Governed agentic patching
for infrastructure that
cannot pause.

Remediate thousands of configuration items per cycle without expanding headcount. Every run follows your CAB policy, produces signed evidence, and stays reversible at every gate.

Outcomes for
Operates inside
ServiceNow Ansible AAP HashiCorp Vault Nexus / Artifactory NetBox Robot Framework
SOC 2-aligned NIST 800-53
Human-in-the-loop

Approvals at every state transition.

Agents propose. Engineers approve. Every gate is traceable, signable, and reversible in ServiceNow.

Evidence-first

Signed artifacts for every CI.

Pre-checks, post-checks, configs, and diffs are captured in HTML, JSON, and YAML for audit-ready review.

Your estate, your data

Runs in your VPC, with your creds.

No external SaaS plane. Secrets stay in Vault. Execution is orchestrated inside your control plane.

Bounded blast radius

Canary, cohort, rollback, by policy.

Every change respects maintenance windows, CI-class limits, and rollback criteria.

01 The Problem

Enterprise patching stalls before the first device is touched.

Every remediation cycle crosses inventory, advisories, maintenance windows, approvals, execution, validation, and evidence. At scale, those steps move through disconnected systems, manual handoffs, and serialized gates.

Cumulative engineer-hours this quarter
4,500hrs
11,200
devices touched
2,800
devices remaining
184
manual handoffs
Forecast At this pace, completion lands Monday 04:14, well after business hours start.

Advisory overload

Teams manually interpret vendor notices and map them to impacted assets.

triage

Inventory uncertainty

CMDB, NetBox, scanners, and spreadsheets disagree on what is actually exposed.

inventory

Maintenance window pressure

Teams compress high-risk work into narrow windows with limited rollback tolerance.

scheduling

Approval fragmentation

CAB, security, operations, and application owners approve in different systems.

approvals

Serial execution

Work runs device by device, region by region, instead of policy-safe parallel cohorts.

execution

Evidence scramble

Screenshots, logs, diffs, and approvals are collected after the fact instead of by design.

evidence
$ Annual cost of manual remediation
18,000hours / year
Manual firmware upgrades consume engineering capacity before execution begins, not counting outages, audit findings, rework, or burnout.
≈ 8.6 FTE
annually
$1.5M
at $85/hr loaded
02 The governed workflow

One approved request. Every control stays intact.

WWT's SWIM automation service converts a manual patch cycle into a governed remediation workflow. One approved request triggers cohort planning, pre-checks, parallel execution, post-check validation, evidence capture, and change closure across vendors and regions.

Before

The manual runbookManual, serial, audit-unfriendly.

  • SSH into one device at a time
  • Hand-map models to firmware files
  • Eyeball pre/post config diffs
  • Copy terminal output into ServiceNow
  • React to post-window surprises
After

The governed workflowOne request. Policy-gated. Evidence by default.

  • NetBox maps target OS per device
  • Ansible executes vendor-specific playbooks in parallel
  • Robot Framework performs structured pre/post validation
  • Evidence attaches automatically to the change record
  • ServiceNow closes the change when checks pass
From advisory to action

The governed remediation workflow.

AI interprets risk. Humans approve action. Deterministic systems execute and verify.

  1. 01
    Ingest

    Advisory released

    Vendor advisory, CVE, or PSIRT notice enters the workflow.

    Advisory record
  2. 02
    Correlate

    Impact assessed

    AI correlates advisory impact across inventory, exposure, and business criticality.

    Impact map
  3. 03
    Recommend

    Plan generated

    Agentic planning proposes cohorts, windows, eligibility, and rollback.

    Remediation plan
  4. 04
    Approve

    Controls applied

    CAB, blast-radius policy, credentials, and human gates approve the run.

    Approved change
  5. 05
    Execute & validate

    Remediation completed

    AAP executes, Robot validates, evidence attaches, and ServiceNow closes.

    Evidence bundle

AI proposes. Humans approve. Automation executes. Evidence proves.

A governed run, end to end.

Follow one approved remediation wave from pre-check to install, validation, evidence capture, and change closure.

0/5 complete live 0 errors
0:000:571:542:513:48 4:455:426:397:368:33 9:3010:2711:22
sw-dc1-core-01 · Arista
sw-dc1-dist-02 · Cisco Catalyst
sw-campus-03 · Arista
sw-campus-04 · Cisco Nexus
sw-branch-05 · Cisco Catalyst
00:00
00:00 · Approved
CHG0048291 approved. AAP webhook fired. 5 devices queued. Parallel fork = 5.
pre-check install post-check flagged (within threshold)
Runs inside your existing control plane
ServiceNow
Change entry and approvals
NetBox
Source of truth and target state
Vault
Secrets and credential control
Ansible AAP
Parallel execution orchestration
Robot
Pre/post validation engine
Nexus
Firmware, artifacts, and reports
03 The Business Case

Quantify the cost of manual remediation.

Model the engineering capacity, maintenance-window pressure, evidence burden, and risk exposure created by your current patching process.

18,000hrs/yr
Reclaimed
Engineer-hours returned to higher-value work.
$1,530,000
/ yr

At $85 / hr loaded

Direct labor value recovered, before avoided outages, rework, and audit exposure.

3,000devices
10010,000
90min
30120
4cycles
112
80%

Maintenance window reduction

Compressed to a tracked maintenance window. Your team monitors dashboards instead of typing commands.

~0

Manual evidence assembly

Reports, configs, and diffs are generated, attached, and archived automatically. Your handwriting stays out of audit.

Devices managed per engineer

Your people grow the fleet without growing the headcount. The boring work goes away; the senior work stays.

Firmware used to be a risk-register line item. Now it is a scheduled line item with receipts. My board stopped asking about it.
Network Manager·Fortune 500 customer·Post Agentic Remediation, year one

See what governed remediation could unlock in your environment.

We'll model one real remediation workflow against your asset counts, CVE backlog, approval model, automation stack, and evidence requirements.