Synthesized vs Tonic.ai comparison

PRODUCTION-FAITHFUL TEST DATA FOR EVERY TEST, MIGRATION AND AGENT.

The Synthesized platform unifies test data generation and lifecycle operations across SAP and non-SAP systems. It helps teams prepare production-faithful data for continuous testing, without the burden of manual data preparation.

Synthesized is an official SAP technology partner and Synthesized platform is listed on the SAP store: sap.com/products/erp/partners/synthesized-ltd-synthesized-intelligent-tdm.html

WHAT IS SYNTHESIZED?

The Synthesized platform is an AI-native test data management platform for SAP, enterprise applications and AI-driven testing. It is the only end-to-end TDM platform that unifies SAP and non-SAP test data generation and core test data operations in one enterprise-wide solution.

Teams can mask sensitive data, create consistent subsets and generate the records production does not contain. Data stays connected across applications, supporting reliable testing of complete business processes rather than isolated tables.

The platform combines generation, copying, time slicing, masking, subsetting and provisioning. Scheduled and automated refreshes deliver data into CI/CD pipelines, test automation and agent evaluations.

UNIFIED TDM: SAP & NON-SAP COMPLIANT DATA

Non-native SAP TDM struggles with complex modules, expensive full-copy refreshes, and stalled automation. Synthesized is built differently.

AI-native, not retrofitted: Built for AI-ready enterprises and Agentic QA. ML-driven test data generation and AI-powered schema discovery are core to the platform, not add-ons.

SAP-native intelligence: Purpose-built SAP HANA / S/4HANA integration understands module boundaries, virtual foreign keys, and business logic, where generic TDM tools break.

One platform for SAP + non-SAP: Uniquely unifies SAP and non-SAP TDM in a single control plane, so end-to-end flows across S/4HANA, Ariba, and Salesforce stay consistent.

Governed & compliant by default: Policy-driven privacy controls aligned to GDPR and SOX remove PII while retaining realism across every non-production environment.

No vendor lock-in: Private cloud, on-prem, or hybrid deployment with a minimal footprint adapts to your enterprise architecture, not the other way round.

CAPABILITIES

• SAP-native integration: Direct SAP HANA / S/4HANA connectivity with module-aware scoping and virtual foreign-key mapping that understands master & transactional data and SAP business logic.
• Test data generation: ML-driven test data that mirrors SAP distributions while removing PII, preserving business logic and edge cases at any scale.
• Lifecycle automation: Copy, time-slice, subset, mask, generate, and provision: every operation from one SAP-native TDM platform.
• Cross-system coverage: Consistent datasets across SAP and non-SAP apps for Order-to-Cash, Procure-to-Pay, Record-to-Report, and more.
• Schema intelligence: AI-powered discovery of SAP module relationships and dependencies, cutting initial setup from weeks to hours.
• DevOps & CI/CD: API, CLI, YAML & business-UI workflows and data-as-code embed test data into CI/CD, GitOps, and environment refreshes.
• Deployment options: Private cloud, on-prem, or hybrid deployments with a minimal footprint and no vendor lock-in.

EASY FLEXIBLE USE

Sythesized is easy to use, with rapid time to value for technical and non-technical users.

1. Easier adoption and faster value: Guided, low-code workflows simplify test data preparation. Teams can get started faster and make repeatable refreshes part of everyday testing.

2. Fewer specialist prerequisites: Teams can prepare test data without first becoming programming or database experts. This reduces reliance on specialist skills for routine tasks.

3. SAP complexity handled for you: AI-powered relationship discovery reduces manual mapping across SAP modules and connected systems. Business-process-level generation preserves the relationships and business logic needed for scenarios such as Order-to-Cash and Procure-to-Pay.

4. Broader SAP ecosystem coverage: Expanded API-level support extends test data workflows across the SAP ecosystem. Teams can coordinate SAP and connected non-SAP test data through one platform.

5. SAP Clean Core alignment: The API-level approach supports a Clean Core-aligned test data strategy. Teams can modernise test data operations while keeping SAP core integrity central to their architecture.

Synthesized runs inside your own environment, keeping production data within your boundary. It supports continuous SAP testing, S/4HANA migration validation and cross-system testing, with availability on SAP Store.

For organisations moving towards the autonomous enterprise, the proposition is practical: make trusted test data easier to access, automate and govern. Give every team a stronger foundation for testing change.

Tonic.ai is designed to streamline the creation of synthetic data for testing and development, enhancing data privacy and security. It serves industries that require safe and realistic data solutions without compromising sensitive information.

Utilizing Tonic.ai facilitates the generation of responsive synthetic data tailored to customer-specific scenarios. It offers data de-identification, supports consistent data quality and is adaptable to complex data environments. This makes it suitable for data-driven industries where security and accuracy are paramount. By foregrounding safe data management practices, Tonic.ai ensures compliance with industry regulations while empowering development and testing teams with realistic datasets.

• Data Anonymization: Protects sensitive information while preserving data utility.
• Data Subsetting: Allows selection of relevant data segments for more efficient testing.
• Data Synthesis: Creates realistic data that mimics production environments.
• Automated Data Generation: Reduces manual workload and accelerates testing.
• Customizable Data Merging: Supports diverse data formats and sources.

• Enhanced Data Security: Safeguards confidential information.
• Improved Testing Efficiency: Enables realistic testing scenarios.
• Time Savings: Speeds up data preparation processes.
• Cost Reduction: Decreases resources needed for handling datasets.

Tonic.ai can be implemented in industries like finance and healthcare where data privacy is critical. For example, healthcare companies can generate synthetic patient data for research, ensuring compliance with privacy laws. Finance sectors can use Tonic.ai to create anonymized transaction data for developing fraud detection models.