Ask your data in plain English. Get answers you can check.
Business questions become accurate SQL, answers and KPI dashboards, built on your own data warehouse, with every query shown and every access rule respected.
- Built by engineers who've shipped text-to-SQL at enterprise scale
- Every query shown
- Read-only by design
Your dashboards answer yesterday's questions
- Every new question joins the analytics team's backlog.
- Dashboards show what was planned, not what leaders need to know today.
- Self-service BI tools go unused because they still need expert users.
- Generic AI tools write confident SQL against the wrong tables, and nobody can tell.
The hard part isn't writing SQL. It's knowing your data.
A language model can write SQL. What it can't do on its own is know which of your 400 tables holds “active customers,” how your teams define revenue, or which join double-counts.
Map your data
We document your schema and a business glossary, so “active customer” and “net revenue” mean what your teams mean.
Retrieve the right schema
Only the relevant tables, columns and relationships reach the model, which improves accuracy and keeps prompts small.
Build a structured prompt
The question, the user's intent, the retrieved schema and your rules are combined for context-aware SQL.
Check the SQL before it runs
Read-only access, approved tables only, row limits and permission checks.
Answer, show and chart
A table, chart or KPI tile, with the SQL visible. Ambiguous questions get a clarifying question instead of a guess.
Test and monitor
Accuracy measured on your real questions before launch, then tracked with response time and cost per question.
- Question
“How many claims took more than 5 days to allocate this month, by payer?”
- Retrieved tables
- claims.allocations
- claims.claims
- dim.payer
- Business rule applied
“Allocation time” means received date to allocation date, in business days.
- SQL, shown to the user
SELECT p.payer_name, COUNT(*) AS slow_claims FROM claims.allocations a JOIN claims.claims c ON c.id = a.claim_id JOIN dim.payer p ON p.id = c.payer_id WHERE a.business_days > 5 AND a.allocated_on >= DATE_TRUNC('month', CURRENT_DATE) GROUP BY p.payer_name ORDER BY slow_claims DESC;
Illustration. Read-only, approved tables only, row limits applied.
Questions it answers the same day they come up
Finance “What was gross margin by region last quarter, compared with the same quarter last year?”
Claims operations “How many claims took more than 5 days to allocate this month, by payer?”
HR and payroll “How did overtime hours change across sites since the new schedule started?”
Executives “Which five customers grew fastest this year?”
Built by engineers who've done it at enterprise scale
- Team experience
Our engineers have built text-to-SQL for a large US enterprise's analytics platform, including the schema retrieval that makes answers accurate.
- Integriti result
A finance data platform on Azure and Power BI for a Canadian investment fund, with a 25% gain in operational efficiency.
Your data never leaves your control
- Read-only connections, limited to approved tables and views
- Your row-level and column-level permissions applied to every query
- Runs in your cloud account, on AWS, Azure or Google Cloud
- A full log of every question, query and result
- Personal data masked where needed
Bring 20 real questions
A 2 to 3 week pilot on a copy of your data: we connect to a sample of your warehouse, answer 20 questions your team really asks, and show you exactly how many it got right. Fixed scope and fixed fee, agreed before we start and credited toward the full build.
Conversational analytics FAQ
What is text-to-SQL?
AI that turns a question in plain English into a database query, runs it, and returns the answer. Good systems also show the query so people can check it.
Can it handle our messy schema?
Yes, if we map it first. A documented schema and business glossary make the difference between a demo and a tool people trust.
Which databases does it work with?
SQL Server, PostgreSQL and Azure Synapse, among others. We confirm yours during the pilot.
Does it replace our BI tools?
No. It answers the questions dashboards don't, and can feed results back into the tools you already use.
How accurate is it?
We measure it on your own questions before launch, so you know the accuracy before your team relies on it.
Ask it the question your dashboards can't answer
In a 30-minute call with our Head of AI and our CEO or CTO, we'll look at your data sources and the questions your leaders keep asking, and show you what a pilot would answer.
- Questions answered live on a sample schema, with the SQL shown
- How your access rules would be enforced
- What a 20-question pilot would measure