BlazeSQL is an AI data analyst that connects to your database and answers questions with SQL, charts, and dashboards.
BlazeSQL connects directly to your database and acts as a chat-based analyst. Ask questions in plain English and it writes SQL, runs it, and returns charts and tables you can pin to dashboards. It learns your schema, remembers context from earlier questions, and can build multi-chart dashboards from a single request. For teams that lack a dedicated analyst, it turns database questions into self-serve answers.
Because BlazeSQL executes queries rather than only writing them, it can iterate: ask a follow-up question and it refines the previous query, drills into segments, or re-charts the data differently. Dashboards built from these conversations become living reports refreshed against the live database.
The chat workflow suits exploratory analysis: start with a broad question, refine with follow-ups, and pin the useful charts to a dashboard. Because each answer shows its SQL, technical teammates can audit what the AI actually ran.
BlazeSQL offers a free trial. Paid plans are per-user subscriptions with tiered query limits and team collaboration features.
Product managers, founders, and operations teams who need live database answers without writing SQL or building BI models.
A free trial is available; continued use requires a subscription.
Integrations and embed options are offered for teams; details are provided during onboarding.
Query generators stop at SQL text; BlazeSQL executes the query and produces dashboards, covering the full answer loop.
Connections are encrypted and query execution follows read-only best practices; enterprise plans add stricter controls.
BlazeSQL supports popular SQL databases and warehouses; connection specifics are covered during setup.
BlazeSQL states customer data is not used to train public models.
Yes, saved dashboards can refresh against the live database on a schedule.
Yes, saved dashboards can be shared with colleagues for collaborative review.
Yes, it is designed for real production databases, generating efficient queries and visualizations against live data at scale.