One platform. Every source you have.
iDBQuery connects your databases, spreadsheets, PDFs and APIs and lets you query all of it in plain language. One live model, cited answers, no warehouse project.
Six systems
- customersPostgres48,210 rows
- ordersMySQL212,884 rows
- invoices.xlsxExcel9,640 rows
- ticketsMongoDB31,402 docs
- contractsPDF · OCR1,180 pages
- billingREST API17,250 records
One live model
joined on shared keys — every row askable in plain language
One platform, connected end to end.
One live model from everything you have.
MySQL, Postgres, Mongo, Excel, CSV, PDFs and REST APIs — iDBQuery connects them and builds a single queryable model. No warehouse project. No pipelines.
How connecting works →Ask in plain language. Get a cited answer.
Ask a question across every connected source. Every number traces back to its source row, and you can see the exact query behind any figure. Conversations persist with full audit logging.
It understands cryptic schemas.
A semantic layer maps obscure table and column names to plain business meaning, so iDBQuery answers correctly even when your database was never built to be readable.
Dashboards and shareable reports.
Turn one answer into a live dashboard or a shareable report. Filters bound as parameters at query time. Stat tiles, charts, tables, calendars, maps, and AI-native forecast and anomaly widgets.
Reports and dashboards →An autonomous Analyst agent.
Hand a question to the Analyst and it investigates on its own — across every source — and ranks what matters by impact, with the evidence behind each finding.
Meet the Analyst →Document intelligence.
PDF, Word and Excel files are indexed page by page. Ask a question and iDBQuery returns the answer with the exact file and page it came from, and it joins with your structured data: which contracts have no signed amendment on file?
Cloud, your VPC, or fully air-gapped.
Run iDBQuery where your data already lives. The Desktop app and Embedded SDK keep data local, so nothing leaves your walls. Data residency is set per customer.
Built for the teams that live in their data.
See it on your own data.
Bring a database, a spreadsheet and a folder of PDFs. We’ll run the demo on your real data.
What iDBQuery does, in plain terms
What does iDBQuery actually do?
iDBQuery connects your databases, spreadsheets, PDFs and APIs into one live model and answers questions about them in plain language, returning text, a chart, a table or a live widget — with every figure linked back to the source row it came from.
Read the full answer →Is this a BI tool or a chatbot?
Neither on its own: it queries your real sources like a BI tool and is asked like a chatbot, but unlike a general chatbot it reads only your data and cites it, and unlike a BI tool it needs no dashboard built in advance.
Read the full answer →How long before it answers a real question?
Minutes, not a project. You connect a source with credentials, iDBQuery introspects the schema and builds the model, and you can ask it something straight away — there is no warehouse to stand up and no pipeline to author first.
Read the full answer →What can I do with an answer once I have it?
Pin it to a live dashboard, schedule it as a report that emails itself, hand the question to the autonomous Analyst to investigate further, or export it to PDF, Excel or CSV. Every one of those keeps the source links attached.