Qlevia provides an operational knowledge platform that builds a semantic graph linking fragmented enterprise data, explicitly modeling entities, relationships, business rules, and dependencies. The unified knowledge graph can be accessed via APIs for AI model integration, delivering explainable results, auditability, and automated actions for large, complex organizations.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprise AI initiatives often fail because operational data is spread across disparate systems, and the contextual relationships, rules, and dependencies that give that data meaning are lost in silos. Without a unified operational knowledge layer, AI outputs cannot be reliably explained, audited, or acted upon in critical business processes.
Solution
Qlevia offers an operational knowledge platform that creates a semantic graph layer linking fragmented enterprise data. By explicitly modeling entities such as people, assets, events, policies, and business rules, the platform preserves the meaning and dependencies of operational information. This structured knowledge graph can be consumed directly by AI models, enabling them to reason, generate explainable results, and trigger automated actions. The platform is built for large, complex organizations and provides a scalable, auditable foundation for integrating AI across multiple systems and workflows.
Target Audience
Primary customers are large enterprises and institutions with complex, multi‑system operations that require trustworthy AI integration, such as financial services, manufacturing, and utilities.
Features
- Semantic graph engine that ingests data from heterogeneous sources and maps it into a unified knowledge graph
- Explicit representation of relationships, business rules, and dependencies to retain operational context
- APIs for AI model integration, allowing direct consumption of the knowledge graph for reasoning and inference
- Built‑in audit trails and provenance tracking to support explainability and regulatory compliance
- Scalable architecture designed for high‑volume enterprise environments with complex operational data