Use Case
Land data from every source
Schedule Fivetran, Airbyte, and dlt loads from the same place you run dbt™. Ingestion and transformation run in order, on one schedule, with one set of alerts. DinoAI writes the sources and staging models from the landed schema.
Products
Pick the way you ingest
Managed connectors, Python pipelines, or your own cloud jobs, all on a Bolt schedule.
Managed connectors
Run Fivetran and Airbyte syncs from Bolt.
- Trigger connector syncs from a Bolt schedule and run dbt™ when they finish.
- See connectors in the catalog with lineage through to the models built on them.
- Read sync status and failures in the same run logs as your dbt™ commands.
dlt pipelines
Python ingestion in the same repo as your models.
- Write dlt pipelines in the Code IDE with shared warehouse credentials.
- Run them on a Bolt schedule ahead of the dbt™ commands.
- Load Google Sheets, APIs, and databases without a per-connector fee.
Cloud jobs
Your own ingestion, triggered in order.
- Run AWS Glue, Lambda, Step Functions, Dataflow, Cloud Run, Azure Data Factory, and Matillion from a Bolt step.
- Chain them ahead of dbt™ so models never run on stale data.
Workflows
From source to staging model
How teams land data and make it usable.
Schedule the load
Add a Fivetran, Airbyte, or dlt step to a Bolt schedule. Run it on a cron, after another schedule, or on demand from the API.
Generate the sources and staging models
DinoAI reads the warehouse metadata and writes sources.yml. It then writes staging models that follow your .dinorules, with tests and docs.
Check freshness before models run
Check source freshness before the dbt™ build. If a load is late, the run stops and you get an alert in Slack, Teams, or email.
Heal schema drift
When a source renames a field or nests a value, a DinoAI agent inspects the raw data. It patches the staging model and opens a pull request with a drift report.
Platform
Fits your stack
Connect your warehouse, git provider, and the tools around them. Keep data inside your own perimeter.
Built to fit your tools and teams
Snowflake, BigQuery, Redshift, Databricks, and a dozen more warehouses. Fivetran, Airbyte, and dlt for loading. Looker, Tableau, Power BI, and Sigma for BI. Slack, Teams, PagerDuty, and Datadog for alerts. Anything else through the API, CLI, or Python SDK.
Enterprise-grade security
SOC 2 Type II, single sign-on, custom roles, audit logs, and the option to deploy the data plane inside your own AWS, GCP, or Azure account.
Customers
Teams that run the whole pipeline on Paradime
Ingestion, transformation, and delivery on one schedule.
PushPress builds AI-powered data platform with 3x efficiency with Paradime
How to successfully run 400 models every hour with a 100% uptime
Customer.io boosts dev speed 25%+ and cuts costs 20%+ with Paradime
Resources
Go deeper
Run ingestion syncs, Python scripts, and dbt™ commands from a single Bolt schedule.
Build and run dlt ingestion pipelines alongside your dbt™ project with shared credentials.
Generate complete, accurate sources.yml files directly from your warehouse metadata.
An agent that heals dbt™ failures from schema drift. It inspects the raw data and patches the staging model.
Join industry leaders winning with DinoAI agents
Data engineers and analysts at the most AI-native startups and enterprises use Paradime's DinoAI agents everyday to become market leaders.