Extracting actionable insights from structured databases in regulated industries, such as credit unions, is often hindered by complex schemas, legacy systems, and stringent data governance requirements. We present Tursio, a secure, on-premises, database search platform that enables business users to query enterprise databases using natural language. Tursio automatically infers a context graph -- a schema-level metadata structure that captures join paths, column semantics, and domain annotations -- and uses it to systematically generate accurate query plans through LLM-assisted compilation, grounding, and rewriting. Unlike existing AI/BI tools that require extensive manual context curation, Tursio automates this end-to-end and deploys entirely on-premises. We demonstrate Tursio through realistic scenarios in the credit union domain, and discuss its applicability to other regulated settings.

翻译：在信用合作社等受监管行业中，从结构化数据库提取可操作的洞察常因复杂的数据模式、遗留系统及严格的数据治理要求而受阻。本文提出Tursio——一个安全的本地化数据库搜索平台，使业务用户能够使用自然语言查询企业数据库。Tursio能自动推断上下文图（一种捕获连接路径、列语义和领域标注的模式级元数据结构），并利用该图通过LLM辅助的编译、接地与重写技术，系统化生成精确的查询计划。与现有需要大量人工上下文管理的AI/BI工具不同，Tursio实现了端到端的自动化流程，并完全部署于本地环境。我们通过信用合作社领域的实际应用场景展示Tursio的功能，并探讨其向其他受监管环境的扩展适用性。