Unleash the power of graphs. Augment human decisions.
If a graph database is the beating heart of your contextual decision intelligence system, graph analytics and AI are its brain. Together, they deliver unrivaled results to empower data-driven professionals to swiftly cut through the noise of billions of entities and relationships and reveal answers to complex questions - augmenting human decisions with rich and precise context-based insights like never before.
Dive deeper in your data, faster
Leverage high-performance native graph algorithms to accelerate your time to insights in a variety of use cases. Linkurious’ graph analytics and AI capabilities help you uncover outliers, clusters, and trends, hidden deep within complex networks. Quickly optimize resource flows and routes, assess the importance and influence of groups of suspicious transactions and bad actors, or evaluate the resilience of your IT network.
Let your data work for you
Leverage graph analytics to make sense of complex connected data. Detect intricate patterns, identify communities, and enrich your machine learning models with contextual insights. Use these capabilities to enhance prediction accuracy, generate risk scores, detect fraudulent behaviors, and foresee supply chain disruptions or potential cyber threats.
Automate to work smarter, not harder
Simplify the use of graph analytics by automating your graph queries into recurring data enrichment workflows or alerts. Streamline data cleaning processes, enhance the detection of suspicious activities, and gain additional insights effortlessly. Linkurious empowers you to turn complex graph data into actionable intelligence within minutes.
Features
Built-in graph algorithm library
Depending on your graph database, seamlessly access up to 65 advanced graph algorithms like PageRank, community detection, centrality, similarity or pathfinding.
Entity resolution AI
Integrate data from various sources, despite varying structures or formats.
Graph embeddings
Capture the complexity and structure of your graph and transform it for use with machine learning.
Graph-native ML techniques
Link prediction and node classification helps fill in the blanks in your data and predicts changes in the structure of your graph.
Graph based multi-model alerts
Via a user-friendly interface, combine multiple customized graph queries within a single alert to signal sophisticated patterns that would remain hidden with traditional systems and reduce the volume of false positives.