How is iDBQuery used by biotech startups?
Biotech startups use iDBQuery to ask plain-language questions across experimental, sample, spend and program data, getting cited answers in seconds without SQL. It builds one live model across databases, spreadsheets and files and can run air-gapped, so proprietary research and IP stay inside your environment.
Early-stage biotechs generate data across lab databases, LIMS or ELN exports, sample inventories, program trackers and burn spreadsheets. iDBQuery unifies them into one live model so scientists, ops and finance ask plain-language questions and get a cited answer.
Examples:
- What is our cash runway and monthly burn by program?
- Show sample and reagent inventory, and what is running low.
- Which experiments or assays are behind the program timeline?
- What did we spend by CRO/vendor and program this quarter?
- Summarise results across a set of experiment records.
iDBQuery connects lab and program databases, Excel and CSV exports and even PDF reports (with OCR) together with no pipeline, joins them, and cites each figure to source, so board and program reporting is trustworthy. The Analyst agent can investigate an open question across datasets on its own.
Because research data and IP are highly proprietary, deployment leads: run in your own VPC or fully air-gapped, use the Desktop app to keep data local, and rely on query-in-place, RBAC and encryption. iDBQuery makes no certification claims; the value is architectural, proprietary research and financial data stays entirely within your walls while a lean team gets instant, verifiable answers.
Updated 2026-06-22