Database and analytics companies are rolling out text-to-SQL tools that let users query databases in natural language, but experts warn non-specialists should be cautious. Toronto University computer science professor Nick Koudas said systems can generate queries that are grammatically correct but not what business users intended. He put current accuracy at about 80 percent, below human experts at around 93 percent, and said company-specific data and jargon are hard for LLMs without extra training.

B2B fintech firm Webcash is moving to secure solutions for the emerging era of AI agent banking, which it sees as a core axis of next-generation financial competition. At a conference in Seoul, it unveiled the architecture and use cases of OPERIA, an engine that connects general-purpose AI with banks’ relational databases. Webcash said internal tests showed 99 percent accuracy in its cash management solution and introduced a V2 cash management agent expanding coverage to about 800 customers.