Scalefusion puts device trust at the centre of AI-era security

As AI makes cyber threats harder to predict, Scalefusion Chief Product Officer Sriram Kakarala explains how linking device security with access decisions can help enterprises protect sensitive data, enforce policies consistently and respond faster when security gaps emerge.

As AI makes cyber threats faster and harder to predict, enterprises need to reduce the time between identifying a security exposure and fixing it, says Sriram Kakarala, Chief Product Officer at Scalefusion. For Kakarala, that starts with reassessing whether a device or application can still be trusted as the conditions under which it accesses data change.

“Data security is only as strong as our understanding of the context in which data is accessed, used and secured,” Kakarala says. In an enterprise, he adds, that context rarely stays the same. A device’s security and compliance status can change, and access decisions need to reflect those changes.

Connecting device security with access decisions

Scalefusion applies that principle through a Zero Trust approach. Kakarala says the company brings endpoint management, security, identity and access together in a single dashboard through its unified endpoint management (UEM) offering, Veltar and OneIdP. This connects decisions about whether a device meets security requirements, whether a user should have access and what action to take if either condition changes.

As privacy and regulatory expectations evolve, Kakarala says enterprises need to be able to enforce policies consistently, adapt them as risks change and show that the controls are working. He points to the link between device status and access as a differentiator for Scalefusion. A compliance gap triggers corrective action, while security controls stay with the endpoint wherever employees work.

Measuring how quickly exposures are resolved

Kakarala identifies four measures enterprises can track to assess how well their controls are working: compliance posture, unresolved vulnerabilities, remediation time and access-policy violations. Together, these measures help security teams see where gaps remain and how quickly they are addressed.

“As AI makes threats faster and harder to predict, the advantage comes from shrinking the time between detecting exposure and actually removing it,” he says.