GHL Conversation Summaries + AI Automation

Kollab App – More Control

• What it does
  • Gives your team tighter control over how collaboration actually happens inside Kollab, especially when it comes to shared tasks and internal approvals.
• Where in GHL
  • Kollab App → Project / Task Settings → Updated collaboration controls.
• Who benefits most
  • Agencies managing internal production teams.
  • Businesses using structured task workflows.
  • Teams coordinating client deliverables across departments.
• Impact
  • Improves operational clarity and reduces task confusion. This is about smoother teamwork and tighter internal execution.

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Better Playback, Stronger Security

• What it does
  • Enhances media playback performance across the platform while strengthening access controls and security around shared content.
• Where in GHL
  • Media / File Access Areas → Playback & Security Settings.
• Who benefits most
  • Agencies delivering video content or digital assets.
  • Teams sharing internal training materials.
  • Businesses handling sensitive files or private resources.
• Impact
  • Smoother playback improves user experience. Stronger security reduces risk. This is an operational stability upgrade, less buffering, fewer access issues, and better protection of shared content. It’s about performance and trust, not flash.

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Configure Payment Provider by Channel

• What it does
  • Allows businesses to configure different payment providers depending on the sales channel being used.
• Where in GHL
  • Settings → Payments → Channel-Based Payment Configuration.
• Who benefits most
  • E-commerce brands.
  • Agencies running multi-channel funnels.
  • Businesses separating online vs. in-person payments.
• Impact
  • More flexibility in payment processing. Better financial tracking and channel-level control.

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Configure Granular Permissions for Sub-Account Settings

• What it does
  • Introduces more detailed permission control inside sub-account settings, allowing admins to restrict specific configuration access.
• Where in GHL
  • Agency View → Sub-Account Settings → Permissions & Roles.
• Who benefits most
  • Agencies managing multiple clients.
  • Teams with tiered staff access levels.
  • Businesses wanting tighter account security.
• Impact
  • Stronger access control. Less risk. Better role-based governance.

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Communities Learning Tab – Private Course / Member-Specific Access

• What it does
  • Enables private course access within Communities, allowing content to be restricted to specific members or groups.
• Where in GHL
  • Communities → Learning Tab → Course Access Settings.
• Who benefits most
  • Coaches and course creators.
  • Membership site owners.
  • Agencies running paid communities.
• Impact
  • Improves monetization control and member segmentation. More structured content delivery.

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Introducing New Templates

• What it does
  • Adds new pre-built templates to accelerate page, workflow, or asset creation.
• Where in GHL
  • Templates Library → Select Template Type → Apply.
• Who benefits most
  • Agencies deploying quickly.
  • New sub-accounts.
  • Teams wanting faster build times.
• Impact
  • Speeds up execution and reduces build friction.

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Standard Builder – Drag-and-Drop Triggers and Actions

• What it does
  • Introduces a drag-and-drop interface for building workflows using triggers and actions visually.
• Where in GHL
  • Automation → Workflows → Standard Builder.
• Who benefits most
  • Automation-heavy agencies.
  • Users building complex workflows.
  • Teams wanting better visualization.
• Impact
  • Improves clarity in automation building. Faster workflow creation. Fewer logic mistakes.

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OpenRouter Actions & Triggers

• What it does
  • Adds OpenRouter integration actions and triggers for expanded AI model connectivity inside workflows.
• Where in GHL
  • Automation → Workflow Actions & Triggers → OpenRouter.
• Who benefits most
  • Advanced AI users.
  • Agencies building AI-powered automations.
  • Developers integrating multi-model AI workflows.
• Impact
  • Expands AI flexibility and automation intelligence across models.

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Monday.com Actions and Triggers

• What it does
  • Enables direct workflow triggers and actions tied to Monday.com boards and updates.
• Where in GHL
  • Automation → Workflow Actions & Triggers → Monday.com.
• Who benefits most
  • Agencies using Monday for project management.
  • Businesses syncing CRM and task systems.
  • Operations-focused teams.
• Impact
  • Stronger cross-platform workflow automation. Reduces manual syncing.

