that matches your brand and avoids the robotic feel. * Set the language and timezone so calls happen at the right local hours. * Select the agent type: Inbound (answers calls) or Outbound (places calls). * Assign a phone number for the agent to call from or receive on. Step 3 - write your agent's conversation script. SimpleTalk uses a visual flow builder made of conversation nodes. A reliable structure looks like this: * Opening node: "Hi, this is [Agent Name] calling from [Business Name]. Am I speaking with [First Name]?" - if yes, move to qualification; if no, apologise and end politely. * Qualification node (max 3 questions): the service needed, the area/location, and the timeline - within a week or two versus a future project. * Booking node: "I'd love to get you booked in with our team. Do you have a few minutes to pick a time?" - if yes, transfer or book; if no, send the booking link. * Fallback node: "No problem - let me have one of our team call you back within the hour." Here is a sample home-services script Ghlprime deploy for clients: Opening: "Hi, this is Sarah from Apex Plumbing. Am I speaking with John?" Qualify: "Great - what kind of plumbing issue are you dealing with?... And which suburb are you in?... Is this something you need sorted in the next week or two, or further down the track?" Book: "Perfect, John. I'd love to get you booked in with one of our plumbers. Do you have a couple of minutes to pick a time that works?" Fallback: "All good - I'll have one of our team give you a quick call back within the hour to lock it in." Step 4 - trigger simpletalk calls from GHL workflows. There are two ways to fire a SimpleTalk call from GoHighLevel. Method 1 - Native action. In your GHL workflow, choose Add Action > SimpleTalk > Make Call, select the agent, and map the contact's phone number field. Done - no code required. Method 2 - Webhook. Add a webhook action that sends a POST to your SimpleTalk webhook URL with the contact details: POST https://api.simpletalk.ai/v1/calls Content-Type: application/json {"phone": "{{contact.phone}}", "name": "{{contact.first_name}}", "agent_id": "agt_8f2a9c41"} When to trigger calls: * New lead: call immediately while intent is hot. * Cold lead at 3 days: re-engagement call. * 24 hours before an appointment: a confirmation reminder. * 2 hours after service: a follow-up and review request. Step 5 - send call outcomes back to GHL. This step is what separates a gimmick from a real system. Configure your SimpleTalk webhook to POST call results back into GHL and map each outcome to an action: * Answered + qualified: tag simpletalk-qualified and move the contact into the Qualified pipeline stage. * Not interested: tag the contact and remove them from active sequences. * Voicemail: tag voicemail-left and fire an SMS follow-up. * No answer: schedule an automatic callback in 2 hours. With outcomes flowing back, your SimpleTalk GHL integration becomes a self-managing lead engine. Real results from SimpleTalk + GHL deployments. * Home services: 40% of inbound calls were qualified and booked entirely by the AI agent, no human touch. * Real estate: an outbound campaign to 300 cold leads hit an 18% answer rate and converted 11% into booked appointments. * Healthcare: after-hours coverage handled 100% of calls with zero missed - every patient reached a real conversation. Common SimpleTalk Setup mistakes. * No fallback node - calls go silent when the contact says something unexpected. Always build the catch-all. * A robotic voice - pick a natural voice or hang-ups spike in the first ten seconds. * Not mapping outcomes back - without webhook results, GHL has no idea what happened on the call. * Wrong calling hours - set a sensible window like 9am to 7pm local time to avoid annoyed prospects and compliance issues. * Not A/B testing opening lines - small tweaks to the first sentence move answer and continuation rates more than anything else. SimpleTalk pricing - what to expect. Pricing changes over time, so always check simpletalk.ai for current rates. Generally you can expect a per-minute call charge plus a platform fee. If you are running high volume, it is worth negotiating a custom plan - providers are usually flexible at scale. At GHL Prime, Ghlprime include full SimpleTalk setup and conversation scripting as part of its Voice AI packages, so you are not left wiring webhooks alone. Want a SimpleTalk AI agent built and integrated? GHL Prime handles the full setup - agent creation, call scripting, GHL workflow integration, and outcome tracking. Ready in under a week. Need help implementing this in GoHighLevel? Its team builds, automates, and scales GoHighLevel systems for agencies every day. Book a free call and Ghlprime'll map out exactly what to ship next.

