Research domain
Retrieval & Knowledge Systems
Advanced RAG pipelines, vector search, semantic indexing, legislative intelligence and knowledge graph research.
Enterprise AI is only as good as the knowledge it can find. We research how to retrieve the right passage from millions of documents, connect related facts, and ground every answer in sources people can check, in both Arabic and English.
Why it matters
Organizations hold their most valuable knowledge in documents: laws, policies, contracts and reports. AI that can reliably find and connect that knowledge, and show its sources, is the foundation for trustworthy answers.
Questions we are working on
How do we find the exact passage that answers a question in a very large library?
How can relationships between laws, policies and documents be captured and used?
How do we keep answers grounded in sources and show those sources clearly?
How do retrieval systems stay current as documents change?
Focus areas
Advanced RAG pipelines
Retrieval-augmented generation designs that combine search, ranking and grounded answers.
Vector search
Embedding and indexing strategies for fast, accurate semantic search at scale.
Semantic indexing
Breaking documents into meaningful units such as articles, clauses and sections.
Legislative intelligence
Understanding legal text, cross-references, amendments and possible conflicts.
Knowledge graphs
Linking entities and documents so AI can reason over relationships, not just text.
Source citation
Showing where every answer comes from so experts can verify it.
Our research approach
01
Understand the documents
Parse structure such as articles, clauses, tables and references.
02
Index for meaning
Combine semantic and keyword search for accurate retrieval.
03
Link the knowledge
Build graphs of how documents, entities and rules relate.
04
Ground every answer
Generate answers only from retrieved sources and cite them.
What it delivers
Accurate answers
Responses based on the right passages.
Verifiable sources
Every answer points back to its documents.
Hidden conflicts found
Relationships and contradictions surfaced automatically.
Arabic and English
Retrieval designed for bilingual content.
Milestones
2023
Enterprise retrieval foundations.
2024
Semantic indexing for large policy libraries.
2025
Arabic legal AI across 8,000+ UAE legislations.
2026
Knowledge graph research for legislative intelligence.
In practice
- Arabic legal AI that reads more than 8,000 UAE legislations and detects conflicts between them.
- An HR companion that searches thousands of policy documents for 14,000 employees.
Related BrainShift products
Frequently asked
How large a document library can it handle?
The research targets national-scale libraries with many thousands of documents.
Does it work in Arabic?
Yes. Arabic legal and policy text is a core focus.
How do we know an answer is correct?
Answers cite their sources so experts can check them directly.
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