The Q-Sensei approach
Q-Sensei provides a new foundation for intelligence, helping users move beyond fragmented AI systems to intelligence that is more efficient, precise, and trusted.
A foundation built for understanding
Long before today’s LLMs, Q-Sensei was working on a problem that is increasingly important to AI: how to understand information, retrieve what is relevant, and surface meaningful insights when users cannot fully articulate what they need.
Q-Sensei developed a patented approach that describes objects through attributes and their associated kinds, enabling progressive, guided discovery. This helps users explore information, uncover connections, and build a deeper understanding of how data relates.
Today, those same principles give both users and AI a richer foundation to work from. By connecting data with context and relationships, Q-Sensei helps users explore information more effectively and enables AI to move beyond generating answers to understanding the information behind them—supporting greater precision, better traceability, and more efficient data processing.
Complex information
Attributes & relationships
Connected discoveries
One engine for connected intelligence
Today’s AI stack is fragmented across data platforms, search, vector databases, graph technologies, analytics, LLMs, and agent frameworks.
The AI Data Engine connects these capabilities in one integrated engine, spanning the data foundation, indexing, graph-based reasoning, AI models, and delivery through the Native Analytical Interface and APIs.
At its core are two proprietary technologies: the Multi-Dimensional Analytical Index, which captures content, attributes, entities, relationships, and context, and the Neural Graph Processor, which reasons across relationships, constraints, conditions, and business rules.
Together, they connect structured and unstructured data with the context AI needs to understand what is happening, why it is happening, and what should happen next.
Multi-Dimensional Analytical Index
Neural Graph Processor
Proactive intelligence
Most AI systems respond when someone knows what to ask. The AI Data Engine is designed to continuously analyze information to identify patterns, anomalies, relationships, and emerging issues—including things nobody thought to search for.
This moves AI beyond simply answering questions toward helping users discover what matters, recognize what is changing, and act with greater awareness.
Responsible AI
Responsible AI starts with trustworthy information. The AI Data Engine provides AI access to trustworthy, connected, contextualized data while applying the policies, constraints, and permissions that govern how that information can be used.
This helps AI distinguish what is known, what is relevant, and what it is permitted to do—supporting more precise, transparent, and accountable decisions and actions.
Give AI the context to go further
Discover how connected data and context can support more precise and responsible AI.