Leaders in Situated Reasoning

Our Purpose

To advance the world through scalable situated reasoning

By pioneering systems that can understand context, handle uncertainty, and navigate the open world of possibility, Sirius-beta Labs is redefining what reasoning means.
We are building solutions that reason about both knowns and unknowns, model futures without precedent, and help solve the world’s “blue swans”: events you know are going to happen but how they happen is always different.
What we are Doing

Enabling better decisions in the open world

We are delivering scalable situated reasoning – empowering humans to reason about both knowns and unknowns in the open-world.

We want to model futures without precedent and solve the world’s toughest challenges. 

Our focus: Turning uncertainty into understanding, and possibility into progress.
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The Challenges with Reasoning

Our systems are designed to process complexity — identifying contradictions, weighing incomplete evidence, and surfacing meaningful patterns even when data is unclear or inconsistent.
We don’t rely on static datasets. Our models continuously probe, test, and re-evaluate assumptions, enabling adaptive reasoning that evolves with new information and context.
Complex environments require reasoning that accounts for interdependencies and delayed outcomes. Our approach models how changes propagate through systems, uncovering hidden effects.
True reasoning combines what can be measured with what can be inferred. We integrate structured logic with abstract intuition — bridging quantitative precision with human-level understanding.
The Solution / Technology

A New Framework for Reasoning Intelligence

Sirius-beta Labs is developing a new architecture for understanding — where AI systems interpret not just data, but the world around it.
Our Core Principles:

Open-World Understanding:

Systems that reason beyond fixed datasets to navigate dynamic, real-world conditions.

Contextual Inference:

The ability to assess meaning, relevance, and influence — not just probability.

Scalable Reasoning Systems:

Frameworks that expand and adapt as the world evolves, enabling richer, more flexible intelligence.

What We Do
Our Team

A team built on experience.

Professor Ted Goranson

  • Founder and Principal

Assistant Professor Beth Cardier

  • Chief Narrative Modeller

Adjunct Professor Mathew Hancock

  • Founder and Principal

Dr Naso Evangelou-Oost

  • Senior Mathematician
partnering with the best

Who We Collaborate With

Chief Scientist

Professor Ted Goranson

Ted specialises in cognitive modeling, bringing profound experience from U.S. National Security and Intelligence, notably with DARPA. His work integrates three innovative concepts: an advancement in situation theory, the organizing principle of dynamic narrative causality, and implementable formalisms based on category theory and geometric logics.
Ted’s research spans three key applications: engineering advanced virtual enterprises, understanding cinematic narrative, and remodeling biomolecular dynamics, with impactful results particularly in the realm of advanced virtual enterprises.
Chief Narrative Modeller

Assistant Professor Beth Cardier

Beth’s career has focused on cognitive narratology, the understanding of how the human mind comprehends and processes narratives and extracting mechanisms from stories to expand formal models of reasoning.
She is an expert at creating innovative trust models and has been involved in several collaborative efforts including Disney Research, where she worked alongside renowned context logician Keith Devlin at Stanford, and the Virginia Modeling Analytics and Simulation Center, contributing to the development of a prototype immersive modeling environment based on her methods. Beth has also led research in the interplay between aesthetic design and reasoning.
Chief Risk Modeller

Adjunct Professor Mathew Hancock

Drawing on deep experience in corporate governance, enterprise risk management, and management systems, Mathew is focused on evolving conventional management and decision-making approaches into adaptive, context-aware and continuously optimising systems.
His mission is to chart the course for application of situated reasoning and advanced modelling and AI tools to management systems and decision-making within complex organisations. As the team’s “LLM whisperer,” he is also integrating natural language processing, prompt engineering and agentic methods into the Sirius-beta Labs product roadmap.
Senior Mathematician

Dr Naso Evangelou-Oost

Naso is a mathematician and software designer whose work bridges abstract theory with implementation. At Sirius-beta Labs, he applies valuation algebras, category theory, and sheaf-theoretic methods to develop resilient, scalable systems for knowledge representation and predictive reasoning.
His background in formal methods and concurrent systems informs a principled approach to complex software challenges, with a focus on local-to-global structure, abstraction, and rigorous design.