The most powerful foundation for machine intelligence is behavioral depth

For business-critical decisions, knowing what people do is not enough. You must be able to anticipate their next move.

Why we exist Founders Careers Privacy & Ethics Brand

Why we exist

In a world of infinite data and ever more powerful AI, the true competitive edge lies not in how much information we process, but in how well we understand human behavior: The choices people make, and the forces that shape what they do next.

Traditional AI systems excel at pattern recognition, but struggle to distinguish signal from noise in the complexity of human life. This is the frontier TRACE was built for.

We believe that the most meaningful foundation for AI isn’t just data, but behavioral depth. A deep, evolving understanding of how people think, feel, and act.

We build living behavioral models: Bespoke AI systems that learn, adapt, and simulate human behavior in real-world contexts. These systems reveal patterns that surveys, dashboards, or static models miss. Capturing not only what people do, but why they do it. Each project feeds a growing behavioral knowledge base, turning every decision into a faster, smarter, and more contextual one.

Just as market data underpins trading, and risk modeling supports engineering, we believe behavioral intelligence will become foundational to high-stakes decision-making; across strategy, product, policy, and innovation.

Organizations that work this way won’t respond to change. They will anticipate it by operating with a continuous, real-time understanding of the people and markets they serve.

Founders

Our founding team brings together expertise in the social sciences with sophisticated AI product-building experience. We’ve led high-impact projects across top consultancies, universities, and technology companies. We unite a deep understanding of human behavior with state-of-the-art AI to create Trace’s AI system.

SebastianCo-founder
PhD in Economics specializing in large-scale behavioral analysis and AI. His career bridges academia and industry, with research positions at the University of Copenhagen and the London School of Economics, and over a decade of experience leading complex data and AI projects for global corporations.
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ThomasCo-founder
PhD anthropologist with over a decade of experience helping world-leading companies uncover the human complexities behind business challenges. He has held research positions at the University of Copenhagen and Harvard University. He has built his career translating rich anthropological insight into commercially decisive strategies.
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JessCo-founder
Data Scientist and Machine Learning Specialist with a Master’s in Software Engineering and more than 15 years of experience developing commercial AI products. He has led large-scale data projects at prominent AI companies, delivering solutions that turn advanced analytics into trusted, decision-ready tools.
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Careers

Join us in building the next layer of intelligence

We’re looking for candidates with backgrounds in fields such as behavioral science, machine learning, computational social science, linguistics, cultural analysis, or related disciplines. Strong analytical skills, intellectual curiosity, and a commitment to real-world application are essential.

If you're motivated by the challenge of bridging human insight and machine intelligence, we invite you to get in touch with info@trace.systems

Data Privacy and Ethics

Data Privacy

Handling sensitive data is core to our work, and privacy and security are built into every layer of our systems. Our solutions are designed to comply with GDPR, emerging AI regulations, and other relevant legislation. Each engagement operates in its own single-tenant cloud environment, protected with AES-256 encryption at rest, TLS 1.3 in transit, and governance aligned with ISO 27001, NIST 800-53, and SOC 2 standards.

Ethics

As social scientists, we consider not only the immediate effects of our work, but its broader effects on people and society.

Our ethical approach is grounded in six principles that shape how we design, build, and deploy our work: fairness is engineered from the start, transparency is built into every process and output, data is representative for the context it models, systems are subject to continuous audit, accountable human oversight is mandatory, and privacy is the default.

We apply the same rigor to ethical considerations as we do to technical architecture – assessing each project individually, adapting to its specific use case and risk profile, and ensuring every engagement stays within both ethical and regulatory boundaries.