Evidence before generation
Research writing starts from screened sources and structured evidence records — not from unsourced text.
SARAP is developed as part of Sharq University's research infrastructure initiative. Its purpose is to support responsible AI-assisted academic research: evidence integrity, transparent research governance and structured institutional research management across Uzbek, Russian and English scholarship.
SARAP is designed for institutional research practice rather than general-purpose generation. Each principle is expressed in the platform as a recorded state, not as a promise.
Research writing starts from screened sources and structured evidence records — not from unsourced text.
AI output carries no academic authority until a named researcher evaluates, edits and verifies it.
A project cannot be recorded as complete without a supervisor decision on academic quality.
Every recorded object keeps its origin, its decision history and its current verification state.
Literature discovery and source selection.
Evidence extraction, structuring and research-gap analysis.
Research problem, objectives, questions, hypotheses and methodology.
Evidence-grounded manuscript development with claims and citations.
Research integrity, citation integrity and methodological consistency.
Supervisor-governed research completion and institutional record.
Stages advance on recorded researcher and supervisor decisions — never automatically.
SARAP was conceived and initiated by Sherzod Atamuradov, PhD, Associate Professor, Rector of Sharq University, who serves as the concept author and project lead.
Concept Author and Project Lead of SARAP
Explore how SARAP connects research evidence, academic reasoning, verification and institutional governance across the research lifecycle.