Precision Synthetic Data for Unmatched AML Standards

Achieve faster compliance, reduce risk, and enhance detection with our advanced synthetic data solution designed for rigorous financial compliance.

High-Fidelity Synthetic Data
That Looks And Behaves Like Yours

We know one-size-fits-all data doesn’t work. Our synthetic data mimics the shape, logic, and messiness of your world - safely.

How It Works

We don’t need your real data - just the structure that defines it. From there, we create high-fidelity synthetic datasets that look, feel,
and behave like your own, ready for safe testing inside your NayaOne sandbox.

1

Share your data schema

We don’t need your real data — only your table structures and key fields.

2

Define what matters

Tell us the test cases, data behaviours, and statistics you want represented.

3

We configure agent-based generators

Our agents create data row by row, following your logic.

4

Generate and validate

You receive a dataset that mirrors your world, ready to use in a secure sandbox.

Your Data Stays Yours

We never touch production data. You keep full control - we simply replicate its structure so you can run proofs safely.

1

Your Schema

Share table structures, keys, and relationships — no real data required.

2

NayaOne Generator

We configure agent-based generators that follow your logic row by row.

3

Secure Sandbox

Receive a sandbox-ready dataset that mirrors your world for safe validation.

One Platform.
Multiple Synthetic Data Use Cases.

RISK AND COMPLIANCE

Identity and Onboarding

Generate synthetic identity documents and onboarding records to safely test KYC/KYB and customer verification processes - without using real customer information.

FRAUD AND FINANCIAL CRIME

Fraud and Risk

Generate datasets that include edge cases, anomalies, and suspicious patterns so risk teams can test fraud detection models and resilience - without exposing live customer data.

RISK AND COMPLIANCE

Regulatory Compliance

Generate datasets that replicate reporting obligations and audit scenarios, helping compliance teams validate systems against regulatory standards without exposing sensitive data.

CREDIT AND LENDING

Lending and Credit

Create loan application, repayment, and credit history data that mirrors production environments, enabling fair testing of credit decisioning tools and lending platforms.

INSURANCE

Claims and Insurance

Produce synthetic claims, policy, and payout datasets so insurers can test AI, automation, and fraud detection in claims processes — all without customer exposure.

AI AND AUTOMATION

AI and Model Testing

Provide high-volume, production-like data for testing AI/ML models, ensuring governance and compliance without relying on customer datasets.

Types of Data We Generate

High-fidelity datasets that stay consistent across systems, built to replicate the complexity of your production environment.

Structured

Claims, policies, and transaction records that mirror production systems.

Semi-Structured

Create event logs, payment flows, and activity streams to test integrations and workflows.

Unstructured

Contracts and ID documents in realistic formats.

Clean and Messy

Perfect datasets or noisy ones to test resilience.

What Our Customers Say

From locked data to live evidence - in weeks, not months.

See how high-fidelity synthetic data unlocks faster proof-of-concepts and enterprise-grade validation.

FAQs

We start with your data schema, not your real data. You share the structure – tables, relationships, and field types – plus any behaviours or test cases you want represented.

From there, our agent-based generators build data row by row, mirroring the logic, complexity, and quirks of your environment.
The result: synthetic data that behaves like the real thing, without ever exposing live information. 

Yes. NayaOne supports both structured datasets (tables, transactions, logs) and unstructured data (text, documents, images). We can simulate structured relationships – like customers, accounts, and transactions – and also create realistic document data for areas such as claims, KYC, or support conversations. If your use case spans multiple data types, the generators can connect them all in one coherent dataset.

Absolutely. Every dataset maintains referential integrity, meaning linked tables and entities (like customer → account → transaction) stay consistent. This ensures synthetic data behaves the same way your systems expect it to – crucial for running accurate AI training, API validation, and integration testing.

Typically a few days to a few weeks, depending on complexity. Once we receive your schema and test requirements, we configure the generators and return a first version for review. Unlike traditional anonymisation or manual data prep, this process is fast, repeatable, and can be reused across multiple PoCs or projects.

All synthetic data stays within your secure NayaOne sandbox environment. We never move or access your production systems. The data generation, validation, and testing all happen inside isolated, governed workspaces that align with your security and compliance requirements.

Yes. Once your generators are configured, you can tweak variables (volume, frequency, specific entities, edge cases) and instantly produce new datasets. This is ideal for regression testing, new AI models, or when your schema evolves.

Generate Your First Dataset

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