GraphReplica Synthetic Data
Synthetic data your models trust
Generate fully synthetic datasets that keep the statistical shape and the relationships of the original. Train models, run analytics, and ship demos on a faithful replica. Share it safely with zero PII leakage.
See the tradeoff
Privacy goes up. Utility stays
Slide up the privacy guarantee. The synthetic replica keeps tracking the real distribution, task utility holds, and PII exposure drops to zero.
Privacy strength
Slide up the privacy guarantee. Watch the replica stay close to the real data.
Models trained on the replica stay close to real-data accuracy.
Stronger privacy widens the mix of cases for agent training and red-teaming.
Zero exposure. Provable privacy verified by a leak check.
Medium privacy. Recommended. Zero leakage with a replica that tracks ground truth closely.
Why GraphReplica
Other tools copy one table. We keep the whole picture.
A faithful replica is only useful if the pieces still fit together. GraphReplica generates across your entire dataset at once.
Relationships survive across tables
Most synthetic tools work one table at a time and break your keys. GraphReplica keeps primary keys, foreign keys, and entity links intact across the whole dataset so joins still work.
The shape of the data holds
The synthetic distribution tracks ground truth closely. Analytics, dashboards, and BI tools read the replica the way they read production.
Differentially private by default
GraphReplica generates differentially private synthetic data. The privacy guarantee is mathematically provable. Every record passes a leak check before release and stress tests show 0% PII leakage.
More privacy can mean better models
Adding privacy noise increases task diversity while model performance stays stable or improves slightly. Synthetic-trained classifiers stay close to real-data accuracy across privacy budgets. You get a stronger guarantee without paying for it in results.
Replica utility stays within about 5% of real-data performance.
PII leakage across membership inference and canary stress tests.
Bring a sample dataset. We will generate a safe replica and show you the utility.
What teams build with it
Move faster than the privacy review that used to block every project
Once your data is safe to use, every downstream team gets unblocked at the same time.
Train and evaluate AI agents
Build realistic corpora to train, evaluate, and red-team agents. Stronger privacy settings widen scenario diversity so models see more cases.
Power BI and analytics on a safe copy
Point coding agents and BI tools at a faithful replica instead of production. No privacy review queue, no exposed customers.
Stand up demos, QA, and staging
Spin up environments that look and behave like real data without ever touching a real customer record.
License and share proprietary data
Hand partners a usable dataset that carries none of the underlying PII, PHI, or IP.
Tables, documents, and messy sources
Generate from CSV, JSON, Parquet, XLSX, SQLite, and more. Tables keep row counts and types. Documents keep their structure. The replica looks like the real thing.
Runs inside your environment
A container runs in your cloud, data center, or Databricks. Your data never leaves and never reaches Secludy. Every run produces audit-ready reports built to meet GDPR, CCPA, and HIPAA requirements.
Generate a safe dataset this week
Book a demo and we will generate a safe synthetic replica on a sample of yours. First safe dataset in under a week.