Tarjama& Bags US$15 Million To Grow Its Arabic.AI Platform

Tarjama&, the UAE-based language technology company, has bagged US$15 million in a Series A funding round to accelerate the expansion of Arabic.AI, its enterprise-focused Arabic language artificial intelligence (AI) ecosystem.  

The round was led by the Dubai-based international venture capital (VC) firm Global Ventures, with participation from Dubai-based Wamda Capital, Ukraine-based TA Ventures, Oman-based Phaze Ventures, Singapore-based Golden Gate Ventures, and New York-based Endeavor Catalyst. 

Founded by Nour Al Hassan in Amman in 2009, Tarjama& has steadily transformed from a translation service provider into a deeptech firm building language solutions for Arabic-speaking markets. Today, it operates in over 30 markets, having processed more than two billion words across 50 languages and 22 Arabic dialects. The backbone of this transformation is Tarjama&’s Arabic.AI agentic ecosystem, designed to help organizations automate complex workflows using AI agents built specifically for the region’s linguistic and cultural context. 

“Most global AI models were trained primarily on English and Western-language datasets, leading to serious limitations when applied to Arabic,” Al Hassan told Inc. Arabia in an interview. “These models often struggle with script variations, cultural nuances, dialects, rich morphology, and semantic precision, resulting in outputs that feel artificial, inaccurate, or simply unusable.” 

To address this, Tarjama& built Pronoia—its proprietary large language model (LLM)—entirely from the ground up. Designed as an Arabic-first model rather than a derivative of global systems, Pronoia has been trained on high-quality datasets curated across dialects, domains, and real business contexts. 

“It’s not a layer on top of global tech,” Al Hassan explained. “It’s an Arabic-first foundation that understands, reasons, and generates language natively.” 

The performance of Pronoia is already drawing attention. According to the company, it outperforms global models like GPT-4o, DeepSeek-V3, and Cohere on Arabic-specific tasks, achieving stronger contextual accuracy and enterprise-grade reliability in language processing. It also topped the open Arabic LLM leaderboard on the AI benchmarking platform Hugging Face upon its launch in December 2024. 

Tarjama&, which is already profitable, has reported a 20 percent compound annual growth rate in revenue over the past three years. Its current focus is to scale Arabic.AI as a foundational infrastructure for the MENA region’s digital economy, serving over 400 million Arabic speakers whose needs have long been underserved by global AI tools. 

With the fresh capital, the company plans to expand its research and engineering teams, invest in infrastructure across sectors, and launch a major new initiative called the Arabic.AI Academy. The academy will be dedicated to training enterprise and government professionals in AI implementation, bridging a critical gap in regional AI adoption. 

“Only six percent of companies globally are adopting AI the right way, a number that’s shockingly low compared to the potential,” Al Hassan explained. “With the right tools and training, AI can unlock cost savings, boost efficiency, and free up human time for strategic decisions, not repetitive tasks.” 

Al Hassan also noted that access to technology alone doesn’t guarantee adoption, pointing to two main challenges holding back wider AI integration in the region. First, she noted the shortage of Arabic-first training materials, since most resources are designed for English-speaking users and fail to address the specific needs of the MENA. The second challenge, she explained, is a general lack of preparedness within organizations, where many teams find it difficult to understand how AI can be applied in their daily workflows. 

Arabic.AI Academy is designed to meet these challenges head-on. “We’re launching the Arabic.AI Academy to provide practical, contextualized training that helps leaders move from interest to impact,” she said. 

As for other startups building AI tools for languages or regions overlooked by big tech, Al Hassan offered clear advice. “Don’t wait for big tech to solve local problems. Build with context, and build with community. Success in underrepresented languages comes from deeply understanding user pain points and creating culturally relevant solutions, not just translating existing tools.”  

She added, “We also believe in vertical integration, owning the model, the platform, and the training ecosystem. That’s how we’ve built Arabic.AI: not just as a product, but as infrastructure for the future of Arabic digital transformation.” 

Pictured in the lead image is Tarjama& founder Nour Al Hassan. Image courtesy Tarjama&.