Skip to content

Pricing

Three ways to start.

Try it on synthetic data, run it yourself in your own Azure, or shape an Enterprise rollout around your estate. Validation always runs inside your tenant — we keep the metadata, never your rows.

We're in private beta. Every plan starts with a conversation — tell us about your pipelines and we'll find the right fit.

Demo

See it on synthetic data.

Watch a full validation run end-to-end on a synthetic Azure Data Factory dataset — discover, define, validate, and drill into a caught failure. No setup, nothing connected to your data.

  • A synthetic ADF dataset, preloaded
  • The full discover → define → validate flow
  • A bad-record evidence walkthrough
  • No Azure connection required

Self-Serve

Most popular

Run it in your own Azure.

Deploy General Validation into your tenant and validate your own pipelines. Pair source to target, attach value and outer-value checks, and get results, reporting, and bad-record evidence — your data never leaves your cloud.

  • Runs entirely in your Azure tenant
  • Validate Parquet, CSV, Delta Lake, and Azure SQL
  • All twelve checks, incl. value & outer-value reconciliation
  • Reporting dashboard, run history, CSV export, bad-record drill-through

Enterprise

For regulated estates and scale.

Everything in Self-Serve, plus the access controls, tenant isolation, audit evidence, and hands-on rollout a regulated data org expects — shaped around your environment.

  • Role-based access (reader / contributor / owner) + tenant isolation
  • OIDC / SSO sign-in, CSRF protection, audit logging
  • Hands-on onboarding against your real pipelines
  • Hash-sealed evidence packs and SLAs shaped with you

On every plan

The same metadata-first contract, regardless of plan.

The boundaries don't change with the tier. Your data stays in your Azure; we keep the results and diagnostics, never the rows.

  • Runs inside your own Azure — we orchestrate, your environment reads and writes
  • Stores only validation metadata and results — schemas, metrics, status, diagnostics — never your rows
  • One reusable ADF Mapping Data Flow; new tests don’t spawn new pipelines
  • A four-stage run lifecycle that tells a broken pipeline apart from failed data

Security features are supported and tested — they are not a compliance certification.

Get started

Bring a pipeline. We'll find the right fit.

Book a call and we'll walk your Azure Data Factory workload together — what to validate first, which plan fits, and how it runs in your environment.

Private beta · metadata only · runs in your Azure.