Research
Whitepapers, technical blog posts, and collaborative research from the Tiresias team. We believe in building in public and sharing what we learn.
Our foundational whitepaper detailing how the T-score compresses psychographic trait vectors into a universal preference signature - and why it outperforms collaborative filtering by 41% with zero user data.
A technical deep-dive into our approach to the cold-start problem. We show that psychographic trait inference from minimal digital telemetry yields preference predictions that rival systems trained on months of behavioral data.
Early results on using the T-score to predict preferences across entirely unrelated domains - from media consumption to savings behavior and ad response affinity.
An opinion piece on the structural fragility of behavioral data pipelines and why a psychographic-first approach is both more ethical and more predictive than the status quo.
We're always looking for academic partners and industry collaborators who share our interest in psychometric approaches to personalization.
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