01 / Reskilling
PACE
Precision AI Capability Engine
Conventional training teaches you about AI. PACE evolves you with it. Practice-based episodes, generated continuously, tuned to your cognitive shape and the work you actually do.
Live demo · PACE
Learner profile · researcher-027
NEXT EPISODE
EP-001
Calibrating model uncertainty against a noisy assay
Validation capability · Confidence calibration
TWELVE COGNITIVE DIMENSIONS
- Critical reasoning62
- Validation capability54
- Error detection47
- Judgement under uncertainty58
- Cross-domain synthesis71
- Ambiguity tolerance49
- Problem decomposition66
- Evidence weighting52
- Counterfactual thinking44
- Confidence calibration38
- Abstraction control60
- Skill transfer56
Indicative interaction. Live scores are illustrative; the production platform publishes its retention metrics openly.
Adaptive episodes, not phased instruction
PACE is built around a simple inversion. Conventional training proceeds through curriculum: chapter one, chapter two, assessment. PACE proceeds through episodes. Each episode is a short, hands-on practice scenario generated for you, based on your current skill profile and your target skill profile.
Between episodes, PACE updates its model of you. It identifies the cognitive abilities where AI complements you and the ones where AI risks displacing you. The next episode is generated to strengthen the complementary relationship — and to surface the displacement risk before it becomes invisible.
Twelve cognitive dimensions, published openly
PACE measures retention and growth across twelve cognitive dimensions, including critical reasoning, validation capability, error detection, and judgement under uncertainty. We publish the metrics openly, not as a marketing exercise but because this is how the field should work.
Public launch June 2026
PACE will launch publicly in June 2026, free to access for feedback. The first cohort focuses on scientists and engineers working in regulated life sciences and digital health. Join the waitlist to be in the first cohort.