Provides a virtual knowledge graph platform that integrates fragmented data sources, enabling organizations to perform optimized big data queries and derive explainable insights without data migration. This system reduces operational costs, minimizes human error, and supports applications in fields like drug discovery and financial compliance by offering fully auditable reasoning and traceable results.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations struggle to integrate and query data spread across disparate databases and schemas, leading to complex data pipelines and hindering efficient data analysis. Traditional data migration processes are time-consuming and costly, often requiring specialized expertise and resulting in data silos.
Solution
Prometheux offers a virtual knowledge graph platform that enables organizations to perform optimized big data queries and derive explainable insights without migrating data. The platform connects to fragmented data sources, allowing users to formalize business logic and enrich datasets with new information. Its reasoning engine applies business logic to the data, eliminating the need for complex database queries. The platform provides a complete reasoning trace, enabling users to audit the logic and data used to derive results.
Target Audience
The primary customers are data scientists, analysts, and researchers in industries such as finance and pharmaceuticals who need to query and analyze data from multiple sources.
Features
- Virtual knowledge graph creation from disparate data sources without data migration
- Optimized big data queries across multiple databases and schemas
- Formalization of business logic using a self-describing language
- Reasoning engine to enrich datasets with new information
- Auditable reasoning trace for understanding how results were derived
- Support for financial network analysis, drug discovery, and general data processing