A returns request sits in a ticket queue for two days. Asking in chat returns 184, with no ticket filed.
Skip the queue
Someone asks how many orders came back last month. They get the number before the meeting — no ticket, no wait.
Ask your database in plain English. Get a trustworthy answer, see the SQL that produced it, and verify the rows behind it. Tell it when it’s wrong, and it learns from your feedback for next time.
200 free questions a month Read-only by design Learns from your feedback
Someone in ops asks
“What was revenue by region last quarter?”
BeyondQueries first wrote SUM(o.total) as revenue. An analyst flagged that this counts refunded orders, and corrected it to SUM(o.total minus o.refunded). Once the correction was approved, later revenue questions on this database start with it applied.
Illustrative example. The correction cycle is how the product works.
Questions answered
People using it
Answers rated
Every company has a few people who can write SQL and a line of people waiting on them. The data was never the hard part. Getting to it is.
A returns request sits in a ticket queue for two days. Asking in chat returns 184, with no ticket filed.
Someone asks how many orders came back last month. They get the number before the meeting — no ticket, no wait.
Ops, sales and customer success all used to wait on one analyst. Each of them can now ask the database themselves.
The few people who can write SQL stop being a help desk. Everyone else asks the database themselves.
A generic tool reports $1.24 million by summing order totals. BeyondQueries subtracts refunds, because that is what revenue means here, and shows the SQL.
A generic AI doesn’t know that revenue means paid orders minus refunds. You see the SQL, so a confident wrong number can’t hide.
BeyondQueries sits between your question and your database. It writes the SQL, checks it is safe, runs it read-only, and answers in plain English, with its work shown.
Point it at PostgreSQL or MySQL with a user that can only read. Nothing is copied or synced.
Switch off any table or column, like phone numbers or CNICs. Hidden means the AI never sees it.
Write short notes once: what revenue means, which orders to ignore, which date to report by.
Type the question the way you'd ask a colleague. Follow-up questions keep the context.
Every answer comes with the SQL that ran and the rows behind it. Nothing is hidden.
On team plans, flag a wrong answer and say why. Once a reviewer approves the fix, similar questions use it.
A plain-English answer, the SQL that produced it, and the rows themselves — side by side, so the analyst and the operator can both trust it.
Show me the top 5 customers by revenue this month
Here are the top customers by revenue for this month.
| name | revenue |
|---|---|
| Acme Corp | $125,430 |
| TechStart Inc | $98,210 |
| Global Systems | $87,540 |
Written for whoever asked, not for whoever maintains the schema.
Shown by default, never hidden — so it can be checked and corrected.
Formatted tables with the tables touched and the time taken.
Row count, the tables touched, and how long it took — so a result is never a black box.
One click hands the exact query to anyone who wants to run it, tune it, or drop it straight into a report.
A plain text-to-SQL tool starts from zero on every question. BeyondQueries starts from what your people have already written down and already corrected.
Write down once what your terms mean. Every query after that follows them.
“Revenue” means paid orders minus refunds
Returns are counted by the date they came back
Test and cancelled orders never count
On team plans, anyone can flag an answer and say why. A person approves the fix, and similar questions use it from then on.
Nothing changes without a person signing off
The same mistake doesn't come back next week
No model is retrained, so nothing drifts
How a correction travels
Letting an AI near your database should be an easy yes. Every query is checked before it runs, and anything that could write, delete or read a hidden column is stopped with the reason.
Every query is parsed before it runs, and you connect with a read-only user. Two locks, not one.
Columns you switch off are left out of everything the AI receives, and any query naming one is refused.
Database passwords and AI keys are encrypted at rest and never shown again after you save them.
On team plans, five roles from Owner to User, granted database by database.
What the guard does with each query
Refusal messages are the guard’s exact wording. Read how your data is handled.
Start on your own with one database. Bring your team in when the questions outgrow you.
Founders, shop owners, operations leads. You have a database and a question, and no time to learn SQL or wait for someone who knows it.
Ask in plain English, get the answer yourself
See the SQL, so you know it counted the right thing
Free plan, no card needed
Managers and stakeholders ask for themselves. The people who know the schema write the notes once and approve fixes, instead of pulling numbers all week.
Everyone asks directly, nobody files a ticket
Roles per database decide who sees what
Wrong answers go to a review queue, not a group chat
With follow-ups that keep context
Copy it with one click
Real results, not summaries
One SELECT or nothing
Never sent to the AI
Your terms, applied to every query
Every question, kept
Take the rows anywhere
Fix a wrong answer once
Owner, Admin, Editor, Analyst, User
More databases coming
OpenAI, Anthropic, Gemini, Bedrock, Azure, Ollama, vLLM
Connect a database with a read-only user and ask your first question. The Free plan includes 200 questions a month and needs no card. Upgrade when you need more.