Upload credentials, run audits, and explore the sovereign academic verification protocol.
Note: This is a non-production UI demo. Professional verification requires server-side document parsing and signed audit responses.
In 2026, AI-generated synthetic data can produce convincing-but-fraudulent academic credentials. Traditional verification methods — PDF signatures, email confirmations, manual registry lookups — are no longer sufficient against sophisticated deepfakes and document forgeries.
Aegis-Graph combines Agentic GraphRAG with a Multi-Agent Reasoning Swarm to cross-reference credentials against institutional evidence graphs, detect AI-generated artifacts via pixel-level forensics, and produce cryptographically signed audit trails — all without central authority dependency.
"In an era of synthetic data, truth must be sovereign." — ACLAS Sovereign Node Group
Four specialized AI agents collaborate, each handling a distinct layer of the audit protocol, reaching consensus before issuing a final verdict.
Pixel Forensics — detect AI-generated artifacts in digital credentials via pixel-level and OCR-based analysis
Stage 1Graph Navigator — cross-reference with institutional evidence using local index + ROR lookup
Stage 2Logic Auditor — evidence-weighted consistency checks for registry status, timelines, and blacklist aliases
Stage 3All agents reach consensus before issuing a final Sovereign Audit Certificate
FinalAegis-Graph operates via a collaborative Multi-Agent Reasoning Swarm. Each agent handles a specific layer of the audit protocol, reaching consensus before issuing a final verdict.
Pixel-level & OCR-based AI artifact detection in digital credentials
ROR Node Sync — cross-reference with institutional evidence databases
Chain-of-Thought validation — evidence-weighted consistency checks
All 3 agents reach consensus → Sovereign Audit Certificate issued
Aegis-Graph is fully localized for international adoption, serving academic institutions worldwide with a truly multilingual audit interface.
Governed by the AEGIS-GRAPH Open Governance Board with technical support from the ACLAS Sovereign Research Group.
git clone https://github.com/aclascollege/aegis-graph.git
pip install -r requirements.txt
python main_pipeline.py
If you use Aegis-Graph in your research, please cite it using the BibTeX entry below. This helps others discover and build upon this work.
BibTeX · MIT License
ACLAS develops sovereign, transparent AI tools for the future of education and academic integrity.