MELBOURNE, FL – 15/03/2026 – (SeaPRwire) – Skymantics, LLC has announced the integration of its DataGenesis synthetic data engine with the Anna Orchestration Layer developed by Geo Orchestration AI. The collaboration is designed to provide government and enterprise users with a unified simulation environment capable of generating high-fidelity synthetic datasets for advanced AI orchestration and scenario modeling.
As organizations increasingly adopt AI-driven decision systems, the demand for large-scale, high-quality data continues to grow. However, strict privacy regulations and protections for personally identifiable information (PII) often limit access to real-world datasets. This challenge has made it difficult for orchestration platforms to model complex systems with realistic data inputs.
The newly announced integration addresses this limitation by combining the orchestration capabilities of the Anna platform with synthetic datasets produced by Skymantics’ DataGenesis engine. The system generates Isomorphic Synthetic Data, which preserves the statistical characteristics and longitudinal patterns of real populations while removing direct connections to identifiable individuals.
According to Brad Molander, the integration aims to provide a more complete simulation environment for organizations exploring long-term operational scenarios.
“Anna functions as a powerful orchestration platform, but complex simulations require a deep and dynamic data foundation,” Molander said. “By pairing DataGenesis with the Anna orchestration environment, users gain the ability to model evolving systems—such as healthcare demand or regional economic changes—while maintaining strict privacy safeguards.”
Building a Privacy-Safe Data Foundation for AI Orchestration
The joint solution introduces several capabilities intended to support AI-driven modeling and planning in sensitive operational domains.
Zero-Trust Intelligence
Through the integration of synthetic datasets, the Anna orchestration platform can now support simulations across domains that typically involve highly sensitive information, including healthcare records, tax data, and other regulated datasets. Because the underlying data is fully synthetic, the system enables analysis without exposing real-world personal information.
Temporal Evolution Modeling
The DataGenesis engine generates longitudinal datasets that evolve over time, enabling digital population models to reflect dynamic changes rather than static snapshots. This allows orchestration systems to analyze how simulated populations respond to economic shifts, policy changes, or resource constraints across extended time horizons.
Provenance and Systems Engineering Experience
The integration also incorporates Skymantics’ experience in federal systems engineering. By combining these capabilities with Geo Orchestration AI’s flexible orchestration framework, the platform is intended to support the rigorous data governance and information management standards required in many government environments.
Enabling Advanced “What-If” Scenario Modeling
With the combined technology stack, users can design large-scale simulations that evaluate long-term outcomes across multiple sectors. For example, organizations may use the platform to simulate healthcare system demand over multiple years, test economic development strategies, or evaluate infrastructure planning scenarios.
The developers say the integration provides a scalable “plug-and-play” simulation environment in which orchestration logic and high-fidelity synthetic data operate together within a single platform.
About Skymantics
Skymantics, LLC specializes in model-based artificial intelligence, systems engineering, and synthetic data generation. The company focuses on bridging legacy data infrastructure with advanced simulation environments, enabling public sector agencies and enterprise organizations to analyze complex systems and modernize data-driven operations.
source https://newsroom.seaprwire.com/technologies/skymantics-announces-integration-of-datagenesis-with-anna-orchestration-layer-to-advance-ai-simulation-capabilities/
