Decision Engine
AI · Enterprise · Design Systems
Business teams now configure decision workflows themselves, with zero engineering tickets — turning a system only engineers could touch into one anyone can run.
Transforming a complex internal decisioning ecosystem into a scalable no-code workflow platform that business teams can configure independently, without engineering support.
(Challenge)
The platform originally functioned as an engineering-heavy internal decisioning system built primarily for technical users. Business teams were highly dependent on engineers to configure workflows, which limited scalability and slowed down operations.
(Approach)
I synthesized research into role-based personas — operational analysts, low-code builders, business administrators — then restructured the information architecture around clearer domains, reusable workflows, and a marketplace layer, translating that structure into consistent UI patterns for real workflows.
(Results)
Engineering dependency
Task completion time
Configuration errors
Onboarding time
CSAT
(03)
(Deep Dive)
© 2026
The Challenge
Understanding User Roles, Workflows, and Adoption Barriers
Journey Mapping From Onboarding to Scale
Restructuring the Information Architecture
Designing a Scalable System: From Architecture to Real Workflows
Translating Structure Into UI Patterns
Designing Real Workflows With the System
Key Elements of the Design System
Applying the System in Real Scenarios
From System to Real Product Experience
Impact
