Built by Those Who've
Done the Work

Beza brings deep expertise in clinical health informatics and the operational realities of implementing digital health at scale across resource-limited settings. Her career has been defined by a clear-eyed focus on the gap between what health technology promises and what it actually delivers in the field, and an unwavering commitment to closing it.

She has led EMR implementation programs across multiple health system tiers, working directly with clinical officers, nurses, and district health administrators to adapt digital workflows to the rhythms of real care delivery. Her experience includes overseeing data quality frameworks, clinical training programs, and system governance structures that ensure EMR investments produce durable, trustworthy clinical records rather than just installed software. Beza brings to ClinicDx an exceptional ability to translate clinical need into system design that clinicians actually use.

Brook brings over a decade of hands-on experience designing, building, and deploying electronic medical record systems across emerging markets. He previously led EMR development and rollout programs that touched multiple countries simultaneously, coordinating with Ministries of Health, international implementing partners, and clinical teams on the ground to bring structured health information systems to facilities that had never had one.

His work spanned the full spectrum of deployment complexity: from configuring OpenMRS in single-clinician community health posts to architecting national-scale infrastructure serving hundreds of facilities and millions of patient records. Brook has a rare combination of technical fluency and implementation realism. He understands not just how to build health technology, but what it actually takes to make it survive contact with the environments it is meant to serve.

Jack brings deep expertise in large language model research and applied machine learning, with a focus on building systems that perform reliably in high-stakes, low-resource environments. His background spans model pretraining, fine-tuning, and evaluation, with particular depth in medical and scientific domains where output quality and factual grounding are non-negotiable.

At ClinicDx he leads the model development pipeline, from dataset curation and training strategy through quantization and inference optimization. His work ensures that ClinicDx-v1 delivers structured, evidence-grounded clinical reasoning on hardware that field deployments can actually afford.

Iddo comes to ClinicDx from a background at the intersection of clinical medicine and health data science. He has worked across health system design, clinical decision support research, and the translation of medical knowledge into computable formats, with a consistent focus on what AI systems need to get right before they are trusted at the point of care.

His contribution to ClinicDx centers on clinical validation, knowledge base integrity, and the design of outputs that clinicians find actionable and trustworthy. He ensures that the system reasons the way a careful clinician would, not just the way a well-trained model does.