Grandhoo Causality Analysis System
Empowering decision-making with 'rules', paving a new way for the data analysis frontier.
Interpretability
Using graph theory as the foundation for logical rule deduction, enabling explanations for predictive outcomes.
Rule Discovery
Continuous discovery and accumulation of ‘surprising’ rules and clues hidden from the ordinary view.
Real-time Response
Sub-second response for processing billions of data and supporting additional dimensions of data and a larger data scope.
Security
Logical reasoning and computation based on data features that are safely encrypted, after encrypt processing of user's private data still being able to participate in the computationn.
Digital Transformation Requires
Improved Artificial Intelligence Technology and Related Data
Limitations of Existing Relational Systems
Heavily reliant on the collaboration of data experts and industry experts, making it difficult to discover 'surprise' rules.
AI's associative recommendation results are unexplainable, and the accuracy is low and results are inconsistent.
Relational data management is difficult to fully uncover the implicit value hidden within the massive and multi-source data.
Grandhoo Causality Graph Data
Powerful analytical capabilities can avoid various limitations in manual analysis processes.
Embed multiple machine learning models into logical rules to fully release the value of data.
Based on graph data, ensure that explicit and implicit correlations are accurately and extensively discovered.
Grandhoo Causality
Graph Computing
Utilize graphs as data models, distributed parallel computing for mining the association rules existing within graph data.
Distributed Computing
Support real-time monitoring of the status information of each node to ensure the system reliability.
Logical Rules and Machine Learning
Address issues related to the accuracy of manually formulated rules, enhancing the interpretability of machine learning outcomes.
Offline Encryption
Support users to encrypt data locally, avoiding data compliance issues from the processing flow.
Automated Feature Engineering
Perform data validation, cleansing, and feature extraction on customer data to obtain improved data features.
Optimization of EV Battery Production Processes
High-Precision prediction of EV battery capacity, to optimization of production process flow.
Predictive Maintenance for Electric Vehicles
Discovering the relationships between vehicle sensors, and between sensors and faults.
Identifying Drug-Disease Associations to Facilitate New Drug Development
Discovering potential relationships among a vast number of genes (targets), diseases and drugs.
Customer Churn Attribution and Prevention
Automatically Discovering Patterns of Substantial Customer Churn.
Trading Pattern Rule Discovery
Real-time streaming processing and rule discovery, real-time presentation of indicators and intra-day rule generation.
Precision Lead Generation to Increase Marketing Reach Rate
Combining recommendation rules with operational expertise for more precise lead generation.
Feature Introduction
R&D Achievements Awarded
Based on the International Frontier, Solving Industry Challenges
Promoting Digital Transformation of Enterprises
Driving Decision-Making with Data
Explore the era of Data Analytics 4.0 together