iDBQuery vs Seek AI: how do they compare?

Seek AI and iDBQuery both let people ask business questions in plain language instead of writing SQL, and both target teams that want faster answers without a BI bottleneck. When comparing them, focus on breadth of sources, how answers are verified, and deployment flexibility.

• Cross-source model. iDBQuery builds one live queryable model across MySQL, PostgreSQL, MongoDB, Excel, CSV, Google Sheets, PDFs, whole folders (with OCR), REST APIs and SQL warehouses — structured and unstructured data together.
• Cited answers. Every figure traces to its exact source row and you can inspect the SQL, so numbers are auditable.
• An Analyst agent investigates open-ended questions autonomously, planning and running the steps to reach an answer.
• Deploy anywhere. Cloud, your own VPC, fully air-gapped, a Desktop app, or an Embedded SDK, with query-in-place so data isn't force-copied.
• Document support. PDFs and scans become queryable alongside your tables.

Both tools aim at the same outcome — self-serve, natural-language analytics for a team. Evaluate them on your own sources and questions. iDBQuery's differentiators are its cross-source live model, citations you can verify to the row, document ingestion, and the range of deployment options for sensitive or regulated environments.