7 portfolio startups. One shared AI architecture. Each one scaled globally.
The result
7 portfolio startups equipped with AI Revenue Engines. All expanded beyond regional markets.
The Challenge
iPark manages a portfolio of startups at different stages, in different sectors, with different products and different target customers. Building a custom Revenue Engine for each startup from scratch would take too long and cost too much. iPark needed a partner who could deploy a consistent architecture quickly and adapt it to each startup's specific situation.
The Solution
Kawkab built a shared Revenue Engine architecture and deployed a tailored version inside each of the seven portfolio startups. The core system was the same across all seven. The targeting logic, the agents, and the conversion playbooks were rebuilt specifically for each startup. Every week Kawkab ran cross-portfolio performance reviews. When something worked inside one startup the learning was shared across the portfolio.
What we delivered
A shared Revenue Engine architecture deployed inside all seven startups.
Per-startup ICP analysis, agent configuration, and conversion playbook.
Weekly cross-portfolio performance reviews. Learnings from one startup shared across the whole portfolio.
Full onboarding and handover materials for every founding team.
A continuous optimization layer running across all seven deployments.
The Results
7
Portfolio startups equipped with AI Revenue Engines
All 7
Expanded beyond regional markets
Shared
Architecture. Seven tailored playbooks.
From the client
“Kawkab gave our portfolio a shared advantage. Each founder gets a Revenue Engine tuned to their product, but the underlying system gets sharper across the whole portfolio.”
Managing Partner
iPark
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