The challenge

The 2AM wake-up call that shouldn't happen

Data teams move fast, but change without context creates real downstream risk.

Unclear downstream impact

Code changes ripple through models, pipelines, and dashboards. Most teams cannot see what each pull request will affect until it breaks something important.

Slow manual review cycles

Engineers trace lineage by hand just to understand whether a schema change is safe. Reviews stall, incidents slip through, and delivery slows.

Stakeholder confidence drops

Executives lose trust when dashboards conflict or fail. Every broken metric creates churn for analysts and decision makers.

Current tools start too late

Catalogs and observability tools react after problems appear. Teams need validation at the point of change, not after damage is visible.

Column level precision across SQL, dbt, Python, and BI

See how owner notifications and optional CI/CD blocks keep teams aligned and issues contained.

Request Demo

Effective prevention starts with clear visibility

Early clarity lets teams resolve risks fast, reduce incidents, and keep delivery moving.

Instant impact reports

Every pull request that touches data is scanned within seconds. Reviewers see a clear summary of affected assets, owners, and risks so they can move faster with full context.

Column level lineage

Deep lineage connects code to downstream models and dashboards. Teams understand exactly which metrics and reports depend on every column, transformation, and table.

Integrated review workflow

Impact results appear directly in the tools teams already use. No switching contexts and no scattered conversations. Engineers collaborate around one shared understanding of risk.

What teams achieve

Higher engineering throughput

Manual tracing disappears. Reviews accelerate. Engineers spend their time shipping improvements instead of chasing breaking changes.

Reliable executive dashboards

Stakeholders trust the numbers. With early validation, dashboards stay accurate and decisions stay aligned.

Better cross-team collaboration

Owners see how their work intersects. Data engineers, analytics engineers, and analysts share a unified view of lineage and impact.

Safer high speed development

Teams keep delivery velocity high without risking data quality. Pre-merge validation enables modern development practices with fewer incidents.

“Foundational gave us instant clarity on our data. With column-level lineage, we stopped wasting hours chasing data lineage and started fixing issues before they became problems.”

Eyal El-Bahar, VP of BI and Analytics

"A data change can impact things your team may be unaware of, leading folks to draw potentially flawed conclusions about growth initiatives. We needed a tool to give us end-to-end visibility into every modification.”

Iñigo Hernandez, Engineering Manager

“With Foundational, our team has a secure automated code review and validation process that assures data quality. That’s priceless.”

Omer Biber, Head of Business Intelligence

“Foundational has been instrumental in helping us minimize redundancy and improve data visibility, enabling faster migrations and smoother collaboration across teams.”

Qun Wei, VP Data Analytics

“Foundational helps our teams release faster and with confidence. We see issues before they happen.”

Analytics Engineering Lead

See every dependency and risk before code hits production

The challenge

The 2AM wake-up call that shouldn't happen

The solution

A better way to validate every pull request

PR is opened and Foundational analyzes instantly

See what will break via impact report in PR

Fix issues before merge and production stays stable