Synthesized joins 8thElement’s AIM framework for enterprise AI testing

Synthesized has become 8thElement’s preferred test data automation partner, embedding its platform into the consultancy’s AIM framework for enterprise AI programs. Financial terms were not disclosed, and the deal is aimed at a specific infrastructure problem: helping companies test models, agents and modernization workflows against realistic data without moving sensitive production data into less controlled environments.

8thElement’s AIM framework, short for Assess, Implement, Mature, is used to move AI initiatives from early evaluation into deployment and ongoing operation. Synthesized’s role in that process is to provide governed synthetic and masked datasets that retain the statistical patterns and record relationships needed for production-like testing.

The joint offering is available immediately for AIM engagements. It is designed for SAP and non-SAP enterprise data estates, including SAP S/4HANA migrations, application modernization projects and agentic AI deployments.

The buyer problem is familiar to large enterprises trying to move AI out of pilot mode. Models may perform well on curated datasets, while production systems contain rare events, skewed distributions and messy dependencies that expose bias, drift or brittle behavior. Privacy rules and internal controls often prevent teams from copying live data into development, test or model-validation environments.

Conventional masking can also create problems if it breaks relationships between records, while synthetic datasets can be too tidy if they fail to preserve the edge cases that matter. The partners are positioning the integration as infrastructure for more realistic validation rather than another front-end AI tool.

Within the Assess stage, Synthesized’s schema intelligence is used to identify sensitive data, relationships and quality issues across SAP and non-SAP systems. Those findings feed into 8thElement’s review of data, model, process and governance readiness.

During implementation, teams can use synthetic and masked data on demand for models, agents and business workflows. The companies said the datasets are designed to preserve referential integrity while reducing the need to place production copies in non-production environments. Audit trails are also included for governance and review.

In the Mature phase, the integration supports recurring test data provisioning for regression testing, drift detection and continuous validation as enterprise systems change. The same pattern applies across software releases, S/4HANA migration stages and expanded agentic AI workflows.

The governance angle is central to the pitch. The offering is designed to keep production data inside secure environments while using synthetic or masked data for development and testing. The partners said those capabilities can support programs tied to GDPR, CCPA and HIPAA, as well as change-control processes associated with SOX. They also noted that synthetic data does not replace an organization’s own legal, compliance or anonymization review.

Santosh Rajput, president of 8thElement, said enterprise AI readiness depends on whether systems are validated with data that reflects production reality, not just clean test sets. Nicolai Baldin, Synthesized’s founder and CEO, described the partnership as a way to add a missing operational layer for teams that need realistic testing without compromising privacy or delivery schedules.

Initial focus areas for the governed test data automation for AIM engagements include test data modernization, regulated-industry agentic AI deployments and AI-driven application modernization across enterprise data estates.