人工智能方案目錄

dthinkr.ai is an AI-powered innovation platform designed to support departments in delivering more effective, user-centric solutions. By embedding the principles of design thinking into an accessible and scalable digital system, dthinkr.ai enables teams to streamline complex problem-solving processes, reduce manual workload, and accelerate service innovation.

The platform empowers professionals to efficiently ideate, prototype, and test policies, services, and initiatives—without requiring extensive design thinking expertise or external consultancy resources. This not only improves operational efficiency but also enhances cross-department collaboration and data-driven decision-making.

By bridging the gap between strategic intent and practical implementation, dthinkr.ai helps organizations respond more effectively to evolving customer needs, improve service delivery, and foster a culture of continuous innovation.

Use Case: Enhancing Service Innovation in Hong Kong

Example 1:

The department regularly faces challenges in improving estate management, tenant engagement, and community satisfaction. Traditionally, identifying and testing new service improvements requires lengthy consultation cycles, manual workshops, and external consultancy support.

Using dthinkr.ai, the teams can digitally run structured design thinking processes to: Gather and synthesize tenant feedback using AI-assisted insights Rapidly generate and evaluate service improvement ideas (e.g., smart estate services, waste reduction programs) Prototype and simulate policy or service changes before pilot implementation This allows frontline staff and administrators to co-create solutions more efficiently without requiring deep expertise in design thinking.

Cost vs Benefit

Costs: Subscription or licensing cost for dthinkr.ai (significantly lower than hiring external consultants) Minimal onboarding and training time due to guided AI workflows

Benefits: Reduction in consultancy spending for innovation projects Faster turnaround time for service improvements (weeks instead of months) Improved tenant satisfaction through more responsive and tested solutions Institutionalization of innovation capability within the department

Example 2:

The office focuses on improving service delivery across departments but often relies on fragmented processes and manual facilitation of workshops.

With dthinkr.ai, the office can: Standardize innovation frameworks across departments using a unified platform Enable staff to run guided innovation sprints independently Scale design thinking practices across multiple policy areas simultaneously Track and evaluate innovation outcomes using centralized data insights

Cost vs Benefit

Costs: Platform integration and deployment across departments Initial change management and internal adoption effort

Benefits: Scalable innovation capability across the entire government ecosystem Reduced duplication of effort between departments Data-driven policy experimentation and validation Long-term cost savings by reducing inefficiencies and failed initiatives

Overall Impact on Service Sector By adopting dthinkr.ai, departments can shift from slow, resource-intensive innovation processes to a more agile, data-driven, and citizen-focused model. The platform lowers the barrier to applying design thinking, enabling staff at all levels to contribute to meaningful service improvements while optimizing operational spending.