Enterprise data, queried in plain language.

The challenge

Enterprise data rarely lives in one place, and the people who need answers from it are rarely the people who write SQL.

The client wanted a workspace that connected directly to scattered business data and let non-technical stakeholders ask questions in natural language, without loosening the access controls that enterprise and public-sector buyers expect.

What we built

• Natural-language query engine that turns plain-language questions into SQL and data queries.
• Auto-generated BI dashboards, created and saved from the question itself.
• Document analysis and insight extraction across PDFs, reports, and contracts.
• Direct connections to scattered business data, so teams query sources where they live.
• SSO integration and enterprise RBAC, so each user sees only the data their role allows.

How we delivered it

• Shape. Full-cycle design of the workspace, with SSO, role-based access, and data privacy treated as requirements from day one.
• Prototype. Proofs of concept with enterprise clients and public-sector organizations.
• Build & Integrate. Query engine, dashboard generation, and document analysis connected directly to the client’s business data.
• Deploy. In production with enterprise clients, behind SSO and enterprise RBAC.

The outcome

The workspace is in production with enterprise clients and has been proven in public-sector proofs of concept. Non-technical teams ask a question and get a chart, a dashboard, or an answer drawn from their documents, inside the access controls their organization enforces.

Read more about our AI & ML engineering and data engineering capabilities.

Client details are withheld. A detailed walkthrough is available under NDA on request.