GoHighLevel Workflow Automation: new AI Agent. GoHighLevel workflow automation just changed: the new AI Agent action hands a trigger to an AI that tags, enriches, and replies from one prompt. Here's what it really automates - and what still needs a human. By Arcytex · GoHighLevel, Workflow Automation, AI Agents, CRM, Lead Follow-Up GoHighLevel's new AI Agent action turns gohighlevel workflow automation from a list of steps you build by hand into a single prompt you hand to an AI agent. A lead fills out a form, and the agent tags them, creates the opportunity, and replies on its own. It handles the repeatable 80% - the edge cases still need you. This post distills Nuno Tavares's video, This New GoHighLevel Feature Automates Everything For You. What is GoHighLevel's new AI Agent workflow action? It's a new step you can drop into any GoHighLevel workflow that hands the job to an AI agent instead of a chain of "if this, then that" actions. You give it a prompt describing what you want done, and the agent decides the steps and runs them. Here's the diff. The old way: a trigger fires, then you build every action by hand - add tag, create opportunity, send SMS, send email, wait, branch. The new way: a trigger fires, and you divert it to an AI agent with a prompt. The agent reads the contact, figures out what to do, and does it. It lives under Automations. Build a workflow, add your trigger, hit the plus, scroll down to AI Agent. It's still in beta, so treat it as powerful but not set-and-forget. How is this different from normal GoHighLevel automation? A normal automation is deterministic. You define every branch, so it does exactly what you built - no more, no less. That's great for predictable steps and terrible for anything that needs judgment. The AI Agent is the opposite. You describe the goal in plain language and let it reason through the specifics for each contact. In the video, a form submission triggers an agent that thanks the lead, tags them, enriches the record, checks for an existing opportunity, creates one if needed, generates a booking link, and sends a personalized text and email - all from one prompt. "Instead of you creating an AI automation that's going to have a bunch of steps, you now can just divert it to an agent and the agent will take care of everything afterwards." The trade-off is control. Deterministic workflows are boring and reliable. Agents are flexible and, because they reason each time, a little less predictable. You want the agent where personalization matters, and plain automation where the steps never change. What can the AI Agent actually do? When you add the action, GoHighLevel drops in a library of pre-built agent templates so you're not starting from a blank prompt. The ones shown in the video include: * Form lead follow-up * No-show appointment recovery * Facebook lead nurturing * Stale deal nudge * Research and enrich new contacts * Enrich and confirm new appointments * Quiz lead scoring and routing * Call transcript summary and action items * Instagram or Facebook comment-to-DM * Lead pipeline tracker (uses memory to check in as leads move through stages) Each template comes with a written prompt you edit to match your business - your pipeline name, your assigned user, your calendar, your tone. The agent also gets tools: it can read and update contacts, send data, hit webhooks, and connect out to apps like Notion and ClickUp, even via MCP. You pick the underlying AI model too, so you can trade cost for quality. That range is why this matters for more than lead capture. The same pattern drives AI that answers, follows up, and books on its own - the agent is just the brain wired into your existing GoHighLevel workflow automation. How do you set up an AI Agent workflow in GoHighLevel? The setup mirrors any workflow, with the agent as the payoff step. * Build the workflow and trigger. In Automations, create a workflow. Add the trigger that should start it - a form submission, a no-show appointment status, an Instagram comment, whatever fits the job. * Add the AI Agent action. Hit the plus, scroll to AI Agent, and pick a matching template. It auto-loads a prompt with the parts you need to swap marked in yellow. * Personalize the prompt. Replace the placeholders - assigned user, pipeline and stage name, business description, calendar link, and any tags to skip (like customer or appointment-booked). A fast trick from the video: paste the template prompt into an AI model that already knows your business, have it rewrite the prompt for you, then paste it back in. * Clear conflicts. Turn off