BackBox Adds AI to Network Automation With Human Approval Gates

Network automation vendor BackBox has introduced Kilter AI, an intelligence layer that applies artificial intelligence to vulnerability management and configuration tasks while requiring human approval before any changes execute in production environments.

The company has rebranded its network resilience platform as Kilter AI and embedded AI capabilities across lifecycle management, configuration, and vulnerability functions. The system analyzes network data, identifies issues requiring attention, and recommends remediation actions—but stops short of autonomous execution.

The human-in-the-loop approach

BackBox CEO Rekha Shenoy describes the architecture as a "smart intern" model. Kilter AI processes large volumes of network and vulnerability data, determines what needs remediation, and proposes solutions. Network engineers retain final authority over whether those solutions deploy.

"We're seeing customers that are getting more comfortable with automation that are afraid of AI," Shenoy said. She cited one global service provider that discovered it had inadvertently given an AI system sufficient access to make network changes independently. "There's no accountability, and that's what scares them."

When Kilter AI generates an automation workflow, it presents the sequence as a human-readable visual chain showing each step. A typical workflow might back up a device, test its configuration, apply a change, test again, and create another backup if successful. Failed changes can trigger ServiceNow tickets for manual investigation.

Administrators can test AI-generated automations in non-production environments before approving them for production use. Enterprises can also deploy changes using canary-style rollouts rather than fleet-wide updates.

Addressing multi-vendor complexity

The system draws on vendor vulnerability information, BackBox's library of more than 5,000 tested automations covering 180 vendors, and activity patterns within the customer's environment.

Shenoy emphasized that network infrastructure presents unique patching challenges compared to server environments. Enterprise networks typically include switches, routers, firewalls, and VPN devices from multiple vendors, each running different software versions. Unlike homogeneous Windows or Linux server fleets, this diversity makes vulnerability tracking and remediation particularly difficult.

For example, an enterprise might face hundreds of CVEs across network devices. Kilter AI can analyze which vulnerabilities apply to specific devices in the environment and determine whether a configuration workaround or software patch is required.

The infrastructure demands associated with AI deployments add another layer of complexity. As enterprises add network devices to support AI-related bandwidth and connectivity requirements, they simultaneously increase the number of devices requiring maintenance and patching.

Why it matters

BackBox's approach reflects a broader tension in enterprise IT: Organizations need automation to manage growing infrastructure complexity, but many remain uncomfortable with fully autonomous AI systems making production changes. By positioning AI as an advisor that generates recommendations rather than a decision-maker that executes independently, BackBox addresses compliance and accountability concerns while still reducing manual workload for network teams. This middle path may prove more palatable to risk-averse enterprises than fully autonomous alternatives.

Kilter AI is available now as an upgrade for existing BackBox customers and as part of the Kilter platform for new customers, according to details first reported by Network World.