Transformation without the headaches
You connect the sources. We deduplicate, model, and load incrementally. The transformation engine ships the consulting-grade defaults our founders spent a decade building.
Raw tables
Clean tables
Your data lake, included.
Every workspace ships with a SQL data lake. Encrypted, isolated, included. Outgrow it? Point Pillar at your Snowflake, Databricks, BigQuery, or Fabric.
- Auto-provisioned
- Zero config
- Encrypted at rest
- Isolated per tenant
- One invoice
Integrated SQL Data Lake Runs on the engines you trust.
Write once. Runs on every supported warehouse.
Total Transparency & Control
Inspect every pipeline. Override anything you need to.
Data Coverage
See which standard models your sources cover, and which still need a connection.
Automated Quality
Every column scored on five dimensions. Tests are generated, not hand-written.
Interactive Lineage
Trace any column back to the source row.
Manual Import
Upload budgets, targets, or historical CSVs straight into the pipeline.
Field Overrides
Override any field mapping when sources disagree.
Already run dbt? Point us at your repo.
The transformation engine isn't a black box. If your team already has a dbt project, connect your Git repository and Pillar clones it, runs your models on your warehouse on the schedule you set, then layers automated quality scoring, lineage, and Ask Your Data on top — no runners to host, no orchestration to babysit.
- 1 Connect your repo
Add your Git URL and branch with a read-only deploy key. Public or private.
- 2 We clone & build
Pillar clones it and runs
dbt buildon your warehouse, every sync. Your code, our managed runtime. - 3 Governed on top
Quality scores, lineage, and Ask Your Data wrap your existing models automatically.
dbt build