01
Ingest
Pick up live queries via webhooks from your engines or via lightweight pollers that read query statistics directly. Nothing sits in your traffic path.
How it works
Quietly observe. Confidently advise.
QueryInsights sits beside your databases, learns from what actually runs, and turns that into specific, ready-to-ship recommendations.
How it works
Four quiet steps. Loud results.
QueryInsights sits beside your PostgreSQL, MySQL, or Trino database, learns from the queries that actually run, and turns that into specific query-optimization advice — so you stop guessing where to look.
02
Normalize
Strip out the literals so a thousand variants of the same query collapse into a single pattern. You see real workload shape, not noisy duplicates.
03
Understand
Each pattern is paired with the real table definitions it touches, so the AI has the context it needs to reason about your database, not a generic one.
04
Recommend
Get specific, ready-to-ship rewrites for individual queries — and broader schema and index advice for the whole workload, updated as it evolves.
The flow
Sits beside your stack. Stays out of the way.
QueryInsights is a side-car for your databases — it observes, learns, and serves up advice. Nothing in the request path. Nothing for your application to integrate.
Design principles
Built to stay out of the way.
Out of the request path
QueryInsights observes from the side. It never proxies your application traffic, so there's no risk to latency or availability.
Grounded in your real schema
Every recommendation is generated against the actual definitions of the tables a query touches, not a generic textbook example.
Patterns, not symptoms
By normalizing queries to their pattern shape, the same fix solves a thousand variants — and you stop chasing duplicate noise.
Early access
Want to see what's slowing your database?
QueryInsights is in early access. Tell us a little about your workload and we'll be in touch.
Or email us at hello@queryinsights.dev