About Confidentia

Reality Signal is built by a team that helped shape modern uncertainty quantification — with scientific founders and advisors who turned the theory into tools that work in production.

A reliability company for AI decision systems

From raw scores to optimized decisions.

Confidentia AI Inc. exists for one simple reason: raw model confidence is not a probability. When teams threshold on uncalibrated scores, they silently accumulate cost — through over-automation, unnecessary escalation, or expensive mistakes.

Reality Signal turns model outputs into true probability + uncertainty so AI engineers can route decisions with clarity, defend outcomes, and monitor reliability over time.

World‑class expertise in uncertainty quantification

Over 75 years of combined experience across industry and academia.

CEO • Serial entrepreneur
Built and scaled multiple software companies, including products acquired in telecom and enterprise software. Brings a product-first mindset to making reliability usable for engineers.
CTO • Reliable ML research & deployment
Bridges research and production: applied AI reliability in high-stakes environments and academic work on reliable machine learning.
Head of B&D • Applied AI leader
Led AI initiatives across healthcare and industrial settings, focusing on measurable outcomes, adoption, and governance.
Scientific Board

Prof. Vladimir Vovk — a pioneer in uncertainty quantification and probability-based prediction.

Prof. Alexander Gammerman — a founding figure behind conformal prediction and its practical use for reliable ML.

What this means for customers
You get decision-grade outputs you can build policies on — not vibes. Our focus is engineering reality: latency budgets, auditability, drift, and the economics of routing.
  • • Calibrated probabilities you can threshold on
  • • Uncertainty as a first-class signal
  • • Monitoring for reliability in production