Secludy AI — Make sensitive data safe to use for AI
Make sensitive data safe to use for AI
GraphReplica replaces the sensitive PII entities in your data with realistic synthetic data.
The same person or entity gets the same replacement across your tables, documents, and images in one pass. One replacement, matched across all data formats.
| Format | Description |
|---|---|
| Tables | Data structured in rows and columns |
| Documents | Main written content and text containers |
| Images | Visual representations or graphics |
Original
- Name: Sofia Martinez
- Email: sofia.martinez@example.edu
- Zip: 94107
- School: Bayview University
- Employer: Northstar Robotics
- Role: ML Infrastructure Intern
Replica
- Name: Elena Cruz
- Email: elena.cruz@example.edu
- Zip: 94110
- School: Pacifica University
- Employer: Orion Robotics
- Role: Data Infrastructure Intern
Zero leakage you can prove
Train a model on raw enterprise data and it memorizes what it sees. In stress tests, unprotected models leaked about 27.5% of injected sensitive values. Data built with GraphReplica leaked none. Every run ships an audit-ready report you can hand to your legal and security teams.
PII leakage stress test
| Model | Leakage |
|---|---|
| Unprotected model | 27.5% |
| GraphReplica | 0% |
Use cases
Put safe data to work
GraphReplica unblocks the work that real data used to block. One safe replica that stays realistic and usable.
Train and evaluate AI agents
Build realistic environments to train, evaluate and red-team agents on data that behaves like production.
Unblock coding agents and BI
Point coding tools and BI at a safe replica instead of waiting on privacy review.
Safe demos, QA and staging
Stand up demo, test and staging data without exposing real customers.
License and sell data
Sell or license datasets to AI labs and partners without exposing PII, PHI or IP.
Keep joins across tables
Keep foreign keys and relationships intact across many tables and files.
Resolve identity across docs
Match the same real entity across email, PDFs, spreadsheets and notes.
Test for PII and PHI leakage
Prove whether sensitive data leaked with membership inference and canary tests.
Move past privacy review
Ship AI work in days instead of waiting on long privacy reviews.
Interactive demo
Try GraphReplica
Step through a graph-preserved replica, then move the slider to see why masking breaks data and replicas keep it usable.
Input formats
| Format | Example |
|---|---|
| XLSX | Excel / CSV |
| Resume | |
| JSONL | Recruiter notes { candidate: "Sofia Martinez", zip: "94107" } |
| TXT | Interview feedback |
Privacy-aware entity graph
| Original | Replica |
|---|---|
| Sofia Martinez | pending |
| sofia.martinez@example.edu | pending |
| 94107 | pending |
| Bayview University | pending |
| Northstar Robotics | pending |
| ML Infrastructure Intern | pending |
Why teams choose GraphReplica
Same entity, same stand-in, everywhere
GraphReplica finds the sensitive entities in your data and replaces only those. The same real person, customer, employee or account gets the same stand-in across every file, table and document. This holds across millions of records and years of history. Random replacement breaks this. Masking leaves nothing usable.
Joins survive
Foreign keys and relationships stay intact across many tables and documents. Your downstream joins and queries still work.
Runs in your environment
A container that runs in your cloud, data center or Databricks. Your data never leaves. Every run is air-gapped and audit-ready.
Unstructured data
Works on free text too. Toggle between the source and the safe replica.
Compliance
Built to meet data protection requirements across the EU, US and APAC with one integration. Built to meet GDPR, CCPA and HIPAA requirements. No customer data is retained after processing.
How it works
From messy data to a safe replica
GraphReplica runs five stages and gates every release on a leak check. No release ships if an original value survives.
- Detect
Find sensitive entities across messy multi-format sources. - Resolve
Group the records that refer to the same real entity. Surface conflicts. - Replace
Swap only the sensitive entities for consistent realistic stand-ins. - Validate
Run a leak check and a consistency check on the output. - Report
Produce audit-ready detection, replacement and risk reports.
0% PII leaked in stress tests
100M+ records held consistent
0.9 F1 detection and replacement
Within 5% of real-data utility
Support
Frequently asked questions
What does GraphReplica do?
GraphReplica finds the sensitive entities in your data and replaces only those with realistic stand-ins. Everything that is not sensitive stays exactly as it was. The same real entity gets the same stand-in across every file, table and document.
How is this different from data masking?
Masking removes values and leaves your data unusable. GraphReplica swaps sensitive values for realistic stand-ins so the data still reads naturally and your downstream work still runs.
Does my data ever leave my environment?
No. GraphReplica runs as a container in your cloud, data center or Databricks. Your data never reaches Secludy. Every run is air-gapped.
Which regulations does this help with?
GraphReplica is built to meet GDPR, CCPA and HIPAA requirements. No customer data is retained after processing.