Archives
Are Dead.
Knowledge
Is Alive.
KELIR is a hybrid neuro-symbolic AI built for strict institutional environments. It doesn't just search PDFs; it enforces administrative logic.
KELIR is a hybrid neuro-symbolic AI built for strict institutional environments. It doesn't just search PDFs; it enforces administrative logic.
Before a single query is run, raw institutional decrees are processed entirely offline. KELIR utilizes advanced Natural Language Processing pipelines to extract entities, perform chunking, and map structural logic.
It splits data into two realms: semantic embeddings for the Vector DB, and strict relational mapping for the Neo4j Knowledge Graph.
When an authorized user queries the system, KELIR doesn't just guess. It performs a semantic search to find relevant context, while simultaneously traversing the knowledge graph to ensure those rules haven't been superseded by newer laws.
This hybrid approach guarantees that the Retrieval-Augmented Generation (RAG) output is structurally bound to legal reality.
Zero hallucinations. We engineered a strict Human-in-the-Loop validation queue. AI outputs are quarantined until cryptographically signed by an Archivist.
"Berdasarkan SK Rektor 2025, mahasiswa Bisnis Digital wajib melaksanakan magang 1 semester (20 SKS)."