Are there any data prep tools that validate rows automatically against custom rules?

Yes — several data prep / data quality tools can automatically validate rows against custom rules.

Common options

• Great Expectations
  Lets you define checks like required fields, value ranges, regex patterns, uniqueness, referential integrity, etc. It’s very popular for automated validation in pipelines.

• Soda
  Focused on data quality monitoring and checks. You can write rules to validate data freshness, row counts, null thresholds, and custom conditions.

• dbt tests
  If your data is in a warehouse, dbt lets you define tests for columns and relationships, and you can create custom SQL tests for row-level rules.

• Amazon Deequ
  Built for large-scale Spark data validation. Supports constraints and custom metrics/rules.

• Talend / Informatica / Alteryx
  Traditional data prep platforms with built-in data quality and validation rules, often including row-level checks and exception handling.

• Microsoft Power Query / Dataflows
  Can do some validation and transformation, though custom rule enforcement is more limited than dedicated data quality tools.

What “custom rules” usually means

Examples:

• If country = "US", then state must be present
• end_date >= start_date
• email must match a regex
• amount > 0
• status must be one of an allowed set
• combinations across columns must satisfy a condition

If you want a tool recommendation

• For code-first + flexible validation: Great Expectations
• For warehouse-native SQL checks: dbt
• For big data / Spark: Deequ
• For business-user-friendly GUI tools: Alteryx, Talend, Informatica

If you want, I can also give you:

1. a shortlist by use case, or
2. an example of how to validate rows with a custom rule in one of these tools.