Uncertainty quantification and explainable AI for safety-critical decisions
digiLab builds machine learning systems for high-stakes, regulated industries where decision confidence matters as much as accuracy. The tech stack (Python, NumPy, SciPy, React, Docker, AWS) reflects a tight, research-oriented team focused on probabilistic modeling rather than infrastructure scale. Active hiring is concentrated in engineering (6 roles, mostly senior/lead level) with nascent sales and exec functions, signaling a transition from technical founding to repeatable revenue—a shift underscored by pain points around sales operations and turning strategy into execution.
digiLab is an AI company founded in 2021 and based in Exeter, Devon, serving governments and organizations in safety-critical and regulated sectors (clean energy, medical diagnostics, etc.). The core product is The Uncertainty Engine, a platform that combines machine learning with uncertainty quantification to enable high-confidence decision-making when data is sparse, complex, or incomplete. The team includes machine learning specialists and data scientists. Current focus extends to a frontend product (engine designer) and establishing repeatable sales processes. All hiring is currently within the United Kingdom.
The Uncertainty Engine, a platform combining machine learning and uncertainty quantification designed for safety-critical decisions in regulated industries where data is sparse or incomplete.
Python, NumPy, SciPy, React, Docker, AWS, MongoDB, TypeScript, and GitHub for CI/CD—a research-focused stack emphasizing probabilistic computing and web delivery.
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