Use Case
Data operations that run without you
Schedules as code, CI on every pull request, deploy on merge, and alerts in Slack, Teams, PagerDuty, or Datadog. Run the platform on Bolt. DinoAI agents handle the requests and the failures.
Products
Schedule, test, and alert
The three pieces of a production data platform, in one product.
Bolt schedules
Production runs, defined in YAML.
- Cron, on-completion, on-merge, TurboCI, and API triggers.
- Add a Run Paradime DinoAI Agent step to any schedule, so agents run on the same cron as the models.
- Retry from the point of failure, or let self-healing open the fix.
CI/CD
Test every PR, deploy every merge.
- Build changed models in a temporary schema with TurboCI and get the report on the pull request.
- Pre-commit hooks for SQLFluff, Prettier, and dbt-checkpoint.
- Continuous deployment from the default branch.
Alerts and incidents
The right people, with context.
- Slack, Teams, and email on success, failure, or SLA breach, with custom templates.
- Incidents in PagerDuty, Datadog, incident.io, New Relic, or Rootly.
- Tickets in Jira, Linear, or Azure DevOps.
Workflows
From repo to running platform
How teams run the whole operation without manual steps.
Schedules as code
Define every Bolt schedule as YAML in your repo. Deploy from the UI or on merge.
Chain the whole stack
Ingestion syncs, Python scripts, dbt™ commands, dashboard refreshes, and reverse ETL syncs run in order in one schedule.
Test every change
Run TurboCI and pre-commit hooks on each pull request. A merge to main deploys to production.
Take requests in Slack
A DinoAI agent interviews requesters in plain language and files a Jira or Linear ticket. Ask another agent to pick up the tickets and open the pull requests.
Watch it from Slack
You get run status, alerts, and self-healing fixes in the channel. Mention the DinoAI Slack Agent to trigger a run or ask about one.
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 production on Paradime
Reliability and efficiency measured on real schedules.
How to successfully run 400 models every hour with a 100% uptime
With less context-switching, the Tide team boosted their productivity
How MyTutor’s Analytics Engineers saw a 50% jump in efficiency
Resources
Go deeper
Define Bolt schedules as YAML in your dbt™ repository and deploy them straight from the UI.
Deploy dbt™ changes to production when a pull request merges.
Add a Run Paradime DinoAI Agent command to a schedule. The agent then runs on a cron, after another schedule, on merge, or in TurboCI.
A Slack bot that interviews data requesters and files well-formed tickets with priority, labels, and acceptance criteria.
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.