A Closer Look at The Lifter Across Systems

Data Lifter

Is your schema migration still a success if downstream systems misinterpret the data? Relying on schema-only mapping often creates a "semantic gap" where the data arrives intact, but the governing business context is stripped away. This mismatch results in months of manual fixes for broken reports and skewed post-migration analytics.

Data Lifter closes this gap by parsing legacy ETL packages and stored procedures to map lineage and extract hidden transformation logic, providing the automated profiling needed to ensure the new stack delivers the exact same business outcomes as the old one.

Legacy Lifter

Modernization projects often evolve into expensive forensic archaeology when the original intent of the system is buried under decades of undocumented code. Teams end up revisiting the same codebase repeatedly, trying to piece together dependencies, undocumented logic, and integration points that no one fully owns anymore.

The real delay comes from reconstructing this understanding before any change can happen. The Legacy Lifter demo walks through how it surfaces these relationships and impact areas upfront, so the initial discovery phase becomes far more structured.

Test Lifter

Maximizing code coverage percentages often results in coverage theatre, a scenario where green dashboards create a false sense of security while leaving the system's true logic untested. This gap between metrics and reality is why critical issues slip into production despite perfect QA reports. It slows down releases and makes every deployment harder to trust.

The demo gives a clear view into how Test Lifter replaces that false confidence with validation tied to real system behavior, generating and adapting tests based on how the system runs rather than what’s assumed.