Research
Our mission is to expand human capability by transforming organizational efficiency, and empowering individuals to create meaningful impact. We develop the models, agent architectures, and workflow systems needed to make these capabilities reliable in the real world.
Methodology & Principles
Real World Reliability
We study methods to improve the correctness and consistency of AI systems operating under real-world uncertainty.
Transparency & Provenance
We develop frameworks for tracing data lineage and model outputs across the system lifecycle.
Alignment
We investigate alignment techniques that ensure models act in accordance with user intent and task requirements.
Control & Observability
We explore architectures that make system planning, actions, and decisions observable during execution.
Featured papers
March 11, 2026
The Mathematics of Predictive Lead Scoring in B2B Markets
An analysis of how combining firmographic data with real-time intent signals creates a more accurate conversion probability than traditional manual qualification.
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