How a Global Networking Company Automated Compliance Across Federated Jira Environments

Company Type

Fortune 100 global enterprise networking and technology company.

Compliance Challenges

• Federated business structure with decentralized compliance ownership.
• Dozens of independently managed Jira instances across business units.
• Resistance to migrating away from Jira for compliance tracking.
• Manual, error-prone evidence collection and audit preparation.

Key Use Cases

• Automated employee offboarding and access-termination controls.
• Centralized compliance workflows within Jira.
• Conditional logic for assessments and task automation.
• Integration of Wiz posture data into compliance evidence pipelines.

Technology Stack

• Compliance Platform: ComplianceCow
• Work Management: Jira (multiple instances)
• HR Systems: Workday, Fieldglass, internal contractor system
• Security Tools: Wiz (security posture management)
• Identity: Duo, Active Directory
• Integrations: AWS, ServiceNow (custom field mapping and reconciliation)

ComplianceCow’s Role

• Middleware for automating compliance across federated Jira environments.
• Dynamic conditional logic and evidence orchestration across systems.
• Custom workflow automation that adapts to each business unit’s tooling.
• Open-box API integrations for posture and identity data.

Deployment & Adoption

• Initial deployment with roughly five core compliance and engineering users.
• Rapid daily customization requests fulfilled by the ComplianceCow team.
• Expanding user base across multiple Jira instances as adoption scaled.

Deployment Outcome

• Centralized visibility for the Global Compliance Team (GCS).
• Reduced manual workload for compliance engineers.
• Faster audit readiness across decentralized business units.
• Enabled creation of an internal “Compliance Rules Team” to maintain custom logic.

This global enterprise operates in a federated model with multiple business units spanning networking, collaboration, and cloud. Each unit has its own leadership and technology stack, while compliance oversight resides with a Global Compliance Team (GCS).

The compliance operating model is a shared responsibility framework:

• Centralized functions: Authentication (Duo, Active Directory), corporate-level compliance policies.
• Decentralized ownership: Business units are responsible for implementing and maintaining compliance for their products, including regulated environments such as FedRAMP-aligned offerings.

The GCS team’s challenge was twofold:

• Fragmented tool landscape: Dozens of independently managed Jira instances across business units, each with unique workflows and routing rules.
• User resistance to process changes: Leadership considered using the company’s internal collaboration platform for compliance, but engineering teams strongly resisted migrating away from Jira.

Without a solution, compliance workflows would remain manual, error-prone, and opaque, increasing the risk of missed evidence, delayed audits, and operational inefficiency.

Executive Summary

A Fortune 100 technology company and global leader in enterprise networking faced an increasingly complex compliance landscape. Managing evidence collection and assessments across multiple business units, each with its own tools, workflows, and compliance obligations, posed a significant operational challenge.

ComplianceCow enabled this organization to centralize compliance operations without disrupting engineering workflows. By orchestrating automation across multiple Jira instances and delivering deep customization, ComplianceCow helped the compliance team achieve visibility, reduce manual effort, and improve readiness for audits at scale.

The company selected ComplianceCow to address these challenges by:

• Meeting teams where they work: Automating compliance workflows inside Jira without forcing engineering teams to adopt new tools.
• Providing deep customization: Allowing the compliance team to define conditional logic, orchestrate tasks, and create automated workflows across multiple Jira instances-capabilities Jira lacks natively.
• Future-proofing integrations: Offering open APIs and flexible connectors for systems such as Wiz, enabling security posture data to flow into compliance evidence pipelines.

1. First Use Case: Automating Employee Offboarding Controls Across Workday, Fieldglass, and Internal Systems

The first deployment wave focused on automating enforcement of termination policies across Workday, Fieldglass, and an internal contractor system.

• Three HR and contractor systems were connected to validate contract end dates and enforce access disablement after a defined grace period.
• Prior to automation, delayed deprovisioning across these systems created recurring audit exceptions.
• Automation ensured access removal for contractors beyond contract expiration plus defined grace periods, closing a recurring compliance gap.

