Train Intelligent
AI Models
Synthesize quality training data for your next fair, private, and robust model, using state-of-the-art generative artificial intelligence
Create quality training data with state-of-the-art technology
Syntheta [θ]
Generate realistic data using our engine
# python
requests.post("api.syntheta.org/synthesize", data=df)(Assuming `df` is an instance of the pandas DataFrame class)
Use Syntheta's engine through our API
Our generative models will then train, synthesize and return new, high-quality tabular data that mirrors the statistical properties of your input.
or
# bash
docker run -p 8080:8080 -v ./data:/data syntheta/engineMount your dataset and access the API at localhost:8080
Made by developers, for developers.
Use Cases
External Data Sharing
Share insights, not identities
Zero Data Egress
Synthetic replicas allow you to share data externally without any real records ever leaving your infrastructure.
European Sovereignty
Meet EU data residency and GDPR requirements by generating compliant synthetic datasets that stay within jurisdictional boundaries as privacy compliance is built-in.
A New Standard of Data Exchange
Internally, this new paradigm allows data science tooling to evolve around synthetic-first workflows, enabling teams share insights freely across departments, and build pipelines without waiting on data access approvals.
Speed in Client Acquisition
Shorten NDA timelines and due diligence cycles by sharing synthetic samples early, accelerating trust-building with new clients.
Un-biasing Networks
Fairer data, fairer models
Sampling Outliers
Generate synthetic examples of rare events and edge cases so your model learns from the full distribution, not just the centre.
Filling in Gaps
Augment sparse regions of your dataset where real-world collection is impractical, expensive, or ethically constrained.
Appropriate Representation of Minority Classes
Rebalance training data to ensure underrepresented groups receive proportional coverage, reducing systematic bias in downstream predictions.
Ethical Real-world Decisions
Biased training data leads to biased automated decisions with real consequences for real people. The Rotterdam welfare fraud detection scandal showed how algorithmic systems can disproportionately target vulnerable communities when trained on skewed data. Read more.
Best-in-class Regressor & Classifier
One model to generate and predict
Generative Models for Predictive Tasks
The same generative architecture that synthesizes realistic tabular data also achieves state-of-the-art performance on regression and classification benchmarks.
100% Downstream Performance Parity
Models trained entirely on Syntheta's synthetic data achieve equivalent performance to those trained on real data, meaning you can replace sensitive datasets without sacrificing accuracy.
Unified Training Pipeline
Train a single model that can both augment your data and serve predictions, reducing infrastructure complexity and maintenance overhead.
Autonomous & Adaptive
Syntheta's models automatically tune themselves to your data schema, delivering best-in-class accuracy with minimal configuration.
Swipe to browse use cases
Syntheta's Values
Equality
Synthetic data can be used to give models a better understanding of commonly under-represented groups or minorities which allows both critical and safety-critical systems using machine or deep learning to exhibit minimal bias.
Privacy
Synthetic data guarantees privacy by alleviating the issue of training models on Personally Identifiable Information (PII); which puts client data at risk as it can be used to identify an individual, either directly or indirectly.
Intelligence
The machine learning models of tomorrow should be robust and explainable with reasoning being a key for their decision making, with the use of synthetic data, humans can augment datasets and better train and test models' intelligence.
Work in Progress
Syntheta's API is currently under active development. Most features are unavailable at this time unless accessed through a guided demo.
If you have any queries or are a potential client interested in what we're building, feel free to reach out via email at alex@syntheta.org, or connect personally through alex-lalov.com, where more links are available.