01
Ingest
Connect your warehouse and selectively discover schemas, tables, and high-value columns before they become queryable.
Product
Dataira sits between your databases and your team. It understands schema, grounds every query in verified business context, and improves continuously from real usage — corrections, patterns, and production logs alike.
Semantic layer
Schema → Interview → Certify
Learning loop
Corrections feed next answers
Optimization
Indexes · Schema · Materialization
Analytics engine
ClickHouse · Lineage · Jobs
Multi-surface
Web · MCP/IDE · Slack · Discord
Core loop
Dataira doesn't just answer questions. It observes, learns, optimizes, and progressively transforms your databases into high-performance analytics layers.
Human corrections
When users correct an output, Dataira learns the right interpretation and improves future responses for everyone.
Usage observation
Dataira analyzes queries from chat, applications, MySQL logs, and pg_stat_statements to find what matters most.
Continuous improvement
The core loop: question → SQL → correction → learning → pattern detection → optimization → better answers.
Optimization hints
Based on real usage, Dataira suggests indexes, recommends schema changes, proposes intermediate tables, and identifies expensive queries.
Automated transformations
Dataira syncs data into ClickHouse, creates bronze/silver/gold layers, and maintains them with scheduled jobs — like dbt, but automated.
Semantic layer
The platform grounds every query in reviewed business context so responses remain legible as schemas evolve.
01
Connect your warehouse and selectively discover schemas, tables, and high-value columns before they become queryable.
02
Schema owners validate column semantics, PII flags, and low-confidence fields with targeted follow-up prompts.
03
Blessed table groups form business flows. Dependency-aware activation protects trust before answers go live.
Execution surfaces
Onboarding remains web-first; asking can happen across channels without sacrificing correctness or context.
Primary ask surface with layered answers: summary, chart, data view, and optional SQL inspection.
Developer-native access to the same semantic grounding, enabling traceable requests inside tooling.
Thread-native replies with link-backs to the web app for deeper exploration and governance controls.
Security & trust
Control planes, approvals, and auditability are part of the product flow, not bolt-on afterthoughts.
Organization and project boundaries enforce strict workspace segmentation and safer growth paths.
Generated SQL is controlled, auditable, and designed to avoid destructive access patterns.
Encrypted secret handling with clear migration path toward external vault providers.
Changed structures auto-gate affected tables until semantic re-review is complete.