Overnight, Lightwell published new fixes.
Here's the morning after.

This Automation Orchestrator view shows the entire workflow and the handoffs between systems. For this demo, we focus on the fast path for these two applications.

TPA reads the Lightwell SBOM to identify the applications using the affected package. It then provides the information the workflow needs to classify risk and route each change.

The Lightwell Deep Agent uses the SBOM findings to analyze changes, create merge requests, and trigger continuous integration, including unit tests. It is one agent, not a fleet. Each decision is recorded in the merge request it opens.

The merge request and its continuous-integration results are in source control. Because wire-transfer-service is PCI-regulated, this change needs a human decision. The agent did the analysis, created the merge request, and ran the checks. Dinesh approves it. Red Hat OpenShift AI and Automation Orchestrator completed the earlier steps.

For Acme Corp’s non-critical application, the same workflow runs without a manual approval step. Once its checks pass, the merge request is approved automatically. Back in Automation Orchestrator, Dinesh can see progress across both applications.

After approval, the change moves into the build pipeline. Trusted Software Factory builds and tests the application, signs the image, and records the results before release. It works alongside the continuous-integration environments Acme Corp already runs.

The critical application moves through an image build, with Automation Orchestrator coordinating the handoff. The non-critical application is already containerized and is ready for deployment through OpenShift. Both versions match the Trusted Software Factory output.

The merge triggered an Event-Driven Ansible event. Automation Orchestrator ran the deployment workflow: the build was verified, the image was signed, and production was updated. The change record closed, leaving a complete audit trail.