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Find Contact – Additional Email/Phone Search

• What it does
  • Enhances contact lookup functionality by allowing searches using additional email addresses or phone numbers.
• Where in GHL
  • Contacts → Search Bar → Additional Email / Phone Fields.
• Who benefits most
  • High-volume CRM users.
  • Support teams.
  • Agencies handling duplicate or multi-contact records.
• Impact
  • Improves data accuracy and reduces contact duplication. Faster contact retrieval.

GHL just changed how Conversation AI sessions are recorded and used.

With Conversation Summaries, every AI session now generates a structured summary and a full transcript automatically. No manual logging. No copy-paste. No digging through message threads.

Here’s what’s new.

Summaries are generated per session, not per conversation thread. That means each AI interaction is treated as its own event. Once a session ends, whether by inactivity, bot sleep, workflow conditions, message limits, or human handover, GHL creates a fresh Conversation Summary.

It only pulls in messages that happened after the last recap, inbound and outbound, so the record stays clean and complete.

And this isn’t just about storage.

These Conversation Summaries can automatically save to contact records, trigger workflows instantly, and even send email notifications to admins, users, or assigned reps. You can also define inactivity time limits and set minimum message thresholds before a summary is generated.

Important note: This feature must be enabled in Agency Labs, and summaries only capture data while it’s active. It’s not retroactive.

This is a structured, session-based AI logging system built directly into GHL.

To use Conversation Summaries properly, you need to understand how sessions are defined inside GHL.

A summary is generated per session, not per contact and not per entire conversation history. That’s a key difference.

A session ends when one of the following happens:

• The configured inactivity time expires
• The bot is put to sleep
• The maximum message limit is reached
• A workflow forces a bot sleep
• A Stop Bot condition is triggered
• A human handover occurs
• A manual or workflow message interrupts the session

Once that boundary is hit, GHL generates a new Conversation Summary.

The transcript is different from the summary.

The transcript is the raw recording. The summary is the condensed version. Same conversation, different levels of detail.

One important detail: Conversation Summaries are only generated for messages that occur while the feature is enabled. If it’s off, nothing is logged retroactively.

This is clean, session-based AI tracking built for automation.

If you run an agency, Conversation Summaries aren’t just a nice feature. They’re control.

Before this update, AI conversations lived inside message threads. There was no centralized, structured recap. No easy way to audit what the bot said. No clean way to trigger automation based on actual conversation outcomes.

Now you have visibility.

Conversation Summaries give you a session-based record of every AI interaction. That means you can review performance, catch mistakes, improve prompts, and protect client accounts. If a bot mishandles an objection or gives incomplete information, you’ll see it.

That’s operational power.

But it goes deeper than audits.

You can now trigger CRM actions automatically based on real conversation data. Move opportunities. Update custom fields. Tag hot leads. Notify sales reps instantly. Send follow-ups without anyone touching the keyboard.

For agencies managing multiple sub-accounts, this is huge. It standardizes AI oversight across clients and turns chat data into measurable automation.

Instead of AI conversations being temporary, they become structured assets.

And structured data is what drives scalable growth inside GHL.

If you’ve ever wondered what your AI bot actually said… or wished you could trigger automation based on real chat outcomes… this feature is your fix. With Conversation Summaries turned on, every AI chat session becomes usable CRM data. You don’t have to scroll through long threads anymore. The recap, transcript, and automation triggers are already there. You can enable and configure this in just a few quick steps.

1.1 Go to your Agency View.
1.2 Navigate to Settings

1.3 Click the labs
1.4 Locate Conversation Summaries and click activate feature.

2.1 Go to the Sub-Account where your bot lives.
2.2 Navigate to AI Agents > Conversation AI. 
2.3 Click the create bot

3.1 Choose and click if Guided Form Setup, Prompt Base Bot or Flow Based Builder
3.2 Click create new bot

3.3 Then select if General Q&A or Appointment booking
3.4 Click continue

4.1 Select the brand voice
4.2 Then click next

5.1 Fill up your bot name
5.2 Then click next

6.1 Locate Enable Conversation Summary option.
6.2 Toggle it ON.

7.1 Set an Inactivity Time (example: 15 minutes).
7.2 Define a Minimum Message Count required before a summary generates.
7.3  Enable workflow trigger when a summary is created.
7.4 Choose whether to automatically save the summary to a custom field.
7.5 Configure email notifications (All admins, All users, Assigned user, Specific users, or Custom emails).
7.6 Then save

Your AI conversations are now logged, summarized, and driving CRM action automatically.

