Overview

TigerGraph’s AI & Machine Learning Solution is a native massively parallel processing (MPP) graph database engineered for enterprise-scale, real-time graph analytics. It enables deep link analytics to power machine learning applications, addressing challenges like feature engineering, data integration, and explainability. TigerGraph’s platform supports creation of rich graph-based features, scalable traversals across billions of nodes, and real-time inference workflows for use cases like fraud detection, recommendation engines, and explainable AI. The platform integrates seamlessly with ML ecosystems and supports full traceability of feature generation to improve transparency and model trustworthiness.

Features and Capabilities

• **Scalable Feature Engineering: **Enables extraction of graph-based features (e.g. node embeddings, small graph patterns) across terabytes of data for real-time ML model input, enhancing accuracy and depth.
• **High-Performance Graph Traversals: **Uses a distributed native MPP engine to traverse multi-hop relationships at scale—ideal for real-time fraud detection and recommendation pipelines.
• **Explainable AI Support: **Captures full lineage of feature generation enabling transparent ML decisions (e.g. why a mortgage was priced higher), with visualization via GraphStudio.
• **Enterprise-scale Integration: **Compatible with popular ML frameworks (PyG, DGL, TensorFlow) and cloud platforms (AWS, GCP, Azure) for seamless end-to-end AI pipelines.
• **Built-in ML Workbench: **Offers a Python-based environment with partitioning, subgraph sampling, batching, node/link prediction and GNN support, accessible via TigerGraph Cloud or on-prem setups.
• **Massive Graph Scale: **Supports billion-node/edge graphs and distributed training, backed by parallel subgraph sampling and graph partitioning for memory-efficient processing.
• **Transparent Logging & Monitoring: **Tracks and visualizes the chain of graph queries and features feeding ML models—ideal for compliance, auditing, or fair decision-making.