Islamic research has always meant long hours cross-referencing classical sources by hand.
Tbyaan is a research platform for Islamic scholarship with two capabilities: semantic search across the Quran, authenticated Hadith, Tafseer commentary and Islamic Q&A datasets - searchable together, understanding classical Arabic and religious context rather than matching keywords - and a deep-research agent that synthesizes evidence and drafts a structured, source-backed outline for a jurisprudential or historical question. Every generated passage maps back to its source.
Search runs through the Qurani.ai API, backed by Kawn Lab's Islamic embedding model. The research agent turns a question into a sourced draft instead of a list of links.
How the research runs
A question
A jurisprudential or historical question, handed over as a question rather than broken down into keywords first.
Search across the corpus
Queries run through the Qurani.ai API, backed by Kawn Lab's Islamic embedding model, over the Quran, authenticated Hadith, Tafseer commentary and Islamic Q&A together rather than four times over.
Synthesis
The agent gathers the relevant evidence and builds an outline, instead of returning a list of links for you to assemble.
A sourced draft
Every piece of generated text maps back to its source, so the output holds up to scholarly scrutiny instead of just sounding authoritative.
Two capabilities
Semantic search that understands the context
The search understands classical Arabic and religious context rather than matching keywords, which is what makes searching Tafseer commentary different from searching a document store.
A research agent that does the research
Hand it a question and it synthesizes the evidence, builds the outline and drafts from classical sources. It does not replace the scholar; it removes the documentation work so the time goes to analysis.
Access
Models
Solutions
Let's talk about what you're trying to build.
Tell us the problem. We'll tell you honestly whether AI is the right answer.