Queries in your users’ words
Formal and informal Arabic, regional vocabulary, mixed-language terminology, and ambiguous requests against Arabic or English sources.
Bayanat Search
Arabic queries paired with the evidence that answers them.
Give your search or RAG system examples of what a useful result looks like. We create queries, relevance judgments, and grounded answers from the documents your product uses.
What we can build together
Graded relevance
Judgments distinguish direct evidence, useful background, and passages that mention a topic without answering the question.
Difficult alternatives
Outdated policies and rules for a different customer group make useful hard negatives when they resemble the right answer.
Grounded answers
Answers link to exact evidence. Include questions the sources cannot resolve, so missing information is part of the training.
How we put the data together
Choose the sources
Start with authorized documents, their versions, and effective dates in one domain.
Review the judgments
Check sample queries, relevance grades, and reviewer reasoning, including cases where reviewers disagree.
Evaluate both steps
Test whether retrieval finds the right passage and whether the answer stays faithful to it. Keep test queries separate from training.
Finding the current returns policy
A user asks informally whether an order can be returned. The right passage comes from the current policy for that customer, even if an old version has almost identical wording.
Common questions
Can Arabic queries retrieve English documents?
Yes. A custom dataset can pair Arabic or mixed Arabic-English queries with English sources. This is useful when employees ask questions in Arabic but company documentation is written in English.
Why include questions with no answer in the source documents?
They help you train and test what the system does when evidence is missing. The expected response may be to ask for a detail or explain that the available sources do not establish an answer.