AI agents and Slack bots
Give LLMs and autonomous agents structured warehouse context via secure, cached APIs.
Read use caseTurn trusted warehouse SQL into secure, read-only APIs. Democratize data usage across apps, internal tools, and AI agents—without driving up your warehouse compute bills or exposing database credentials.
How it works
Why now
Internal tools, customer surfaces, partner workflows, scripts, and AI agents increasingly need precise slices of trusted warehouse data. Direct warehouse access is too broad, custom backend work is slow, and reverse ETL is not an API contract.
Qry creates a narrow governed boundary: the data team chooses the SQL, the allowed inputs, the freshness policy, and the consumers that can call it.
select
account_id,
account_name,
health_score,
current_mrr,
renewal_date
from marts.customer_health
where true
and account_id = {{ account_id }}
and health_score <= {{ max_score }} -- @optional
limit {{ page_size }}Use cases
Qry is not BI, reverse ETL, an app builder, or a backend-as-a-service. It is the narrow API layer around warehouse data that should be consumed programmatically.
Give LLMs and autonomous agents structured warehouse context via secure, cached APIs.
Read use caseServe refreshed billing and platform metrics directly inside your product dashboard.
Read use caseConnect warehouse data to internal ops tools and custom admin panels without slowing down your app or driving up query costs.
Read use caseCloud MVP
Qry Cloud is being built first around hosted teams, durable refresh workflows, immutable snapshots, and operational visibility for API usage.