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Case study — Tokio Marine

Tokio Marine mapped 28 systems and its next steps in two weeks.

Financial services

A searchable application inventory, an AI governance policy and a four-phase roadmap gave Tokio Marine a clear path from discovery to execution.

To a delivered roadmap
2 weeks
Legacy systems mapped
28
Technology decisions made
13
Typical discovery timeline
4-6 months

The challenge

Before deciding where to use AI, Tokio Marine needed a clear picture of the systems it already ran. That meant understanding how its applications fitted together and which technology decisions would shape the work ahead.

Building that inventory and agreeing a direction would typically take four to six months. The team needed a plan it could act on sooner.

What we built

In a two-week engagement, Parallel Loop brought the application estate, architecture decisions and AI adoption plan together.

  • Mapped 28 legacy systems into an enterprise application inventory.
  • Created an architecture document that teams can query with AI.
  • Developed an architecture blueprint and roadmap to the future state.
  • Established an AI governance policy to guide adoption.
  • Resolved 13 technology stack decisions as part of the work.

The impact

Tokio Marine finished the engagement with a defined AI strategy and a four-phase execution roadmap. The application inventory and future-state architecture gave that plan a concrete foundation.

  • Discovery and planning completed in two weeks, against a typical four to six months.
  • One searchable view of the application estate to support future decisions.
  • A clear sequence of work that moved the strategy conversation towards execution.
Parallel Loop

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