How We Built DataQuery, Our AI-Powered Reporting Platform
Most businesses are sitting on more data than they know what to do with. The information is there, but getting a clear answer out of it usually means waiting on a developer, an analyst, or a spreadsheet that only one person fully understands.
DataQuery is our answer to that problem. It is a no-code reporting platform that lets non-technical people ask questions of their data in plain English and get back clear charts, dashboards and scheduled reports. No SQL, no analyst queue, no fragile spreadsheets.
Ask a question, get an answer
The core idea is simple. Instead of writing a database query, you type a question the way you would ask a colleague. "How many enquiries did we get last month, by source?" or "Show me revenue by region this quarter."
Behind the scenes, AI translates that question into a precise query, runs it against your connected data and returns the result as a chart or table. The person asking never sees the query. They just get the answer.
Reports that arrive on their own
Answering a one-off question is useful, but most reporting is repetitive. The same numbers, every week or month, for the same people.
DataQuery lets you save any result as a reusable report block and schedule it. Once it is set up, a polished PDF report is generated automatically and delivered by email on whatever cadence you choose. The work happens once, and the reports keep arriving.
Built for people who do not write code
This was the hard constraint throughout. The people who most need quick answers from their data are often the least able to write a query for it.
So every part of DataQuery is designed for non-technical users. Connecting a data source, asking a question, building a report and scheduling delivery all happen through a visual interface. The technical complexity is hidden, not passed on to the user.
AI used carefully, not as a gimmick
It would be easy to bolt a chatbot onto a dashboard and call it AI. We were more interested in using AI where it genuinely removes friction.
In DataQuery, AI translates plain English into accurate queries, validates those queries before anything is shown, and writes plain-English summaries of what a report actually means. The aim is not novelty. It is to let someone get from a question to a trustworthy answer without needing technical help.
AI can be added to almost any project
DataQuery is built around AI from the ground up, but that is not the only way to use it. The same techniques can be added to systems that already exist.
A natural-language search across your own content. A feature that summarises long documents. A tool that drafts replies, classifies enquiries, extracts data from PDFs, or answers customer questions from your own knowledge base. In most cases, AI can be layered onto an existing product without rebuilding it.
The key is treating AI as a feature with a clear job, not a buzzword. Done well, it quietly removes a specific, repetitive task that used to need a person.
Thinking about AI for your own project?
Whether you are building something new or want to add intelligence to a system you already run, we can help you work out where AI genuinely adds value and where it does not.
If you have a project in mind, we would like to hear about it. Contact us to talk about integrating AI into your product.