# Synthesized > AI\-powered Test Data Management for regulated industries ## At a glance | Field | Value | | --- | --- | | Category | Data & Analytics | | Type | Solutions Provider | | Region | EMEA | | Headquarters | London, UK | | Founded | 2017 | | Stage | Growth | | Employees | 51-200 | | Funding | Series A | ## Overview Synthesized is a test data management (TDM) platform for enterprise software development and QA teams in insurance, banking, financial services, and other regulated industries. The platform automates generation, masking, and provisioning of production-realistic synthetic data, enabling teams to build and test software without exposing real customer records. The platform addresses a common bottleneck in enterprise delivery: development and test teams cannot safely access production data due to regulations such as GDPR and PCI-DSS, yet manually created or masked datasets are slow to produce and unrepresentative of real conditions. Synthesized generates high-fidelity synthetic datasets on demand using generative AI, expressed as YAML or Python configurations and integrated into CI/CD pipelines. It supports major insurance core systems including Guidewire, Duck Creek, and Majesco, as well as cloud data platforms such as Google BigQuery. In September 2025, the company raised a USD 20M Series A led by Redalpine Venture Partners, with participation from IQ Capital, Mercia Ventures, Seedcamp, and strategic investors UBS Next and Deutsche Bank. Deutsche Bank reports halving time-to-test-data since deployment; UBS reports a 40% reduction in QA costs. The company plans to grow its team from approximately 35 to 70+ employees over the following year. ## Products & services ### Synthesized TDM Platform An end-to-end test data management platform providing generation, masking, and subsetting of production-realistic synthetic datasets for enterprise software testing. **Key features:** - On\-demand generation of datasets tailored to test scenarios using generative AI that analyzes schema relationships and constraints - Codified masking rules that anonymize sensitive PII for GDPR, PCI\-DSS, HIPAA, and other frameworks - Role\-based subsetting for access to relevant data slices, reducing storage costs and data exposure - LLM\-assisted configuration generation from natural language requirements *Target users:* Development, QA, and data engineering teams in insurance, financial services, and regulated industries ### Synthesized TDK \(Test Data Kit\) A focused test data management tool for database provisioning with automated sensitive data detection and time-slicing capabilities. **Key features:** - Automated detection and classification of sensitive data fields - Time\-sliced data snapshots for consistent test environments - CLI and API\-first design for integration into CI/CD workflows *Target users:* Database administrators and DevOps engineers ### Synthesized SDK An AI-driven data generation library for machine learning and custom datasets. **Key features:** - Python SDK for programmatic dataset generation - Support for LLM\-assisted configuration workflows - Statistical preservation of distribution properties from source data *Target users:* Data scientists and ML engineers ### Synthesized FairLens A data quality and fairness analysis tool for validating synthetic data integrity. **Key features:** - Distribution analysis comparing synthetic to source data - Fairness metrics for bias detection in generated datasets - Integration with the TDM platform for quality gates *Target users:* Data governance and compliance teams ### Data as Code A methodology built into the platform allowing data requirements to be expressed in YAML configuration files or a Python DSL, enabling version control, peer review, and repeatable data provisioning. **Key features:** - YAML and Python DSL for defining data schemas and constraints - Version\-controlled data configurations compatible with Git - CI/CD integration with GitHub Actions, Jenkins, GitLab, CircleCI, and Apache Airflow *Target users:* Engineering and DevOps teams ## Category & focus - Subcategories: Test Data Management, Synthetic Data, Software Quality Assurance, Compliance & Privacy - Insurance verticals: P&C Commercial, Life & Annuity, Specialty/E&S - Target customers: Carriers, MGAs/MGUs, Brokers ## Notable customers - \*\*Deutsche Bank\*\* \-\- Credit Risk Technology team uses the platform for ESG onboarding testing; halved time to find test data; strategic investor - \*\*UBS\*\* \-\- Overcame regulatory bottlenecks in test data workflows; 40% QA cost reduction; UBS Next is a strategic investor - \*\*European Commission\*\* \-\- Compliant data provisioning across regulated environments - \*\*Accenture\*\* \-\- Enterprise\-scale deployment - \*\*Leading global insurance carrier\*\* \(unnamed\) \-\- Generated millions of representative test datasets for sharing with third\-party vendors; saved 200 person\-hours per project ## Links - Website: - Directory profile: - Blog: - Careers: - Insurance solutions: --- *Last updated: 2026\-05\-18*