Redbird AI syncs dbt models directly to PostgreSQL tables, automates transformation workflows, and keeps your production database in lockstep with your analytics layer. Stop writing custom deployment scripts and manually promoting models to production.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
When dbt model tests pass in staging, Redbird automatically materializes the model to production PostgreSQL schemas. Set schema-specific promotion rules based on test coverage, documentation requirements, or freshness checks.
When columns are added or modified in PostgreSQL source tables, Redbird updates your dbt source YAML files to reflect the new schema. Keep source definitions accurate without manual updates or documentation drift.
Redbird monitors PostgreSQL query logs and compares them against dbt model logic. When downstream applications query production tables in ways that bypass dbt transformations, your team gets notified with the specific queries and impacted models.
When new tables appear in your PostgreSQL operational database, Redbird scaffolds starter dbt models with column descriptions, data type tests, and source freshness checks. Analytics engineers review and refine instead of building from scratch.
Redbird captures full table copies to cold storage whenever dbt snapshot models identify schema changes or business rule updates in PostgreSQL source tables. Maintain historical context for audit trails and data recovery scenarios.
After each dbt model run, Redbird queries PostgreSQL for actual execution statistics, table size changes, and index usage. Analytics engineers see which models create database load and optimize accordingly.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize dbt and PostgreSQL with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird understands both dbt's YAML-based model definitions and PostgreSQL's schema catalog, automatically mapping transformation logic to database objects without configuration.
Redbird parses your dbt_project.yml, model dependencies, and compiled SQL to understand transformation intent. It queries PostgreSQL's information_schema and pg_catalog to map source tables, materialized views, and custom types. When schema drift occurs, Redbird knows which dbt models are affected and suggests specific YAML updates. The AI recognizes naming conventions like staging prefixes, mart layers, and snapshot patterns to route workflows intelligently.
faster than deploying dbt models with custom CI/CD scripts and schema validation
Redbird can pull from dbt and PostgreSQL simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either dbt or PostgreSQL.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from dbt into PostgreSQL, or from PostgreSQL back into dbt. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start automation workflows from dbt model events or PostgreSQL schema changes, and take action in either system.
Fires when any test defined in schema.yml returns failures during a dbt run.
Triggers when source freshness checks exceed warn_after thresholds in sources.
Detects when a new .sql file is added to models/ directory with valid ref() syntax.
Executes dbt run for a specific model and its upstream dependencies.
Modifies source definitions in schema.yml files with new columns or freshness rules.
Runs dbt docs generate and publishes updated catalog to documentation site.
Fires when ALTER TABLE operations add, drop, or modify columns in tracked schemas.
Detects CREATE TABLE statements in specified schemas like public or application namespaces.
Triggers when slow query log shows execution time increases above baseline thresholds.
Executes CREATE TABLE with specified columns, types, constraints, and indexes.
Performs maintenance operations on specific tables to optimize query performance.
Retrieves schema information, table statistics, or constraint definitions from pg_catalog.
Start automating the workflow between dbt transformations and PostgreSQL production tables. Redbird handles deployment, schema sync, and testing orchestration so your analytics engineers can focus on building models.