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EXAMPLE QUESTIONS
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175 Blueprints
Turn any PDF, web page, or text document into structured JSON with OpenAI GPT-4o, then store the results in PostgreSQL and Slack.
Forecast 7-day demand with OpenAI GPT-4o, auto-generate purchase orders for stockout-risk SKUs, and log them to PostgreSQL every 6 hours.
Submit a Python Apache Beam pipeline to a distributed Flink portable runner via a JobServer, triggered after upstream ingestion succeeds.
Use the Beam YAML framework with the Python SDK to read, filter, and rewrite a daily orders CSV, backfill-safe and with a non-injectable threshold.
Run the canonical Apache Beam word-count pipeline locally with the DIRECT runner over a real ingested text file.
Event-driven cross-cloud ETL that loads new Azure Blob CSV files into BigQuery and triggers a dbt Cloud transformation job.
Watch a CloudWatch backlog metric and fire an EMR Serverless Spark job only when work is pending.
Refresh only the BigQuery partitions that changed by loading each day's GCS files into its matching partition with WRITE_TRUNCATE.
Extract data from a REST API, reshape it with Python and Polars, then run analytical SQL on it with DuckDB, all in one Kestra flow.
Run Airbyte Cloud syncs in parallel, then trigger a dbt Cloud transformation job once the data lands.
Ingest Salesforce, Google Analytics, and Facebook Ads in parallel with Airbyte Cloud, then transform with dbt in one orchestrated ELT pipeline.
Run parallel Airbyte syncs, then transform raw data with dbt Core, all in one orchestrated ELT pipeline.
Stream RabbitMQ order messages into real-time executions, validate and forward them to an API, and route failures to a self-provisioned dead letter exchange.
Extract JSON from a REST API, enrich it, and load it in parallel to Postgres and Amazon S3.
Turn plain-English questions into PostgreSQL queries with OpenAI GPT-4o, grounded on schema only so no row data ever leaves your database.
Run a Glue ETL job, validate the output with Athena, then cache the headline KPI in DynamoDB.
Run an Apify actor under hard cost and run caps, then branch on the returned item count so a degraded scrape pages the on-call instead of silently shipping bad data.
Run an Apify actor on a schedule, fetch its dataset, reshape the records, and bulk-load them into Postgres with cost caps and Slack alerts.
Trigger an Airbyte Cloud connection sync on a recurring schedule so your data lands fresh without manual runs.
Run an Apify actor, pull its dataset, and publish the scraped results straight into a Notion page.
Trigger multiple Airbyte connection syncs in parallel from a single Kestra flow to cut total ingestion time.
A Pub/Sub trigger micro-batches streaming messages and appends them to a raw BigQuery table as newline-delimited JSON, staying under DML limits.
Incrementally push freshly updated Postgres rows into an Algolia search index every five minutes.
Trigger an Apache Airflow DAG from Kestra and wait for it to finish.