Talk to us
  • CASE STUDY | THIRD-PARTY LOGISTICS / SUPPLY CHAIN MANAGEMENT

Brainstorming to Jira roadmap in minutes, not days.

A leading third-party logistics provider migrated 25 engineering teams from Azure DevOps to Jira Cloud and deployed an AI-augmented planning layer using the Jira Model Context Protocol (MCP) with Claude. Product leaders now describe a strategic initiative in plain language and push a fully structured Jira roadmap in minutes.

Talk to us
25 engineering teams
300-350 users migrated
Minutes brainstorm to roadmap
AI Epic generation live
  • ON THIS PAGE
Industry Third-Party Logistics / Supply Chain Management
Migration Azure DevOps to Jira Cloud
AI Layer Jira MCP + Claude integration
Scale 25 engineering teams, 300-350 users
Partner Tier Atlassian Platinum Solution Partner
Talk to us
  • THE CLIENT

Who is the client?

A leading provider of technology-enabled transportation and supply chain management services operates 25 engineering teams building and managing integrations between shippers, carriers, and an internal logistics platform. With a product organization described as heavily waterfall-oriented, the goal was both a cleaner Jira foundation and a faster path from strategic initiative to execution.

  • THE BUSINESS CHALLENGE

Legacy complexity. Manual planning. Slow execution.

01

Legacy Complexity

An over-customized Azure DevOps environment made cross-team visibility difficult and slowed standardization across 25 teams.

02

Waterfall Mindset

The product organization struggled to translate high-level strategic initiatives into actionable Jira Epics without extensive manual work.

03

Planning Overhead

Moving from a brainstorming session to a populated Jira roadmap took days of manual data entry.

04

Fragmented Architecture

No standardized structure linked domain-specific Epics to parent initiatives for automated status roll-ups.

  • PROJECT OBJECTIVES

A clean Jira foundation with AI-augmented planning.

01

Standardization

Establish a company-managed Jira blueprint replacing fragmented ADO processes across all 25 teams.

02

Efficiency

Reduce operational costs and tool administration overhead.

03

AI-Driven Planning

Enable product leadership to use Claude with the Jira MCP as a planning partner, bridging brainstorming and Jira execution.

04

Unified Architecture

Link domain Epics to parent Initiatives for automated roll-ups across Carrier, Shipper, Data, and other domains.

  • THE TRUNDL SOLUTION

Jira Cloud foundation plus AI-augmented planning.

01

Jira Cloud Foundation

Established a clean, company-managed Jira environment with a consistent blueprint across all 25 engineering teams, replacing fragmented ADO configurations.

02

Jira MCP Configuration

Configured the Jira Model Context Protocol for the organization's environment, enabling Claude to read and write to the correct Jira spaces using secure Atlassian API tokens within administrator-defined boundaries.

03

AI-Driven Epic Generation

Product leaders describe a strategic initiative in plain language to Claude, which drafts and pushes corresponding Epics into the correct domain Spaces (Carrier, Shipper, Data, etc.) following standardized naming conventions and hierarchy.

04

Unified Execution Plan Architecture

All AI-generated work follows the standardized hierarchy, linking domain Epics to parent strategic Initiatives for automated status roll-ups across the portfolio.

  • DELIVERY HIGHLIGHTS

Quality, value, and speed.

QUALITY Standardized from day one

AI-generated Epics follow the same format and naming conventions as manually created items, ensuring consistency across all 25 teams immediately.

TIME TO MARKET Minutes, not days

The time from brainstorming session to a fully populated Jira roadmap dropped from days of manual entry to minutes.

VALUE ADD AI-augmented Agile

Product leadership moved from a waterfall planning cycle to an AI-assisted flow. Leadership situational awareness across the full portfolio updated in real time.

  • FAQ

Frequently asked questions.

How does the AI integration handle security?

The Jira MCP uses secure Atlassian API tokens and operates only within the specific projects and fields explicitly permitted by Jira administrators. Claude has no access beyond what is configured.

Do AI-generated Epics work with existing boards and reports?

Yes. AI-generated Epics follow the standardized blueprint and are immediately compatible with existing boards, filters, and dashboards across all 25 engineering teams.

Did AI replace the need for Solution Architects?

No. Trundl’s Solution Architects designed the underlying Jira architecture and rules of engagement the AI follows. The AI accelerates execution within a structure that humans designed and control.