CASE STUDY

P&C Policy Administration Platform Redesign

Reimagining Policy Administration with Immersive AI

I was asked to reimagine Majesco’s P&C Policy Administration platform and define how AI should function within it. Although AI capabilities existed, they were accessed through a separate copilot, limiting adoption. The goal was to embed intelligence directly into the core workflow.

The Platform Problem

Policy Details was the most used surface in the platform —
but it wasn’t built for decision-making.

It behaved like a transaction log, not an operational control center.

AI existed — but outside the workflow.
Activity was fragmented across tabs.
Risk and sequence were invisible at a glance.

Current State Assessment

The legacy experience was organized around a tab-driven structure that distributed information across disconnected sections.

  • Heavy reliance on tab navigation
  • Limited lifecycle visibility
  • Fragmented contextual awareness

Embedding AI Into the Workflow

Instead of launching a separate copilot, intelligence appears directly within lifecycle events — where users are already reviewing changes, evaluating risk, or making decisions.

  • Entry points embedded within each lifecycle event
  • Context inherited automatically from the policy state
  • AI designed to interpret activity, not just retrieve data

Client Validation Through Live Prototypes

Live client sessions surfaced friction in filtering and quick-access workflows.

Rather than refine visuals, I restructured the filtering model to better reflect how users evaluate lifecycle activity.

  • Client-prioritized filtered views
  • Faster access to high-frequency lifecycle slices
  • A balance of configurability and speed for repeat workflows

Responsive Experience Across Devices

The Policy Details experience adapts seamlessly across desktop, tablet, and mobile while maintaining a consistent interaction model.

Users can review lifecycle events, access key details, and take action from any device without losing context or clarity.

Design considerations:

  • Consistent interaction patterns across breakpoints
  • Progressive disclosure to manage dense information
  • Touch-friendly controls and spacing
  • Prioritized content and simplified metadata for smaller screens

Navigation & Systems Thinking

From the outset, this redesign was treated as a platform system, not a one-off UI refresh.

This enabled leadership to extend the design beyond P&C as a unifying direction across product lines.

  • Global navigation redesigned alongside the timeline
  • Contextual filtering introduced via push panels
  • Decisions made with reuse and extensibility in mind

Design System & Component Mapping

The experience was delivered as a tokenized Figma system mapped directly to Material UI and Angular Material.

  • Tokens for color, typography, spacing, elevation, and motion
  • Component definitions aligned to framework primitives
  • Documented interaction states and variants
  • Accessibility and multilingual considerations baked into defaults

Measuring Success & Strategic Validation

While formal usability testing and production analytics are planned for the next phase, early validation has been strong across executive leadership, product teams, and client audiences. The redesign has been designated a strategic “Big Bet” for 2026 platform evolution.

Executive Alignment

Adopted as Forward Platform Model

  • Endorsed by executive product leadership
  • Repositioned the platform around lifecycle-driven decision surfaces
  • Established scalable structural baseline for AI expansion
Market Validation

Positioned as Differentiated Modernization Strategy

  • Presented in client-facing design sessions and roadmap discussions
  • Recognized as a structural departure from legacy tab-based models
  • Used by product leadership to support modernization initiatives
Organizational Adoption

Influenced Cross-Team Product Thinking

  • Shifted internal conversations toward contextual, lifecycle UX
  • Referenced as modernization template for adjacent modules
  • Strengthened alignment between design, product, and engineering
Forward-Looking Metrics

Defined Leading Indicators for Platform Evolution

  • Reduced navigation depth and context switching
  • Increased task velocity and feature discoverability
  • Positioned AI engagement as a measurable workflow signal

Project Overview

Role

Lead Product Designer (Principal-Level Ownership)

Scope

Experience architecture, lifecycle modeling, AI integration strategy, design system alignment

Team

Design lead managing 2 direct reports; partnered with product and engineering (Angular / MUI)

Timeline

Concept → Fall 2026 planned release