Legal & Immigration
AI assistant for immigration law
A multilingual mobile assistant explaining residence permits, work permits and immigration procedures for foreign nationals living in Türkiye.

- assistant
- Çok dilliassistant
- answers cite legislation
- Kaynağa bağlıanswers cite legislation
- mobile app
- iOS · Androidmobile app



In short
Can a legal AI assistant give wrong information?
Neuros constrained the assistant to work only over verified legislative sources: where there is no source, it produces no answer and directs the user to the official authority. Procedures were turned into step-by-step checklists and offered multilingually, so a user sees which document to submit in which order in their own language. Because wrong information here means a lost right, the constraint comes before the coverage.
01Challenge
The legislation is complex, official sources are written in heavy legal language and most exist only in Turkish. Users do not know which document to file or in what order — and wrong information costs real rights.
02Approach
The assistant is grounded strictly in verified legislative sources: with no source it does not answer, it refers the user to the official authority. Procedures became step-by-step checklists, served multilingually.
03Outcome
A user asking in their own language gets process steps and a document list, shortening preparation before any professional consultation.
Technology stack
- 01Flutter
- 02Node.js
- 03LLM + RAG
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No. The assistant shows what the legislation says and which steps a procedure consists of; it does not offer case-specific interpretation or advice. That separation is kept in the interface as well: every answer shows the source it rests on, and when a user reaches an actual decision point they are directed to the competent authority or a legal adviser. The aim is not to replace advice but to make the visit better prepared.
The assistant reads from the source set it is connected to rather than from the model's memory, so updating means updating the source, not retraining the model. Every answer carries which text and which dated version it rests on. That design keeps an outdated answer from quietly staying in circulation after the law changes.
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If you're facing something similar, we'll walk you through how we'd approach it on the first call.