Our approach
Why vertical AI
Our thesis in three sentences: General-purpose chatbots don't meet the accuracy bar of regulated professions. Every field demands its own product — its own corpus, procedure and data-sovereignty rules. Those products are built on one backbone, under one parent company.
01The difference
General model vs dedicated system
| Dimension | General chatbot | Kızılelma vertical |
|---|---|---|
| Knowledge source | Internet average; date unclear | The field's real corpus, refreshed daily |
| Accuracy | Convincing but unverifiable | Every sentence tied to a source; unverifiable isn't written |
| Personal data | Sent abroad as-is | Masked in Türkiye; the model sees de-identified text |
| Responsibility | An "I'm an AI" disclaimer | Expert approval flows in the architecture; full audit trail |
| Professional language | Generic; terminology errors | Trained and tested in the field's own language |
We do use general models — wrapped in a domain corpus, a verification layer and a data-sovereignty shield.
02Parent strategy
Prove, carry, repeat
Every vertical passes the same three stages: build the field's corpus, prove the trust architecture, refine the product in the field. The cycle completed in law now restarts in health and accounting — not from scratch, but on a proven backbone.
- Shared backbone — corpus processing, citation verification, masking, agent framework — built once, used in every vertical.
- Domain experts inside — every vertical advances with its own professional advisors; the field decides the product.
- Independent brands — each vertical grows under its own name; the parent carries trust and engineering standards.
SERVICE AGREEMENT
Clause 7 — Either party may terminate this agreement upon 30 days written notice …
Clause 12 — Liability is capped at the fees of the last 3 months…
Representative interface
03Why Türkiye
Data sovereignty is a market advantage
For global AI players, Türkiye is a "region option"; for us it is home ground. An architecture that honours the spirit of KVKK — never letting personal data leave the country unmasked — is a commitment foreign providers structurally cannot make. In professions built on privilege, that difference comes before any feature list.
The same architecture also carries us outward: our engine is designed jurisdiction-independent, for markets that care about data locality as much as we do. First we go deep in Türkiye; then we take the same sovereignty story across borders.
See the thesis in the field
The best proof is a live product: explore Kızılelma AI Law, or let's talk about your own field.