A Fortune 500 Fintech Leader Enables Agentic PDLC with Dragonboat

How a Fortune 500 financial technology company built the operating foundation for agentic product and engineering at scale.

The Goal: 3x Speed for Product Innovation and Delivery

This Fortune 500 financial technology company serves hundreds of millions of customers across dozens of products, led by product executive ownership of its own portfolio and a shared technology platform organization.

The executive team set a clear goal: 3x the speed of product innovation and delivery. The path forward was to transform the PDLC into an agentic operating model where AI and agents are adopted across product, engineering, and business functions. To deliver on that, the company brought in PwC alongside a product engineering ops consultant for transformation and change management. Together with the CTO’s office and Business Operations, they formed a mission team to evaluate and select the right AI PDLC platform for their toolstack.

As the CTO framed it:

“Transformation needs the right operating foundation.”

 

— Chief Technology Officer

Current State and Challenges

The company already had a solid foundation: a robust data lake streaming critical data across tools, LeanIX for enterprise architecture and capability mapping, and an active Jira on-prem to Jira Cloud migration underway via an Atlassian partner.

But the PDLC operating plane told a different story. The internally built dependency management tool was no longer meeting the needs of an agentic PDLC. And like most enterprises grown over the years, the team was managing a fragmented mix of Smartsheet, Airtable, Aha, Productboard, PowerApps, and custom-built tools spanning strategic planning, demand management, dependency tracking, and in-year execution. Each carried its own semantics and context. Connecting them to get any insight or make any decision required manual stitching — resulting in slow decisions, slow action, and compounding tool maintenance costs.

AI tools weren’t solving it either. Glean search results were suboptimal. The deeper issue was structural – tools are not smart, there are no protective agents to detect, flag, or act on risks and signals. A fragmented toolstack doesn’t just slow humans down; it makes agentic operation impossible.

“Current tools do not support scenario planning, forcing us to build custom solutions to assess the impacts of change.”

 

— Platform Engineering Lead

The Evaluation

A cross-functional team of PwC consultants, a PDLC transformation expert, and members of Technology and Business Operations aligned on the new agentic PDLC, and a new enterprise toolstack to support the agentic operating model — where a product operating platform for strategic product and portfolio management, linking strategic planning, Jira, data lake, and enterprise architecture.

The evaluation was comprehensive: existing tools — Jira Product Discovery, Airtable, Aha!, Productboard, Smartsheet, LeanIX, and internal solutions — were assessed alongside new SPM and PPM tools, including ServiceNow SPM, Planview, Jira Strategy Collection, and more.

Each filled part of the need but failed to support the full agentic operating model. Product tools like Aha! or Productboard couldn’t model the product portfolio and dependency management at the required complexity. Jira Align requires a prescriptive operating model and too disruptive to engineering workflows. Planview was too heavyweight and project-centric. ServiceNow SPM was too IT-centric, with a taxonomy misaligned to the product operating model. Customized tools like Airtable or homegrown solutions simply can’t scale to meet the ontology and semantic data needs of an agentic operating model.

“Users must manually connect data across tools to get connected insight across taxonomy. The roadmap today is in slides — multiple meetings, lots of people, lots of hours to get to one C-suit level view.”

 

— Group Manager, Business Office

A key requirement emerged: the platform couldn’t just connect tools or surface data. It needed to actively operate — detecting issues, updating context, and flagging risks — so that executives, teams, and agents could always act on live truth — requiring an ontology-based platform built for the modern agentic operating model.

The Decision

Dragonboat was selected as it’s the only complete platform that covers all key elements of the product operating model and fits in the agentic operating toolstack.

More specifically, on five decisive dimensions:

Modern ontology for the product operating model. Dragonboat’s elastic data model — objects, links, and interactions across the full PDLC — fits the company’s operating reality from strategy to product to capabilities to dependencies natively. This enables simultaneous product, engineering, and org-based perspectives for decision and action from the same underlying data, without custom development or heavy implementation.

Built for the agentic era — headless and actively operating. Dragonboat is not a passive data layer. Its ambient agents detect risks, identify data errors, and flag portfolio issues 24/7 — before they become delivery problems. Its headless design means teams and agents work from wherever they already operate — Slack, MCP, Jira, API — while Dragonboat maintains an active ontological data foundation as the source of context, memory, and runtime portfolio intelligence. Clean, updated data streams in and out of the data lake for broader enterprise use.

“With other vendors what we’re seeing is just more superficial AI. The potential here is a real differentiator.”

 

— Group Manager, Business Office

Toolstack ready, zero disruption. From internal tools to data lake to enterprise architecture and Jira, with tens of thousands of users mid-migration from Jira Server to Jira Cloud, the team couldn’t afford workflow disruption. Dragonboat connected to both environments seamlessly, with custom mapping and multi-instance support adding flexibility across the transition — without touching engineering workflows.

Proven at enterprise scale with robust data governance. Dragonboat’s architecture supports tens of thousands of product managers and engineers, with governance built in and multi-instance structure allowing each business unit to maintain CPO-level portfolio ownership while rolling up into a single enterprise view.

Domain expertise and supported by expert success teams. An ontological system is only as good as the domain expertise built into it. Dragonboat’s founding team and in-house experts are real operators, and best practices refined across thousands of enterprise teams are embedded in the platform — not available elsewhere.

Success & Momentum

Four months in, the results are tangible. The company’s multi-quarter roadmap is live and operational across a connected toolstack. Strategies and bets are pulled in from the top; initiatives and work auto-update to and from Jira. Stack-rank and above-the-line/below-the-line prioritization now run on live data in CTO and VP planning sessions — replacing pre-packaged decks with a shared real-time decision surface. OKR-to-Epic traceability gives every investment a traceable line to the outcome it supports, auditable at every altitude.

“I can use 6Q Roadmap view to see an end-to-end view of the work that supports my outcomes and pivot against different dimensions — org, capability, etc.”

 

— Group Manager, Business Office

Dependency management is now connected with enterprise capabilities, used across TPM, core product, business operations, planners, and engineering teams — accelerating cross-product, cross-portfolio prioritization, planning, and orchestration.

“The engagement was excellent. People are really seeing the trains coming and we better get on board.”

 

— PDLC Transformation Lead

Dragonboat now sits as the active orchestration layer with PDLC apps in a purpose-designed agentic stack: Dragonboat for product portfolio and dependency management, Jira Cloud as the engineering work management layer, agentic coding tools including Claude and Cursor, LeanIX for enterprise architecture, Slack as the communication front door, MCP access for agent visibility, and clean data streaming to the internal data lake for business and operational intelligence.

The companies that move fastest in the agentic era are the ones with a unified semantic operating system — one that leaders, teams, and AI can all operate on. This company built that system.

Ready to Build Your Agentic Stack?

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