2. Integrating Compliance Workflows Into Jira for Continuous Evidence Collection

• Compliance assessments in ComplianceCow automatically trigger Jira stories, epics, and tasks, enabling engineers to respond within their standard sprints.
• Sub-tasks represent specific controls (for example, MFA enabled, access reviews completed), and evidence is uploaded directly to Jira tasks.
• Responses and evidence sync back to ComplianceCow for centralized oversight by the GCS team.

3. Using Dynamic Question Logic to Eliminate Manual Follow-Ups in Compliance Reviews

• ComplianceCow introduced dynamic question sets (for example, “If X is true, follow up with Y”), a capability Jira cannot support natively.
• This reduced errors and manual follow-ups caused by Jira’s free-text limitations and one-size-fits-all forms.

4. Connecting Wiz, AWS, and ServiceNow Data for Contextual Compliance Evidence

• Wiz integration: Correlates security posture data with compliance controls.
• Unlike prescriptive vendors, ComplianceCow’s integration allows custom field mapping and data enrichment, empowering the client to tailor reports and workflows.
• The company favored this “open box” integration model over prescriptive tools such as Drata or Vanta, enabling it to define which Wiz data to ingest, reconcile findings against AWS and Jira, and enrich evidence sets for internal reporting.

5. Delivering Daily Customizations Through ComplianceCow’s No-Code Workflow Engine

• Daily customization requests from the client were fulfilled rapidly by the ComplianceCow team.
• This reinforced ComplianceCow’s flexibility compared to template-driven competitors and helped the program keep pace with evolving compliance needs.

6. Scaling Adoption Through a Core Compliance and Engineering Team

• Initial deployment involved a small core group of roughly five users spanning compliance and engineering functions.
• New users were continuously added under the company domain as adoption expanded across multiple Jira instances.

• Manual effort reduced: Automated task creation and evidence handling across Jira environments eliminated redundant administrative work.
• Improved visibility: The GCS team now has a consolidated compliance view without requiring direct access to each Jira instance.
• Faster audit readiness: Orchestration of assessments and evidence collection reduced coordination delays across business units.
• Scalable operations: The compliance organization can operate at scale without disrupting engineering velocity.

The organization also reports significant qualitative gains as tedious coordination work was replaced by automated workflows. These outcomes positioned ComplianceCow as a trusted strategic partner. The company’s compliance engineering group expanded its use of ComplianceCow by forming a dedicated internal “Compliance Rules Team.” This group now authors and maintains custom logic directly within the platform, a capability that drove renewal and deeper adoption.

Key strategic takeaways for CISOs, compliance leaders, and GRC professionals in distributed enterprises include:

• Integration-first beats adoption mandates: Forcing tool changes rarely works; automation succeeds when it meets users where they already operate.
• Flexibility is critical for scale: Compliance obligations evolve and change. Your platform must adapt quickly.
• Middleware creates leverage: A solution that connects systems, normalizes data, and enables orchestration accelerates compliance maturity.
• As more organizations face the same federated reality, the lesson is clear: scale demands automation that adapts. For GRC teams still relying on manual evidence collection and tool workarounds, now is the time to explore what modern compliance automation can really do.
• The outcome is to give teams systems that move as fast as the business does.

What compliance challenges did the global networking leader face?

The organization operated in a federated model with multiple business units and dozens of independent Jira instances. Manual evidence collection and resistance to tool changes made it difficult to achieve visibility and audit readiness at scale.

How did ComplianceCow automate compliance across Jira environments?

ComplianceCow embedded automation directly into Jira, orchestrating tasks and evidence across multiple instances. It enabled dynamic conditional logic, centralized oversight, and integrations with Wiz, AWS, and ServiceNow for contextual evidence collection.

What were the key outcomes of deploying ComplianceCow?

The compliance team achieved centralized visibility, reduced manual effort, and improved audit readiness. The organization also formed an internal Compliance Rules Team to manage custom logic and workflows, leading to faster adoption and renewal.

Why is this case relevant for CISOs and GRC leaders?

It illustrates how federated enterprises can modernize compliance without forcing tool migrations. Integration-first, flexible middleware platforms like ComplianceCow help distributed teams scale compliance automation while maintaining engineering velocity.