Automation of legacy on-premise identity systems
Identity security company SailPoint has unveiled a new solution that leverages AI to significantly accelerate the cloud migration of legacy on-premises identity systems. The company explains that it supports the completion of transition work within a few days, whereas previously it took several months.
SailPoint announced on the 29th that it has launched 'SailPoint Agentic Acceleration,' an AI-based cloud migration methodology.
The company stated that this solution reduces deployment risks and costs by automatically handling even highly complex tasks during the process of enterprises migrating from existing on-premises identity platforms to SailPoint Identity Security Cloud.
The core technology is 'SailPoint Virtual Architect'.
The company explained that it converts legacy configurations, workflows, and policies into a form that can be immediately deployed to a cloud environment using an AI engine trained on 20 years of accumulated identity security expertise and global large-scale enterprise deployment experience.
Unlike the existing 'Lift-and-Shift' method, it supports verifying in advance how actual applications and provisioning processes operate in a cloud environment before the full-scale transition.
Matt Mills, President of SailPoint, said, “By automating most infrastructure tasks, we are removing the barriers of time, cost, and risk that have delayed digital transformation,” adding, “Customers will be able to realize the value of their cloud investment almost immediately.”
Agentic Acceleration is SailPoint's on-premise product, IdentityFor all customers migrating from IdentityIQ or competitor legacy solutions to Identity Security Cloud, dedicated field engineers (Forward Deployed Engineers) are provided at no additional cost.
The company also stated that it is being utilized as a means to support the partner ecosystem, enabling partners to quickly launch transition projects and focus on responding to security demands arising from the proliferation of AI agents.