About Us
Decision Clarity exists because the tools for rigorous thinking should not be reserved for those with the biggest budgets.
Our Mission
The methods behind Decision Clarity are not new. Structured analytic techniques, probabilistic forecasting, Bayesian updating, and causal reasoning have been developed and refined over decades in intelligence analysis, clinical research, and policy evaluation.
What is new is making them accessible. These tools have historically required specialized training, expensive software, or institutional backing. Decision Clarity wraps them in a conversational interface that anyone can use, without sacrificing the rigor that makes them valuable.
The platform uses a chat-first design that toggles to a structured decision engine when questions involve predictions, tradeoffs, or uncertainty. Simple questions get simple answers. Complex decisions get the analytical depth they deserve.
Every analysis comes with visible reasoning chains. No black boxes.
Built on established analytical frameworks from intelligence and research communities.
Designed for people who need powerful tools, not people who already have them.
A normative firewall separates facts from values. The platform informs your decisions without making them for you.
The Team
CTO & Technical Advisor
Berlin, Germany
Daniele is a data scientist and behavioral cognitive scientist with a PhD and a research position at Humboldt University Berlin. His expertise spans machine learning, deep learning, Bayesian statistical methods, and the cognitive science of human decision making, a combination that directly informs Decision Clarity's engine design and its approach to presenting uncertainty in ways people can actually use.
His research background in numerical cognition and decision making under uncertainty shaped the platform's analytical framework, from prior selection and validation to the design of user-facing outputs calibrated to human comprehension. He previously developed an AI system designed to identify and modify harmful language patterns in interpersonal communication, demonstrating applied experience in building AI tools that serve real human needs with care and precision.
Daniele serves as the technical co-architect of the decision engine, leading the Bayesian specification work, prior validation methodology, and the planned integration of validated psychometric instruments into the platform's intake process.
Founder & Director
South Carolina, USA & Amsterdam, NL
Katherine is the founder and architect of Decision Clarity. Her work sits at the intersection of civic technology, decision science, and AI accountability. She identified the decision intelligence gap after experiencing firsthand how consumer AI tools fail people during high-stakes, time-sensitive situations, while institutions have access to far more sophisticated analytical infrastructure.
She brings a distinctive combination of pattern recognition, systems thinking, and practical business execution. Before Decision Clarity, she built and scaled En L'Air Dancewear, achieving top seller status through strategic positioning and operational discipline. Her background includes commercial real estate management, international business operations, and deep engagement with the European civic tech ecosystem.
Katherine designed Decision Clarity's core architecture and built the working prototype using AI-assisted development, demonstrating that the system's core concepts are viable and functional. The architecture features Bayesian updating, causal inference, evidence grading, and a normative firewall that enforces the structural separation of facts from values.
LinkedInLegal Counsel & AI Governance Advisor
United States
Mark is a product liability attorney and technology developer, and the founder of Grounded DI LLC. His work focuses on complex litigation, risk analysis, and the development of deterministic AI frameworks for real-world decision environments.
His dual expertise in law and AI system design makes him uniquely positioned to advise on Decision Clarity's governance architecture, including the normative firewall's legal defensibility, provenance logging requirements, and the platform's safety and misuse policy framework. He brings practical experience building deterministic AI agents with structured, auditable reasoning, directly aligned with Decision Clarity's commitment to transparency and accountability.
LinkedInDecision Clarity is in active development. We welcome conversations with funders, researchers, civic technologists, and anyone who believes decision support should be accessible to all.
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