Use Case
Transform data with dbt™, faster
Build in a browser IDE made for dbt™. DinoAI writes models, tests, and docs as per your organization's rules. Test every pull request with TurboCI. DinoAI agents create ready-to-review PRs.
Products
Three products, one workflow
Develop, generate, and ship dbt™ models in the browser.
Code IDE
Your dbt™ workspace in the browser.
- Warehouse-aware autocomplete for ref(), source(), and YAML keys.
- Live lineage, data explorer, scratchpad, and one-click lint.
- Git Lite or Git Advanced, with GitLens built in.
DinoAI
Models, tests, and docs written to your standards.
- DinoAI reads your warehouse schema, .dinorules, Skills, and existing models before it writes a line.
- Use Ask mode for questions. Use Agent mode to edit files, run dbt™ commands, and review every change before you accept it.
- Pick the model per session from six providers.
Bolt
Test on every PR, deploy on merge.
- Build only changed models in a temporary schema with TurboCI.
- Get a column-level lineage diff on every pull request.
- A merge to main deploys to production.
Workflows
From request to reviewed model
How analytics engineers and their agents ship a change.
Start from a request
Describe the model in Agent mode, or ask the agent to pick up a Linear, Jira, or GitHub issue. DinoAI inspects the source tables, writes the SQL as per your organization's rules, and adds tests from real data.
Preview and refine
Run the model against production state with defer. Preview results in the data explorer and lint before you commit. Send a failed command's output to DinoAI for the fix.
DinoAI agents complete the PR
On every pull request, DinoAI agents write the missing descriptions, add and validate tests, and report what breaks downstream.
Review and ship
A DinoAI agent posts one review summary that covers scope, code, tests, docs, and downstream impact. A person approves. Merge to deploy, and the docs sync to the catalog.
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 ship dbt™ faster on Paradime
Development time measured before and after the move.
How Zeelo Cut Development Time from 4 Hours to 5 Minutes
Motive accelerates analytics engineering by 10x with Paradime
Customer.io boosts dev speed 25%+ and cuts costs 20%+ with Paradime
Resources
Go deeper
Turn raw source tables into readable SQL with proper joins, CTEs, and transformations that follow team standards.
An agent that drafts missing model and column descriptions from the SQL on every pull request.
An agent that checks scope, code, tests, docs, and downstream impact, and posts a review summary that can block the merge.
Repo-tracked files that steer every DinoAI session: your conventions, reusable capability packages, and shared prompts.
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.