Intelligence, Orchestrated.
Saudi companyArabic + English RAG
Search your PDFs, policies, SOPs, and contracts with citations and do-not-guess behavior. Role-based access. Arabic and English.
Knowledge is scattered across SharePoint, file shares, email attachments, and PDFs. People ask the same questions, get inconsistent answers, or just give up and call someone.
A governed search interface over your approved documents with hybrid retrieval, citations, role-based access, and refusal when sources are weak. Logs every query and answer for audit.
Process PDFs, Word, SharePoint, and approved sources. Extract Arabic and English text. Chunk and index with metadata.
Hybrid retrieval (keyword + vector) finds the most relevant chunks. The model answers with citations, or refuses if sources are weak.
Role-based access, query logs, and a golden-set evaluation run weekly. Refuse-rate and citation-rate are KPIs.
OpsRAG deployed for procurement and operations teams searching policies, contracts, and SOPs with Arabic-language coverage. Proof artifacts under NDA.
Full pilot: SAR 60,000 to 80,000 over 6 to 8 weeks. Mini-pilot: SAR 20,000 to 30,000 for narrow scope on one source type.
Yes. Arabic and English are first-class. Quality depends on text extraction; scanned PDFs need OCR which is tested in UAT.
Role-based access is enforced at retrieval. Users only see chunks from sources they are authorized to view.
Citations, golden-set evaluation, retrieval score thresholds, and explicit refusal when sources are weak. We do not measure usefulness without measuring honesty.
Possible as a next-phase channel, but the pilot should start with one primary interface to keep the evaluation clean.
Yes via official APIs with read-only scopes by default.
Share the workflow, systems, volume, and goal. We reply with scope, KPIs, timeline, and a SAR estimate within 24 hours.
Start nowSaudi companyArabic + English RAG
Search your PDFs, policies, SOPs, and contracts with citations and do-not-guess behavior. Role-based access. Arabic and English.
Knowledge is scattered across SharePoint, file shares, email attachments, and PDFs. People ask the same questions, get inconsistent answers, or just give up and call someone.
A governed search interface over your approved documents with hybrid retrieval, citations, role-based access, and refusal when sources are weak. Logs every query and answer for audit.
Process PDFs, Word, SharePoint, and approved sources. Extract Arabic and English text. Chunk and index with metadata.
Hybrid retrieval (keyword + vector) finds the most relevant chunks. The model answers with citations, or refuses if sources are weak.
Role-based access, query logs, and a golden-set evaluation run weekly. Refuse-rate and citation-rate are KPIs.
OpsRAG deployed for procurement and operations teams searching policies, contracts, and SOPs with Arabic-language coverage. Proof artifacts under NDA.
Full pilot: SAR 60,000 to 80,000 over 6 to 8 weeks. Mini-pilot: SAR 20,000 to 30,000 for narrow scope on one source type.
Yes. Arabic and English are first-class. Quality depends on text extraction; scanned PDFs need OCR which is tested in UAT.
Role-based access is enforced at retrieval. Users only see chunks from sources they are authorized to view.
Citations, golden-set evaluation, retrieval score thresholds, and explicit refusal when sources are weak. We do not measure usefulness without measuring honesty.
Possible as a next-phase channel, but the pilot should start with one primary interface to keep the evaluation clean.
Yes via official APIs with read-only scopes by default.
Share the workflow, systems, volume, and goal. We reply with scope, KPIs, timeline, and a SAR estimate within 24 hours.
Start now