Itifaq, a legal AI platform, aims to simplify legal research and contract analysis by training AI model on local and federal laws of the UAE. Beyond Coders leveraged language translations to understand context and respond in both English and Arabic. This provided law firms, legal departments, and independent practitioners with precise, context-aware answers to legal questions. By reducing document review time and enhancing drafting speed, Itifaq empowers users to streamline their legal processes without requiring a technical background.
Faster legal research and document creation
Accuracy in legal query responses
Reduction in document processing time
Arabic and English support for dual-language legal teams
The Challenge
Legal professionals across the UAE struggle with fragmented information systems, manual document review, and high costs associated with legal research. Adding to the complexity, legal documents are not uniformly formatted or written in a single language; some are in English, others in Arabic, and many include both.
Whether it’s analyzing case law or drafting bilingual contracts, the process is time-intensive and prone to human error. Itifaq needed a solution that would empower its users with AI-generated legal insights grounded in local context, accurate in both English and Arabic, and accessible through a simple chat interface.
What did
Beyond Coders do
We began by gathering requirements and designing intuitive UX flows tailored to legal professionals. After curating and cleaning UAE-specific legal data, we built a secure backend infrastructure with JWT-based user authentication and robust APIs.
Next, we tested and evaluated multiple large language models (LLMs), including Lisan, OpenAI, Llama, and Anthropic, for bilingual performance. A Retrieval-Augmented Generation (RAG) system was implemented for context-rich responses, powered by Milvus and LangChain to maintain natural conversation flow.
We also enabled document uploading and machine-readable conversion for on-the-fly legal document analysis. Everything was containerized, integrated, and deployed in a scalable production environment with real-time monitoring and ongoing model fine-tuning.
The Results
- Up to 85% accurate legal responses in Arabic and English
- 70% faster research compared to traditional workflows
- Legal teams reduced contract turnaround times by half
- Lawyers received actionable insights without needing a technical team
- Seamless handling of mixed-language documents, reducing context loss during analysis
