Equitus KGNN is an automated data unification platform in the knowledge graph and AI data infrastructure category. It is designed for enterprise organizations seeking to ingest, structure, and contextualize large volumes of structured and unstructured data without relying on traditional ETL processes. KGNN automates the transformation of disparate enterprise data into semantically enriched, AI-ready knowledge to support use cases such as analytics, business intelligence (BI), and generative AI (GenAI) deployment.
Equitus KGNN uses a combination of natural language processing (NLP), machine learning (ML), and semantic technologies to dynamically build a self-constructing RDF knowledge graph. This semantic core enables organizations to extract entities, relationships, and contextual meaning from raw data—including documents, logs, and databases—and transform it into structured, vectorized formats optimized for advanced analytics and AI model consumption.
Equitus KGNN is suited for:
Enterprises operating across fragmented data systems.
Organizations needing contextualized data for AI, BI, or compliance use cases.
Teams looking to unify legacy and modern systems without redesigning infrastructure.
Key Capabilities:
Automated Data Ingestion: Handles structured and unstructured sources without manual pipelines.
Semantic Auto-Mapping: Dynamically generates a schema-less RDF knowledge graph.
Federated Integration: Enables bi-directional data exchange across legacy and modern platforms.
Real-Time Vectorization: Prepares data for AI models, RAG/CAG pipelines, and vector search.
Governance and Provenance: Maintains full data lineage, security, and compliance controls.
Benefits:
Reduce reliance on manual data engineering by 80%.
Minimize latency with near real-time data processing.
Improve AI accuracy and explainability through contextual enrichment.
Ensure compatibility with secure, on-premise, or air-gapped environments.
Minimum System Requirements:
IBM Power10/11
40 Cores
512GB RAM
4TB SSD (usable)
RedHat OpenShift 4.18
X86/GPU
24 Cores
256GB RAM
Nvidia GPU with 24GB+
4TB SSD (usable)
RedHat OpenShift 4.18
Equitus KGNN is built for scalability, edge-readiness, and enterprise-grade deployment, enabling seamless data unification across the full lifecycle of AI and analytics initiatives.
