Connecting Hala AI to Your CRM: A Step-by-Step Guide

An AI voice agent that doesn't talk to your CRM is only doing half a job. The call happens, the customer hangs up, and then — nothing. No record update. No follow-up task created. No next step triggered.

The real leverage in voice AI comes when every conversation automatically updates your systems. When a lead is qualified, it moves to the next pipeline stage. When an appointment is booked, it appears in the calendar. When a payment is collected, the account is marked settled. All without a human touching anything.

This guide covers how CRM integration works with Hala AI, what data flows where, and how to set it up for the most common platforms.

How the Integration Works

At its core, the integration is straightforward. After every AI conversation, Hala generates a structured data payload containing:

• Call metadata — timestamp, duration, caller phone number, agent used
• Conversation outcome — qualified, not interested, appointment booked, payment taken, escalated, etc.
• Extracted data — anything the AI captured during the call: name, company, budget, preferred callback time, etc.
• Full transcript — the complete text of the conversation
• Call recording URL — if recording is enabled on your plan

This payload gets sent to your CRM via webhook or native integration, and your CRM uses it to create or update records, trigger workflows, and notify your team.

Salesforce

Salesforce is the most common enterprise CRM we integrate with. The integration maps to standard Salesforce objects.

What gets created/updated:

• A new Lead or Contact record if the caller isn't in your CRM yet (matched by phone number)
• A Task logged against the record with the call outcome and transcript
• Custom fields populated with extracted data (qualification score, budget range, decision timeline)
• An Opportunity created if the lead meets your qualification criteria
• A Flow triggered to assign the lead to the right rep and send them a notification

Setup:

1. In Hala AI, go to Integrations → Salesforce and click Connect
2. Authenticate with your Salesforce org (OAuth2 — no password sharing required)
3. Map your Hala call outcomes to Salesforce lead statuses
4. Define which extracted data fields map to which Salesforce fields
5. Configure your trigger conditions (e.g., "if outcome = Qualified, create Opportunity")

The integration respects your Salesforce field-level security and sharing rules — Hala only writes to fields your connected user has access to.

HubSpot

HubSpot's integration uses native API v3. The data model maps naturally to HubSpot's contact and deal pipeline.

What gets created/updated:

• A Contact created or updated in HubSpot with call data and extracted properties
• A Note attached to the contact with the full transcript
• A Deal created in the appropriate pipeline stage if the lead is qualified
• A Task assigned to the contact owner for follow-up
• An Engagement (call activity) logged with duration and outcome

Setup:

1. Go to Integrations → HubSpot in Hala AI and authorise with your HubSpot account
2. Select which HubSpot pipeline Hala should create deals in
3. Map call outcomes to deal stages (e.g., "Appointment Booked" → "Meeting Scheduled")
4. Enable contact property sync to push extracted data into custom contact properties
5. Set up a HubSpot workflow triggered by the "Hala AI Call Completed" event for any additional automation

Google Calendar & Outlook

For appointment booking flows, calendar integration is essential. When the AI books an appointment, it needs to write directly to the calendar — not just log an intent.

Hala AI supports:

• Google Calendar (via OAuth2)
• Microsoft Outlook / Microsoft 365 Calendar (via Microsoft Graph API)

How it works:

The AI agent checks real-time availability via the calendar API during the call. When a slot is selected, Hala creates a calendar event with:

• Event title (customisable, e.g., "Sales Call — ")
• Guest invite sent to the caller's email (if captured)
• Internal attendee added (the rep or team inbox)
• Location or video link included (e.g., Zoom, Teams link)
• Custom description with call transcript summary

If the caller asks to reschedule, the AI checks availability again and moves the event — no manual action needed.

Webhooks: Custom Integrations

If you're using a CRM or platform not in our native integration list, webhooks let you push Hala call data anywhere that accepts an HTTP POST request.

The webhook payload is a JSON object sent after every call:

{
  "call_id": "hala_abc123",
  "timestamp": "2026-03-01T14:32:00Z",
  "duration_seconds": 134,
  "caller_phone": "+447700900123",
  "outcome": "appointment_booked",
  "agent_id": "agent_loan_collection",
  "extracted_data": {
    "name": "Sarah Johnson",
    "preferred_time": "Thursday 2pm",
    "account_number": "ACC-9921"
  },
  "transcript_url": "https://app.tryhala.ai/transcripts/abc123",
  "recording_url": "https://app.tryhala.ai/recordings/abc123"
}

You can point this webhook at:

• Zapier — to trigger any of 6,000+ app actions without code
• Make (Integromat) — for complex multi-step automation flows
• n8n — for self-hosted workflow automation
• Your own API endpoint — for fully custom handling

What Good Integration Looks Like in Practice

Here's a complete example for a financial services firm using Hala for outbound payment reminders:

1. Hala calls a customer about an overdue account
2. Customer confirms they'll pay by Friday
3. Outcome logged to Salesforce: "Payment Promise — Friday 7 March"
4. Custom field updated: Next Action Date = 8 March (day after promised payment)
5. Task created for the collections team: "Verify payment received — 8 March"
6. Workflow triggered: if payment not received by 8 March, trigger a second call campaign

The entire sequence runs automatically. The collections team only gets involved when a payment is actually missed — not to log every call outcome manually.

Common Mistakes to Avoid

Mapping outcomes too broadly. If you map every call outcome to "Contacted" in your CRM, you lose the nuance that makes the data useful. Be specific — create distinct outcomes for qualified, not interested, no answer, appointment booked, payment promised, and escalated.

Ignoring duplicate matching. Decide upfront how Hala should handle existing records. Match on phone number? Email? Both? If you don't configure this, you'll end up with duplicate contacts.

Not testing with real data. Always run 5–10 test calls before going live. Check that the data appears in the right fields, that workflows trigger correctly, and that your team receives the right notifications.

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