AI Models in Turkish Law: Is AI That Understands Legal Texts Possible?

Turkish legal texts contain long sentence structures, references to legislation, exceptions, joint-and-several concepts, old and new terms, institution names, and complex document formats.

Why are Turkish legal texts difficult?

For this reason, a general-purpose AI model may not always produce sufficiently accurate results on Turkish legal texts.

What does it mean to understand a legal text?

For an AI system, understanding a legal text is not just reading the words. The system must be able to distinguish the parties, obligations, exceptions, deadlines, authorities, underlying articles, and outcomes. For example, even if a contract does not contain the phrase "right of termination," it should be able to understand that the contract will end in the event of a specific breach.

What data is needed for Turkish legal AI?

Legislation, court decisions, contracts, petitions, administrative decisions, trade registry records, and corporate legal documents are important sources for developing Turkish legal AI systems. However, data quality, currency, source reliability, and personal data cleaning are decisive in this process.

Why is RAG important?

For AI in law, relying only on the model's memory is risky. The RAG approach ensures that the model bases its answer on specific documents and sources. This way, the user can see both the answer and the text on which the answer is based.

Hallucination risk

AI systems can sometimes present non-existent decisions, incorrect legislative articles, or erroneous interpretations as if they were real. In law, this risk is greater. For this reason, citing sources, using up-to-date data, and human oversight are fundamental requirements.

How should an in-house legal assistant work?

A good legal assistant should work on the organization's own documents, contracts, and knowledge sources, and provide document-based, sourced answers to the user. In addition, since different users may have different access rights to different documents, role-based access should be supported.

The InfinityQ approach

PrivateGPT can help organizations run secure question-and-answer and analysis processes on their own legal documents. Lexentra, on the other hand, offers specific use cases in more structured corporate legal processes such as signature circulars and the trade registry.

Conclusion

AI that understands Turkish legal texts is possible; but this requires not just a large model, but the right data, up-to-date sources, a RAG architecture, security, and oversight by legal professionals.