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Four enterprise projects, four different answers to the same question: how do you make high-stakes software people can trust? One uses AI that explains itself, one deliberately avoids AI, one is pure research-led simplification, one built the foundation everything else runs on.

▢ 01 · disputes-workspace · fiserv
Dispute Workspace, Fiserv

Disputes Workspace

AI-assisted dispute management for financial institutions, thousands of disputes a month, with AI that explains itself instead of replacing judgment.

call handling−25–35%
capacity+40–50%
training time−30–40%
Open case study
▢ 02 · 360-control · fiserv × desjardins

360 Control

Rebuilding an issuer admin console from the IA up, design system before screens, deliberately no AI, shipped for Desjardins on a contractual deadline.

deadlinemet, contractual
design systemdivision-wide
platformdesktop + mobile, FR/EN
Open case study
360 Control, Fiserv × Desjardins
▢ 03 · cpq · zywave
CPQ, Zywave

CPQ

Research-led redesign of Zywave's enterprise quoting platform, design system from scratch, measured against metrics defined before design started.

quote time18 → 10 min
pricing errors↓ from 28%
spreadsheetsretired
Open case study
▢ 04 · design-system · fiserv

Dispute Workspace Design System

Building the foundation first — a comprehensive design system from scratch that 45+ components and 12+ core workflows now run on, WCAG 2.1 AA from day one.

design output65% faster
development40% faster
post-launch bugs−67%
Open case study
Fiserv Dispute Workspace Design System
© 2026 Abhikant Nirbhavane 4 case studies · more in the archive on request