About AId Core Solutions

One focused health AI company. One core competence.

We build AI systems that turn health data into actionable clinical and operational intelligence, helping healthcare institutions make earlier, more structured decisions and extending that intelligence to the people who need it most.

Why We Exist

Half a billion people live with diabetes. Most of their complication risks sit unread in hospital databases.

Globally, over 90% of diabetic kidney disease goes undiagnosed. Nearly 70% of retinopathy cases are missed. Neuropathy, cardiovascular risk, and metabolic decline progress silently, not because the data doesn't exist, but because no one has time to look.

We built AId Core Solutions to turn routine clinical data into structured risk intelligence so hospitals don't have to choose between thoroughness and scale.

Our Approach

What we don't do matters as much as what we do

We don't

Build generic AI platforms that do everything poorly
Replace clinical judgment with autonomous diagnosis
Require your data to leave your network
Chase model accuracy without workflow fit
Make claims before we have clinical evidence

We do

Focus exclusively on diabetes complication risk
Build decision-support tools that clinicians actually use
Deploy on-premises with zero data egress
Design for hospital workflows first, model architecture second
Validate on real patients before shipping anything

Who We Are

Where the team comes from

Engineering & AI

Co-founded by İTÜ-alumni engineers with deep experience in multimodal AI systems, clinical data pipelines, and production-grade ML deployment.

Academic Research

Doctoral-level academic advisors in health AI, ophthalmic sciences, and biostatistics. Active student researchers contributing to ongoing R&D.

Clinical Validation

Active ethics-approved clinical validation with hospital partners. Built for real hospital workflows, not lab conditions.

Our Portfolio Logic

Three solutions, one shared intelligence layer

Every solution we build draws from the same core capability: synthesizing health data into structured, actionable intelligence. The difference is the application domain and the audience.

Clinical Layer