Launching the "Avner Platform": A Personal Note from Dr. Yiftach Golov

Have you ever wondered what connects a biophysicist with innovative technologies that support the rehabilitation of wounded IDF veterans?
I am proud and excited to lead Avner, an advanced, purpose-built AI initiative that helps veterans with service-related disabilities understand and access their rights and benefits. The "Avner Platform" is now being launched by the IDF Disabled Veterans Organization.
I initiated Avner together with Idan Kaliman, Chairman of the IDF Disabled Veterans Organization. Our guiding vision was to create a personalized, precision-driven system, inspired by the advanced approach used today in medicine and biotechnology: Precision Medicine.
This national project grew out of two defining aspects of my identity:
- I hold a PhD in biophysics.
- I am an IDF veteran with a service-related disability.
The combination of these two perspectives enabled me to develop a technological response to the complex challenge of navigating rights and benefits—a body of knowledge that has evolved over the years into an intricate maze.
Knowing what support you are entitled to is a foundational step in every wounded veteran's journey toward rehabilitation and growth. This makes developing a system of this kind profoundly important. Through more than a year of collaborative planning, research, and development with Avner Golan, Head of the Organization's Rights and Benefits Department—a source of genuine human intelligence on the entitlements of security forces personnel and disabled IDF veterans—I developed the architecture and scientific engine that form the system's computational core. Together with our partners, we built an infrastructure that connects complex professional knowledge with each veteran's individual profile.
To give a sense of the challenge's complexity, the computational engine incorporates:
- Computational biology models: ontology-based architecture, taxonomy, deep learning.
- Hundreds of raw sources, refined into 2,380 vector building blocks.
- A three-phase pipeline: Source Knowledge, Personal Profile, Precision Matching.
- Multidisciplinary clusters: over 10 classification criteria, ~1,750 ontological nodes.
Computational biology
Ontology, taxonomy, deep learning
Raw sources
2,380 vector building blocks
Three-phase pipeline
Source → Profile → Matching
Multidisciplinary clusters
10+ criteria, ~1,750 nodes
The breakthrough is what this makes possible: through a simple conversation on a phone or computer, the Avner Platform helps disabled IDF veterans discover entitlements they may never have known to ask about, understand what is relevant to their circumstances, and identify the next step toward claiming them. The guidance is personalized and precise, with no prior knowledge required—a personal compass for navigating the complex rehabilitation journey.
For me, this system represents far more than technology and science. It highlights the distinctive strength of the Zionist spirit, the State of Israel, and the IDF: the human element. It represents a genuine transformation—a new era of personalized rehabilitation management for a community that now numbers more than 80,000 wounded veterans.