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What You’ll Need

  • Your iGaming platform details (domain, brand name)
  • Integration team access (for the technical setup)
  • 30 minutes for initial configuration

Step 1 — Create Your Account

Go to app.atlas.io/signup and create your organization account. During signup you’ll configure:
  • Organization name — Your company name
  • Primary contact — Billing and compliance contact
  • Jurisdiction — Your primary operating country/region

Step 2 — Add Your First Brand

After account creation, navigate to Settings → Brands → Add Brand. A brand represents a single product (domain). For example:
  • apostas.example.com → Brand “Example Sports”
  • casino.example.com → Brand “Example Casino”
You can add multiple brands under a single organization. All data is isolated by brand. Analytics can be viewed per-brand or aggregated across all brands.

Step 3 — Connect Your Platform

Hand off the following to your development team:

Developer Quickstart

Technical guide for integrating the Events API with your backend
Your dev team will need:
  1. Your Organization ID — found in Settings → Organization
  2. Your Brand ID — found in Settings → Brands
  3. An API Key — created in Settings → API Keys

Step 4 — Verify Data Flow

Once the integration is live, check the Events dashboard to confirm data is flowing:
  • Green status = events being received
  • You should see event counts increasing in real-time
  • First analytics will appear within minutes of receiving events

Step 5 — Configure Your Team

Add your analytics, finance, and compliance teams to Atlas:
  1. Go to Settings → Team
  2. Invite users by email
  3. Assign roles:
    • Admin — Full access including billing and API keys
    • Analyst — Read-only access to all reports
    • Compliance — Access to PLD and Responsible Gambling reports

What Comes Next

Financial Reports

GGR, NGR, and revenue breakdown reports

Risk Analysis

Real-time risk exposure monitoring

PLD Compliance

AML monitoring and COAF reporting

Player Behavior

Segmentation, retention, and LTV analysis