Human-centric AI for optimal, efficient, transparent decision-making.
Standard AI learns patterns to simply model correlations and repeat previous practice. Using the mathematics of causal inference, our proprietary AI derives the mechanisms underlying your data to produce cause-effect insights.
Data in challenging domains such as healthcare is often noisy, sparse, and from mixed sources and different modalities. Our advanced data engineering and infrastructure handles these challenges seamlessly, transparently, and securely.
Following previous practice or gut feeling is suboptimal. Our solutions provide data-driven, cause-and-effect reasoning to compare potential futures and choose the optimal course of action: If I take this action today, what will be the outcome tomorrow?
Chief Executive Officer
International business leader, MBA London Business School
Chief Technology Officer
Expert in human-centric AI systems, founded Latent Sciences (acquired), AI Advisor @ NASA
VP Data Science
Causal inference in healthcare specialist (Intel and Technion)
Uri Shalit, PhD
Professor, Technion Institute
Irit Ben-Aharon MD, PhD
Head of Oncology, Rambam Healthcare
Passionate about innovating in data, healthcare, AI and ML?