Qalam AI · Technology & research initiative
We're building the intelligence layer for Arabic.
A language is more than a sequence of words. It is structure, context, expression and centuries of thought. Our ambition is to build intelligence that helps people engage with Arabic more deeply.
لغة · معنى · معرفة
Language · Meaning · Knowledge
Developing initiative · research directions, not completed capabilitiesAmbition, with an honest starting point
Lisaan is our first application.
We begin with intelligent, curriculum-guided Arabic education: a concrete place to build, test and learn from an Arabic learning experience.
Qalam in Lisaan today
Structured lessons, curriculum-aware text practice, explanations, corrections, retries and private session history. Voice, handwriting, notebook and guided-conversation tools have controlled availability.
Today’s implementation uses external AI providers, structured lesson context and server-side curriculum and assessment safeguards. AI feedback remains probabilistic and can be mistaken.
Try LisaanQalam AI’s longer-term direction
We are working toward specialised Arabic intelligence, informed by the language’s structure and the needs of learners, readers, researchers and builders.
This is not a claim that we have trained a proprietary foundation model, completed the research below or independently validated advanced Arabic understanding. Future capabilities require research, evaluation and appropriate expert review.
An agenda to investigate
From the shape of a word to the meaning of a text.
These are our developing research directions. They are not a list of features available in Lisaan today.
Morphology
Investigating roots, patterns and word formation as foundations for understanding Arabic.
Syntax
Exploring grammatical relationships and how sentence structure shapes meaning.
Contextual semantics
Working toward richer understanding of words and expressions in their linguistic context.
Classical Arabic
Exploring language-aware reading and research support for classical texts, with specialist review.
Trustworthy explanations
Investigating source-grounded explanations, traceable evidence and clear communication of uncertainty.
Adaptive learning
Researching how learning evidence could inform useful support without overstating mastery.
Beyond education · long-term ambition
A foundation for more ways to work with Arabic.
Alongside education, we want to explore Arabic reading companions, research support, tools for engaging with classical texts and developer tools for Arabic-language applications.
These are planned areas of exploration. No research platform, classical-text analysis product or developer API is being offered on this page.
Depth before claims.
Our direction calls for careful evaluation, trustworthy sources, appropriate rights and specialist collaboration. A compelling vision should be matched by evidence as the work develops.
For prospective partners
An invitation to shape the work.
We welcome interest from Arabic-language researchers, educational specialists, prospective funding partners and technology collaborators who share this ambition.
Potential collaboration areas include linguistic evaluation, responsibly licensed source material, learning research and technical infrastructure. This is an invitation to explore the direction, not an announcement of existing partnerships, funding or research results.
Our first documented research protocol, QALAM-R01, investigates whether structured learner evidence can improve curriculum-constrained next-practice recommendations against fixed and LLM-only baselines. The protocol is published for review; benchmark results and validated learning gains are not yet available.
Lisaan is developed by Verda Global Limited
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