older automations tied to the same trigger. In the video, an old 2023 contact form was still live and would have double-fired - so it got switched off first. * Test with a real submission. Fill out the form yourself and watch the execution log. You'll see the agent create the contact, add tags, create the opportunity, generate a booking link, and send the text and email - end to end. One number worth repeating: in the test, that entire run cost about 2 cents, mostly the outbound text. Which brings Arcytex to what this actually costs. What does the GoHighLevel AI Agent cost to run? The AI Agent is a premium action, so it isn't free like a standard workflow step. You pay a small per-run charge plus usage - the tokens the agent burns thinking and the messages it sends. In the video, one full form-to-follow-up run came in around 2 cents. That's cheap for a personalized reply, an enriched contact, and a booked-ready opportunity. But "2 cents" was one contact. Run it across every form, every no-show, and every Instagram DM at scale and the pennies add up, so watch your wallet balance early instead of finding out on the invoice. If you resell GoHighLevel under your own brand, you can mark the run cost up to your clients - the personalization is an easy upsell, and you're only doing the setup once per agent. The honest gotcha: "automates everything" is marketing. The title says it automates everything. It doesn't, and pretending otherwise will cost you. What it really automates is the repeatable 80% - the follow-ups that look the same every time. The edge cases still need a human: the angry reply, the enterprise lead who doesn't fit your pipeline, the weird question no prompt anticipated. Hand those to an agent and you get a confident, wrong answer sent automatically. And here's the part nobody says out loud: a badly-mapped agent automates your mistakes at scale. Point it at the wrong pipeline, feed it a sloppy prompt, or leave an old workflow firing alongside it, and you don't get a few bad follow-ups - you get hundreds, fast, before you notice. The feature is only as good as the system behind it. It's also in beta, which means the menu, the templates, and the pricing can all shift under you. That's the difference between clicking "AI Agent" and having it actually run your business. The dropdown is the easy part. Mapping it to your real pipeline, your messaging, and your fallbacks - and testing it before it touches a live lead - is the work. Frequently asked questions. Is the GoHighLevel AI Agent action free? No. It's a premium action, so each run carries a small charge plus usage costs for tokens and any messages sent. In the video, a full form-follow-up run cost about 2 cents. Test on yourself first and watch your wallet to learn your real per-run cost before scaling. Do I still need to build normal workflows? Yes, for anything predictable. Deterministic workflows are reliable and cheaper for fixed steps. Use the AI Agent where judgment and personalization pay off - first-touch lead replies, no-show recovery, comment-to-DM - and keep plain automation for steps that never change. Can I control what the AI Agent does? You control it through the prompt, the tools you enable, and the AI model you pick. The pre-built templates give you a starting prompt to edit for your business. But because the agent reasons each time, it's less predictable than a hard-coded workflow - so test it against real cases before trusting it live. Is it safe to use in production right now? It's still in beta. That means it works, but the feature can change, and it can make judgment calls you didn't intend. Keep it on the repeatable jobs, add fallbacks for edge cases, and clear any older automations on the same trigger so nothing double-fires. Get it built right the first time. The AI Agent action is the easy 10%. The value is the system underneath - the right trigger, a prompt mapped to your actual pipeline, the fallbacks for what AI shouldn't handle, and the testing that keeps it off your leads until it works. That's the work Arcytex do every day. Arcytex is 12x HighLevel Award winners with 1,000+ builds shipped, and Arcytex install GoHighLevel workflow automation that runs your follow-up without running your leads into a wall - backed by four written guarantees: zero downtime, on-time delivery, a 14-day money-back window, and no long-term contract. Want AI agents wired into your GoHighLevel the right way? Book a scope call and Arcytex'll map it to your setup. Liked this post? Ready to ship something real? 30 min · No pitch · Written plan either way.