This is where Conversation Summaries stop being “nice to have” and start becoming serious leverage.

When a summary is generated, you can trigger a workflow instantly. No traditional trigger required. The session ends, the Conversation Summary is created, and your automation fires.

Inside workflows, you can access two powerful variables:

• Conversation AI → Summary
• Conversation AI → Transcript

That means you’re not just reacting to a tag or a button click. You’re reacting to what was actually said.

Here’s where it gets fun.

You can use GPT actions inside workflows to:

• Extract key buying signals
• Identify objections
• Pull out budget or timeline details
• Update custom fields automatically
• Score leads based on conversation tone
• Append multiple summaries into long-term contact history

You can automatically move an opportunity to a new pipeline stage based on summary content. You can alert a sales rep if negative sentiment appears. You can send internal notifications when a hot keyword is detected.

This turns Conversation Summaries into a decision engine.

Instead of reviewing chats manually, your CRM responds in real time.

That’s automation with context.

Now let’s talk execution.

Conversation Summaries aren’t just about record keeping. They’re about turning AI conversations into revenue-driving actions.

Here are real-world ways agencies can deploy this immediately.

Auto-Tag Hot Leads
 Let GPT scan the summary for buyer intent, phrases about pricing, timelines, or starting soon. If it spots them, tag the lead as hot and notify sales immediately.

Move Opportunities Automatically
If the summary includes intent-based language, move the opportunity to the next pipeline stage without manual review.

Escalate Negative Sentiment
If a transcript shows frustration or dissatisfaction, trigger an internal alert or create a task for immediate follow-up.

Extract Key Data
Pull out budget, timeline, service type, or location from the Conversation Summary and update custom fields automatically.

Build an AI Call Recap
Send an internal email summary to your sales team after each session. No one has to read through the full transcript unless needed.

Create a Knowledge Base
Over time, you can review transcripts to spot repeat objections and common questions. Then adjust your bot replies or create content that answers those issues upfront.

This is where Conversation Summaries become strategic.

You’re not just storing AI conversations.

You’re training your automation to think.

Once Conversation Summaries are running inside your account, things get cleaner. Faster. Smarter.

First, you gain visibility.

You can finally see what your AI is doing across every session. No more guessing. No more scrolling through long chat threads trying to piece together what happened.

Second, your automations get sharper.

Instead of triggering workflows based on surface-level actions, you’re now reacting to actual conversation outcomes. Conversation Summaries give your CRM context. And context is what makes automation powerful.

Third, your follow-ups speed up.

Hot leads get flagged instantly. Sales reps get notified automatically. Opportunities move without manual review. That alone can shave hours off your response time.

Fourth, your CRM gets cleaner.

Key details like budget, service type, objections, and intent can be extracted directly from transcripts and stored properly. No more relying on memory or manual notes.

And long term?

You build a smarter system.

The more Conversation Summaries you analyze, the better your AI prompts, workflows, and sales processes become. You start spotting patterns. You refine responses. You close gaps.

This isn’t just logging.

It’s operational intelligence built into GHL.

AI conversations are data.

And data without structure is wasted opportunity.

Before this update, your Conversation AI sessions lived inside threads. Useful in the moment. Hard to review later. Almost impossible to automate intelligently without extra steps.

Now, Conversation Summaries change that.

Every AI interaction becomes structured, session-based intelligence. It can be stored. Triggered. Analyzed. Extracted. Automated.

That’s a massive shift.

Instead of treating AI like a chat tool, you start treating it like a data engine. Every conversation feeds your CRM. Every session can drive a workflow. Every transcript becomes insight you can act on.

For agencies, this is control at scale.

You can audit bots across sub-accounts. Improve prompts based on real conversations. Automatically escalate issues. Identify buying signals instantly. And build smarter automations that respond to what people actually say.

That’s how AI should work.

Using Conversation AI already? Switch this on and wire it into your automations. Not using it yet? Now might be the time.

Because conversations shouldn’t disappear.

They should compound.