SynthGuard runs real-time automated validation on synthetic data — catching hallucinations, anomalies, and hidden bias before they degrade your model during fine-tuning.
You're using synthetic data to speed up R&D and bridge gaps in real-world data availability. Without validation, every batch you train on is a bet you can't see the odds on.
Your model develops systematic errors on real-world data that never showed up in testing — until production.
Generation errors compound through training and get reinforced and magnified in the final model.
Metric degradation forces rollbacks and re-runs of entire pipelines — discovered weeks too late.
of synthetic data in pilot projects contains critical anomalies invisible to manual review.
Integrate in 10 minutes. Supports JSON, Parquet, PNG/JPG, and WAV, with stream processing for large datasets.
An ensemble of 3–5 specialized models — anomaly detectors, hallucination classifiers, distribution analyzers — processes data in parallel on GPUs.
Receive a JSON report with quality metrics, a list of problematic records, and clear recommendations: use, refine, or discard.
Our pipeline is engineered for maximum GPU utilization and minimal latency.
Run multiple validator models simultaneously to accelerate data checks.
Dynamically allocate resources based on incoming data volume.
Guaranteed API availability for your CI/CD workflows.
This architecture enables terabyte-scale data processing with predictable cost and response times — critical for production-grade systems.
Eliminate manual validation effort and ensure dataset quality before training starts.
Iterate faster in R&D without risking metric degradation down the line.
Guarantee model stability and meet data quality compliance standards.
Automated validation replaces weeks of manual review.
Reduce the risk of metric degradation when fine-tuning on synthetic data.
Detailed reports and metrics for auditability and compliance.
Process terabytes of data without changing a line of code.
Ideal for MVPs and experiments.
For active ML teams.
For large organizations.
SynthGuard reduced our synthetic data validation time from 3 days to 3 hours and prevented degradation of our core model.
Fintech partner
Pilot program, fraud detection team
In pilot projects with top fintech companies.
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