Most lineage tools start at the warehouse. Foundational analyzes the Java, Python, and C# application code and operational databases where your data actually originates, automatically mapping complete flow from source to BI before a single query is ever logged.
Traditional data catalogs only see what is already landed in Snowflake or BigQuery. But the real context, the logic that defines a website entity, calculates attribution, or marks a user as "PII," exists in your application code. Foundational bridges the gap by parsing the engineering side of your data stack, ensuring that downstream visibility includes upstream intent.
We parse application code across Java, Python, Scala, and C# to extract lineage at the source, before data moves anywhere. No query logs. No manual mapping. No blind spots from unexecuted code paths.
Your product databases contain logic your catalog has never seen. Foundational maps lineage through Oracle, SQL Server, Postgres, and MySQL alongside your warehouse, so you understand how application behavior shapes every downstream metric.
Spark jobs, Airflow DAGs, Python pipelines, and ORM-driven writes all contribute to your data. We parse each one and stitch them into a single unified lineage graph alongside your SQL transformations, with no gaps between systems.
Identify sensitive fields as they flow through application code, pipelines, and BI before a breach or audit forces the question. Foundational surfaces PII and PHI at the column level across every system it covers, including the application layer sources catalogs never reach.
Trace every column from its origin in Java, Python, or C# application code through operational databases, transformation pipelines, and into your BI layer. Understand exactly how fields are created, joined, filtered, and transformed at every step, including the steps that happen before the warehouse ever sees the data.
We connect lineage across your application layer and operational databases, including Oracle, SQL Server, Postgres, and MySQL, mapping how product logic written in Java, Python, and C# flows into the metrics your business depends on. No other lineage tool covers this layer. Traditional catalogs rely on query logs, which means any data created through an ORM, a background job, or an unexecuted code path is invisible. Foundational reads the source code directly, so nothing is hidden.
Because Foundational reads your application code, it knows exactly what will break when you change it. Every pull request is analyzed automatically across Java, Python, SQL, and Spark. Before a single line merges, your team sees which downstream models, dashboards, and pipelines are affected, with severity scoring and owner notifications built in. Application layer visibility is what makes this possible. Query log tools cannot tell you what an unmerged change will do because they have never seen the code that creates the data.
Traditional catalogs and observability tools are built around what they can see after data arrives. Query logs, warehouse metadata, and runtime monitoring all share the same blind spot: they have no visibility into the application code, ORM writes, and operational database logic that created the data in the first place. Foundational analyzes the source code itself, giving your team complete lineage coverage from the first line of application logic to the final number in your executive dashboard. Teams using Foundational prevent 50 to 80 percent of production incidents and complete root cause analysis in minutes rather than hours.
Stack coverage from app layer to BI.
Reduction in data incidents.
Manual mapping required.
Request a demo and we will show you exactly what Foundational surfaces across your Java, Python, and C# application code, operational databases, and downstream BI in a live walkthrough of your stack.
