BYOC, BYOI
Qwry.AI runs against your cloud and your infrastructure. Data doesn't move into a Qwry.AI-controlled environment to be processed and handed back. It stays where you put it.
Platform Data Foundation
Say yes to AI without handing over the keys
Your data stays on your infrastructure. Your roles decide what gets queried. Your reviewers sign off before an AI-generated answer reaches someone who'll act on it. Control here is architecture, not a policy document.
access matrix table-level
customers orders employee_salaries Analyst Dashboard viewer Reviewer
Overview
The instinct when a board asks "is this safe" is to reach for a framework name. That's the wrong reflex for a platform still building toward that stage, and it's also not what actually protects a business day to day. What protects a business is whether an intern's role can query the finance tables, whether the AI can quietly infer its way past a permission boundary, and whether anyone reviews an AI-generated answer before it becomes a customer-facing decision. Those are architecture questions, and they're answered below.
Tool-level access, per role
Jupyter, SQL Editor, LLM Chat, and App Builder can each be switched on or off per role. A role built for dashboard viewing never sees a notebook.
Table-level permissions
Access is enforced at the table, not the workspace. A user with access to customers
and orders cannot query employee_salaries, and the AI querying layer
inherits the same restriction, it cannot route around a permission it doesn't have.
Human-in-the-loop reviewer role
A dedicated role exists specifically to validate LLM-generated answers before they're trusted downstream, an explicit checkpoint rather than a hope that the model got it right.
These permissions aren't a separate layer bolted onto querying, they're the same access control that governs AI Querying itself: if a role can't see a table, the AI generating SQL on that role's behalf can't see it either. And because permissions are enforced at the table, not the connection, they hold even as Ingestion & ETL brings new sources into the warehouse.
Insights
Use cases & field notes from the data trenches.
Customer playbooks, technical deep-dives and field notes from deployments into messy enterprise estates.
Technical
JOIN dms_secondary ON erp.sku_code
→ 94% match · conf 0.94
→ 94% match · conf 0.94
Contextual data in personal care manufacturing & distribution: the context between systems is the missing asset.
Every personal care manufacturer generates data at every stage of its value chain, and cannot join it. How automated relationship discovery turns five to eight disconnected systems into cross-source answers in minutes, not days.
Read the white paper Use Case
ERP Secondary Sales GST
One view across distributors, billing, and compliance: how pharma distribution stops flying blind.
Secondary sales in spreadsheets. Distributor stock self-declared. Billing in the ERP. Compliance records as PDFs. How Qwry.AI connects them into one governed view, and what becomes possible when it does.
Read the use caseConnectors
Reads from the systems you already have.
Databases, warehouses, files and the apps you run: connect what you already have, don't migrate. Every source lands in one governed graph, with 200+ on the roadmap.
Don't see your connector? Tell us your stack. We'll scope it.
Reach out →