💼 Multi-Brand Business Group · GCC

Five brands.
One AI intelligence layer.
Zero manual reporting.

How SiMar Group deployed EyebAi's complete 5-system AI stack across their entire portfolio — creating a unified operational intelligence system that the group CEO monitors from a single dashboard, updated automatically every week.

5
Brands unified under one stack
1
Dashboard for the entire group
Auto
Weekly group performance report
8 wks
Full stack implementation

The challenge: running a group with no unified visibility

SiMar Group is a diversified business group operating across multiple sectors in the GCC. As the group expanded from one brand to five, a structural problem emerged: each brand operated in its own silo. Different CRMs, different reporting formats, different content approaches, different advertising agencies, different lead management systems.

The group CEO was spending a significant amount of every week in status meetings, chasing reports from brand managers, and trying to build a coherent picture of group performance from disconnected data sources. The information was always late, often incomplete, and formatted differently by every team member who produced it.

More critically: when one brand had a performance problem — a sudden drop in leads, a spike in cost per acquisition, a retention issue — there was no way to detect it quickly. It would surface in a monthly review meeting, weeks after the problem began.

What EyebAi built

Rather than deploying a single system for one brand, EyebAi designed a group-level AI architecture: a single unified Intelligence CRM with separate brand sub-accounts, a shared reporting layer, and brand-specific automation workflows that all feed into one central dashboard.

The five systems were deployed simultaneously across all five brands — adapted for each brand's sector and customer journey, but architecturally unified so data could be aggregated at group level.

🔍 Intelligence System™
AI readiness audit conducted for all 5 brands simultaneously — producing a prioritised transformation roadmap per brand and a group-level opportunity map.
✍ Content Engine™
Separate content calendars per brand, each with its own voice profile and audience strategy — all managed through a single content operations system.
⚙ Automation Core™
AI employees deployed per brand for WhatsApp enquiry handling, lead routing, and post-interaction follow-ups — each trained on brand-specific knowledge and tone.
📈 Growth Engine™
Unified ad account structure with brand-level campaign segmentation — enabling group-wide budget optimisation and cross-brand audience building.
🎯 Intelligence CRM™
One CRM platform with 5 brand sub-accounts. All leads, pipeline stages, and revenue data roll up to a single group dashboard. Automated weekly performance reports delivered to the CEO every Monday morning — no human input required.

The group intelligence dashboard

The central deliverable for the SiMar Group was the unified intelligence dashboard — a live view of all five brands' performance accessible on any device. The dashboard shows lead volume by brand, pipeline value and stage distribution, conversion rates, content performance, ad spend and ROAS, and customer retention metrics — all updated in real time.

Every Monday morning, an AI-generated group report is automatically delivered to the CEO's email. The report covers the previous week's performance, flags any anomalies or underperforming metrics across any brand, and includes AI-generated recommended actions for each issue identified. The CEO arrives at Monday meetings already briefed — the meetings themselves have become strategic discussions rather than status updates.

"Before EyebAi, I spent Monday mornings collecting information. Now I spend Monday mornings making decisions. That's a fundamentally different business — and it happened in eight weeks."

Results after 12 weeks

All five brands operating on unified AI infrastructure. Group lead response time reduced across the portfolio from an average of 4 hours to under 8 minutes. Content output across the group increased by 3× with no additional headcount. The CEO recovered an estimated 8–10 hours per week previously spent on status reporting and manual data collection.

The most significant impact was operational intelligence: within the first month, the system flagged a significant underperformance in one brand's lead qualification rate. The issue was identified, diagnosed, and resolved within 48 hours — something that would previously have taken 3–4 weeks to surface in a manual reporting cycle.

Running multiple brands?
One AI stack. One dashboard.

Book a strategy call to explore what a unified AI intelligence layer looks like across your business portfolio.

Book Your Free Strategy Call →
← Back to all case studies