Patent-pending machine learning technology learns how experts work within enterprise applications and turns their know-how into contextual guidance, helping organizations preserve expertise and share it across teams.
Turin, Italy — September 15th, 2026 — Newired announced today the launch of Newired® Virgil, a new machine learning technology designed to help organizations discover, preserve and scale the operational know-how of their experienced employees.
As generative AI becomes increasingly accessible, organizations face a different challenge: much of the knowledge that makes them effective has never been documented. It exists in how experienced people navigate applications, handle exceptions, make decisions and adapt formal processes to real-world situations.
Newired® Virgil addresses this gap by learning from how selected expert users perform activities inside enterprise web applications. Its machine learning technology identifies recurring interaction patterns and alternative workflows, which can then be reviewed and validated before being transformed into contextual guidance for other employees.
“AI is making intelligence available to everyone, but it cannot automatically know what makes a particular organization successful,” said Stefano Rizzo, CEO of Newired. “Newired® Virgil was created to learn from the expertise that already exists inside the company and make it transferable. Our objective is not to replace experts, but to ensure that what they know does not disappear.”
From Digital Adoption to Organizational Learning
Traditional Digital Adoption solutions rely largely on manually created guidance and predefined user journeys. Newired® Virgil extends Newired’s approach by introducing a learning layer that can discover patterns directly from real execution.
Its graph-based approach enables Newired® Virgil to model branching and non-linear workflows rather than relying solely on rigid step-by-step sequences. Contextual predictions can reflect the paths observed during actual work, while event normalization helps make learned journeys more robust to variations in user interaction.
The result is a continuous cycle:
Observe → Learn → Validate → Guide → Improve
The approach is designed to help organizations reduce dependency on individual experts, accelerate time to competence, improve execution consistency and reduce the effort required to discover and maintain digital guidance.
Keeping Organizational Know-How Inside the Organization
Newired® Virgil also introduces a different approach to enterprise AI architecture.
Its patent-pending proprietary machine learning algorithms run on-premises, within the customer’s controlled environment, and are not connected to a Large Language Model. This allows organizations to learn from operational expertise without communicating that know-how to an external LLM.
Availability
For more information, demonstrations and availability, visit https://www.newired.com/newired-virgil.