Conventional deliverables
UI, prototypes, research reports, and design systems
In an era when AI is woven into every experience,
companies need Agentic UX that enables AI agents to act autonomously
in order to realize AI’s full value.
From AI-native experiences and operating systems
to brands that give people a reason to choose you in the age of AI,
we deliver the force that drives business forward.
Introducing AI is not the goal.
We design experiences and systems in which AI naturally supports
human judgment and business growth.
Every solution is designed
with this single point as its north star.
How We Practice Agentic Management
As practitioners of Agentic Management,
we are advancing organization design and management built around AI.
Where should AI be used? Goodpatch’s work begins by identifying the answer. By gathering firsthand information and framing the challenge accurately, we propose the most effective way to support you.
Break down management, frontline, and customer challenges, and identify where AI can help.
Determine what to change across product, workflow, and organization.
Choose the right intervention, and bridge to the three solutions.
We propose the right solution for the area identified through diagnosis.
Across products, operations, and organizations,
we leave behind systems that enable people to keep using AI.
Client products
Product experience design
We provide broad support, from developing new AI products and implementing agentic experiences in existing services and products to building AI-driven development environments.
Client business systems and workflows
Building AI design environments
We turn the character and decision criteria that AI alone can easily lose into a repeatable design harness. By elevating judgment and knowledge that tend to remain with individuals into an environment the entire organization can reproduce, we work alongside clients through implementation in their operations.
Client organizations
Discover → Build → Embed
Our goal is to enable clients to continue AI-driven development on their own after our engagement ends, so we work alongside them with in-house ownership in mind. We support each stage, from establishing the development environment and running proofs of concept to deciding when to move into production, leaving the organization with a foundation for self-sustaining progress.
In an era when creating with AI becomes commoditized, company-specific context—what questions to ask, what to value, and how to operate—becomes the hardest competitive advantage to imitate. Goodpatch is committed to translating that context into business impact and strengthening each client’s ability to move forward independently.
Surface
Surface
UI, prototypes, research reports, and design systems
Organizational capability
Organizational Capability
Problem Framing
A system of prompts, evaluation criteria, and decision principles that helps AI address business challenges.
Taste as Infrastructure
Turning brand tone and decision criteria into explicit knowledge that AI can reproduce.
AI Native Workflow
New workflows and organizational forms with human and AI roles built in.
Coherence System
Quality guardrails plus systems for evaluating, monitoring, and updating AI output.
Business economic value
Economic Outcome
Productivity Reengineering
Do the same work in half the time, or double output with the same team.
Improve cost structure and gross margin; turn labor cost into investment capacity
New Value Creation
Customer experiences and personalization that can only be made with AI.
New revenue sources; differentiation competitors cannot follow
Core
Core
AI-native ways of thinking, deciding, and making become embedded inside the client organization.
New revenue sources; differentiation competitors cannot follow
Five phases reworked by Goodpatch for AI × Design. From exploration to adoption, we implement a loop in the business where people and AI learn from one another.
Design the agent-experience concept and north-star measures, then align stakeholders.
Prototype generative UI and agent behavior in short loops alongside human-in-the-loop evaluation.
Connect the design system and inference pipeline, building the foundation for operation and evaluation.
Embed a continuous loop that improves prompts, UI, and models using real usage data.
Identify the problem AI should solve and articulate the assumptions for a proof of concept from business context and user observation.
Implementation stories with clients placing AI at the heart of their businesses, across industries and company sizes. Explore the depth of the challenges and the tangible outcomes.
We launched Gp-AX Studio (Goodpatch AI Experience Studio) to strengthen the group's business foundation in the design × AI domain. Working as one across management, product, and research, we support clients' AI businesses from launch through operation.

Goodpatch Executive Officer
Drawing on his experience supporting numerous clients as an iOS developer and UI designer, he leads the development of AI-first design processes, advances AI capabilities across the company, and creates new solutions. He serves as an Executive Officer with primary responsibility for design.

Goodpatch Business Lead
He leads Strap, Goodpatch’s in-house AI product. He helps client companies visualize their operations and advance DX and AX (AI Transformation).

Goodpatch Product Manager
A product manager of AI products since the machine-learning era, he joined Goodpatch after working on an AI-powered smart EHR project at Alibaba Health. He develops AI products that improve productivity while driving AX across the company.

Corporate IT
Working at the core of Goodpatch’s company-wide information systems, he drives AX through initiatives such as AI tool adoption and business process improvement while strengthening the company’s IT foundation.
Talk to us about anything—UI/UX design for services and products, brand building, AI adoption, new business development, or management and business strategy.