Workflow Automation · Across the Whole Stack

Finish What Tickets
Used to Start.

End-to-end workflow automation that stitches the systems of record together — ServiceNow, CMDB, IPAM, DNS, Vault, monitoring, the firewall, the load balancer — into idempotent pipelines that actually complete the request.

ServiceNow Native Idempotent by Design Self-Hosted Runner Git-Backed
// Book a Discovery Call

30 minutes. Let's talk workflows.

Pick a free slot — we'll learn your highest-toil request types and where end-to-end automation could collapse the ticket chain.

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1
Request, zero handoffs
0
Half-finished tickets
Git
Source of truth
100%
Idempotent runs
Why Tickets Stall

The Last Mile Is Always Manual.

  • ✗ A "simple" request touches five systems and three different teams
  • ✗ Flow Designer can route approvals — it can't reliably execute across all your systems
  • ✗ RPA scripts work until a form changes, then fail silently for a week
  • ✗ The last step — CMDB update, DNS record, monitoring add — is always "I'll get to it"
What MutexOps Does

One Python Runner. Every System.

ServiceNow Flow Designer handles routing and approvals. A self-hosted Python runner handles the actual work — idempotent calls into every system the request touches, end to end, with a single audit trail.

// 01 — INTEGRATION CORE

The Connectors That Matter.

Production-grade Python adapters for the systems your workflows actually touch. Auth, retry, idempotency built in.

  • ServiceNow Table + Flow Designer (HMAC webhook)
  • CMDB read/write with relationship awareness
  • Infoblox / BlueCat / phpIPAM for IP and DNS
  • HashiCorp Vault for secrets, dynamic creds
  • Firewall (Palo Alto, FortiGate, Check Point) policy
  • Monitoring (Datadog, Dynatrace, Splunk) registration
// 02 — WORKFLOW RUNNER

Idempotent. Resumable. Auditable.

Workflows defined as Python — typed inputs, declarative steps, automatic state. Safe to retry, easy to extend.

  • Pydantic-typed inputs from ServiceNow catalog
  • Steps are idempotent — re-run after partial failure
  • State persisted per request — resumable mid-pipeline
  • Per-step audit log written before and after the call
  • Failure modes route back to the originating RITM
  • Every workflow definition lives in Git, reviewed via PR
How It Works

From Request to Done — Without a Handoff.

Approvals stay in ServiceNow. Execution moves to a runner that knows how to talk to everything downstream.

01
Request
ServiceNow catalog item
02
Approve
Flow Designer routing
03
Dispatch
HMAC webhook → workflow runner
04
Execute
Idempotent steps across N systems
05
Close Out
RITM auto-closes with full summary
Collapse the Ticket Chain

Which request type spans the most teams?

30-minute discovery call. Bring us your messiest request — onboarding, app provisioning, network change, decom. We'll sketch how it would look as a single idempotent workflow.

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One click. We'll follow up with a Teams invite.

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No SDR sequence. One email, one calendar invite.
FAQ

Common Questions.

Flow Designer is excellent for approval routing and ServiceNow-native steps. It's not great at idempotent retries across heterogeneous external systems, complex state, or testing in CI. We keep the routing in Flow Designer and move the execution to a Python runner that lives in Git, has unit tests, and can replay safely.

Each step is idempotent and writes state before exit. A failure pauses the workflow at the last successful step. Re-dispatching the same request ID resumes from there — no duplicate work, no half-applied changes. For steps that can't be made idempotent (rare), we use compensating actions instead.

It overlaps with iPaaS philosophically but the format is different: workflows are Python in Git, not a graphical canvas in a vendor UI. That trades a little visual approachability for far better testability, code review, and the ability to do non-trivial logic. Right call if your workflows are non-trivial and your team can read Python.

Usually app onboarding or new-server provisioning, because they touch the most systems and have the clearest before/after metrics. Other common starters: firewall rule requests, DNS record changes, decom workflows, AD group provisioning. We'll help you pick the one with the highest leverage during the discovery call.

Yes — that's the point. Workflows live in your Git repo. Your team writes new ones using the same connector library and step framework. We're around for new connectors, hard integrations, and architectural reviews, but day-to-day workflow authoring is yours.