Auditors ask where data goes — static analysis answers in minutes. See how

Auditors ask where data goes — static analysis answers in minutes. See how

Know Exactly Where Sensitive Data Flows Before Auditors Ask

Compliance, privacy, and model risk reviews all ask the same question: where did this data come from and where does it go?

Gable uses static analysis of your source code to trace data flows from consumer apps through backend systems — no runtime agents, no sampling, no production overhead.
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Gable Traces
Data from Source to Destination

II
// ===== UserProfileService.java =====
package demo;
public class UserProfileService {
  public User getUserProfile(String id) {
    User u = repository.findById(id);
    if (u == null) throw new NotFound("user");
    cacheInRedis(u);
    return u;
  }
  public void updateUserProfile(User u){
    repository.save(u);
    archiveToS3(u);
    indexInElasticsearch(u);
  }
  private void archiveToS3(User u){ /* s3://profiles/{id}.json */ }
  private void cacheInRedis(User u){ /* redis.set("user:"+u.id, json(u)) */ }
  private void indexInElasticsearch(User u){ /* es.index("users", u.id, u) */ }
}

// ===== EventProcessorService.java =====
package demo;
public class EventProcessorService {
  public void processUserEvent(Event e){
    insertUserEventToDb(e);
    archiveEventToS3(e);
  }
  private void insertUserEventToDb(Event e){ /* INSERT INTO user_events ... */ }
  private void archiveEventToS3(Event e){ /* s3://events/{id}.json */ }
}

// ===== FileImportService.java =====
package demo;
public class FileImportService {
  public void processBulkImport(File f){
    List rows = parse(f);
    insertImportRecordsToDb(rows);
    indexImportForSearch(rows);
  }
  public void processDataImportFromUrl(String url){ /* fetch+parse */ }
  private void insertImportRecordsToDb(List rows){ /* batch insert */ }
  private void indexImportForSearch(List rows){ /* es.bulk */ }
}
// ===== UserProfileService.java =====
package demo;
public class UserProfileService {
  public User getUserProfile(String id) { /* ... */ }
  public void updateUserProfile(User u){ /* ... */ }
  private void archiveToS3(User u){ /* ... */ }
  private void cacheInRedis(User u){ /* ... */ }
  private void indexInElasticsearch(User u){ /* ... */ }
}

// ===== EventProcessorService.java =====
package demo;
public class EventProcessorService { /* ... */ }

// ===== FileImportService.java =====
package demo;
public class FileImportService { /* ... */ }

Field-level Lineage for Regulated Enterprises

Trace sensitive data flows, satisfy auditors, ship faster

When Sensitive Data Leaves Your Apps, Visibility Gets Murky

Auditors ask how data flows from consumer-facing apps through backend systems. You spend weeks manually reconstructing flows across hundreds of services.

When AI Systems Touch Sensitive Data, Auditability Breaks Down

ML models and chatbots access customer information. Without field-level lineage, you can't prove what data reaches the model or where it's stored.

When You’re Assembling Compliance Evidence by Hand, Releases Stall

Privacy reviews, model risk, and procurement ask for input lists and lineage. This is when you scramble to answer and releases slip.

How Gable Delivers Data
Lineage at Enterprise Scale

Trace Data from Apps to Storage

Field-level lineage from code

Static analysis traces every data element from consumer apps through backend transformations.

No runtime agents required

Works in CI/CD — no production overhead, no sampling, no data exposure risk.

Audit AI and ML Data Flows

Model input lineage

Document exactly which data reaches ML systems and chatbots — and where it came from.

Transformation audit trail

Show compliance which fields were masked, filtered, or transformed before AI consumption.

Ship safely with clear guidance

Audit-ready exports

One-click lineage reports for compliance audits, privacy reviews, and procurement requests.

Release lineage snapshots

Tie each release to its input list and transformation history — evidence ships with the code.

“I believe that Gable is the first next generation data management platform built for the AI era. It’s game changing for any company that truly values data and in this punch card generation of AI, I believe this is foundational.”

Kelvin Lim

Chief Technology Officer at x15ventures

“After putting Gable in production, we've had 0 data-related incidents.”

Zakariah Siyaji

Engineering Manager, Data Platform

Features for Regulated Enterprise Teams

Field-level data lineage

Trace every data element from consumer apps through backend systems to storage.

AI/ML data documentation

Auto-generate lineage reports showing what data reaches models and chatbots.

CI/CD-integrated analysis

Static analysis captures data flows at build time and ties them to releases.

Audit response kits

Export lineage and control evidence for privacy, model risk, and regulator requests.

Guides for Platform Engineering and Compliance