How does iDBQuery help researchers and academics?

Research data is famously messy — survey exports, instrument output, spreadsheets, PDF papers and public data APIs, all in different shapes. iDBQuery connects them into one live model so you can interrogate everything together without manual wrangling.

• Ask in plain language — no need to write SQL or scripts for routine cross-tabs, filters and aggregations.
• Document corpora — ingest folders of PDFs and scanned files with OCR, then query their contents alongside your structured data.
• Cited results — every number traces back to the exact source row, which matters when findings must be defensible and reproducible.
• Autonomous investigation — the Analyst agent explores an open question across your sources and returns a cited summary you can verify and cite onward.
• Cryptic variables, understood — the semantic layer captures what coded variable names and column abbreviations actually mean.

Because iDBQuery queries data in place with no pipeline to build, you can move from a fresh dataset to answers in minutes. Provenance is built in: rather than trusting a black-box result, you see exactly which records produced each number, supporting transparent, reproducible scholarship.