Assistants & RAG

Knowledge Base Vectorization

We transform scattered documents into a searchable, semantic vector knowledge base.

We consolidate fragmented knowledge from documents and systems, then clean, chunk, and index it into high-quality vector stores. Chunking and embedding strategies are tuned to your Arabic and English content to maximise retrieval accuracy. Your knowledge becomes a reliable foundation for any downstream assistant or semantic search engine.

How we deliver it

01

Scoping session

We map your environment and obligations, then fix the boundaries.

02

Documented execution

A declared methodology with pre-agreed deliverables.

03

Evidence handover

A report and evidence fit for both the auditor and the board.