Dubai-based Arabic.AI unveiled an agentic AI platform specifically engineered for Arabic language.

Founded by serial entrepreneur Nour Al Hassan who was recognized for building language technology provider Tarjama, Arabic.AI has developed Pronoia, a proprietary large language model that benchmarks show outperforming GPT-4, Deepseek and Cohere and other leading systems on Arabic language tasks.

“For too long, Arabic has remained an afterthought in the global AI landscape,” Al Hassan told reporters during the launch event. “We’ve built something fundamentally different—an autonomous system that actually understands the nuances of Arabic across multiple dialects and contexts.”

The company’s agentic platform allows AI systems to execute complex tasks independently, orchestrating multi-step workflows without continuous human guidance. Early enterprise adopters have deployed the technology across financial services, healthcare, legal, and media operations.

Arabic.AI offers enterprises three distinct ways to leverage its powerful Pronoia engine and platform, tailored to meet different business needs:

• Licensing the engine: Clients can license Pronoia—the underlying large language model—and embed it directly into their own software or infrastructure, without using Arabic.AI’s full platform.
• Workflow integration: Organizations can access the Arabic.AI platform as a standalone solution or integrate it into existing systems, using it in applications such as chat interfaces, content generation, or document analysis.
• Custom AI solutions: For enterprises with unique requirements, Arabic.AI offers fully customized solutions. These may involve adapting Pronoia or incorporating additional AI models beyond the core platform to meet highly specialized use cases.

This flexible model allows organizations across industries to tap into cutting-edge Arabic AI—whether through plug-and-play tools, enterprise integration, or fully tailored deployments.

Several Fortune 500 companies are testing Arabic.AI in production environments after participating in pilot programs, according to company officials.

The technology builds on a massive dataset compiled over 16 years, giving it contextual understanding that generic models lack when processing Arabic content. The company offers flexible deployment options including cloud-based, on-premises, and API access.