AIDEN LIN — Enterprise AI Consulting (SPACEBOX VISUAL)

AIDEN LIN's SPACEBOX VISUAL offers the D.R.A.F.T. AI Workflow, an enterprise AI consulting and training service for architecture, interior design, and real estate teams. It transforms AI tools into sustainable business processes, significantly reducing rework and accelerating decision-making and proposal delivery.
建築・不動産,IT・テクノロジーNQ 78/100出典:PR Times

📋 Article Processing Timeline

  • 📰 Published: April 3, 2026 at 18:23
  • 🔍 Collected: April 3, 2026 at 18:57 (33 min after Published)
  • 🤖 AI Analyzed: April 4, 2026 at 04:24 (9h 27m after Collected)
## AIDEN LIN — Enterprise AI Consulting

**Turning AI into a "Process", Not Just Another Tool**
Specialized in introducing AI workflows for architecture, interior, design, and real estate teams. Using the D.R.A.F.T. AI Workflow™, we ground tools into practical processes, reducing rework and decision-making friction.

- Services: Enterprise AI Consulting & Internal Training
- Target Fields: Architecture, Interior, Design, and Real Estate Teams

## Proven Results & Client Testimonials
Focusing on real corporate feedback: executive perspectives, quantifiable results, and verifiable materials.

### 1. Flagship Case | Enterprise Process Implementation: Gemhorn (朕宏國際)
After adopting AI, meetings and SOP processes accelerated simultaneously.
- BEFORE: Meeting summaries and process formulation relied on repetitive manual compilation.
- AFTER: Collaborative creation of AI meeting minutes and SOPs led to a faster cross-departmental decision-making rhythm.
- Results: 30% reduction in meeting summary time (1-2 hr/week), repetitive tasks reduced from 3 to 1 time, and SOP formation cycle shortened from 7 days to 1 day.
- Executive Feedback (Ken, CEO): "The internal training has significantly improved processes across departments, simplifying heavy workloads; we've also integrated AI into pre-decision discussions with excellent results."

### 2. Enterprise Case | Content Production: Auris (艾立思軟裝團隊)
Content production cycle shrunk from months to days.
- BEFORE: A 2-minute video required a long production cycle with high cross-departmental communication costs.
- AFTER: AI was integrated into the workflow, improving the efficiency of script, visual, and proposal integration.
- Results: Production of a 2-minute video dropped from 2 months to 2-3 days. The process-oriented implementation finalized proposals much faster.
- Executive Feedback (Zhengyuan Lin, General Manager): "The rapid development of AI allows our team to add it into our workflow, completing proposals much more efficiently."

### 3. Enterprise Case | Proposal Delivery: Phoebe Interior Design (室內裝修團隊)
Proposal timeline compressed from 30 days to 15 days.
- BEFORE: High rework in rendering and retouching easily delayed proposal deliveries.
- AFTER: Following training, AI usage matured, moving the rendering process and delivery nodes forward.
- Results: Proposal delivery cycle halved from 30 days to 15 days. Stable processes improved rendering and retouching efficiency.
- Executive Feedback (Zhengkan Chen, Manager): "After the training, internal AI usage has achieved considerable results, greatly aiding rendering and retouching."

### 4. Enterprise Case | Management & Collaboration: Management Department
Post-implementation, both meeting times and repetitive work decreased.
- BEFORE: Offline information was scattered, and cross-departmental communication easily led to repetitive confirmations.
- AFTER: Online information combined with AI collaboration unified colleagues' common language.
- Results: Meeting times reduced by over 20%.

## FAQ

**Q: How is the D.R.A.F.T. methodology different from general AI training?**
A: General training teaches you how to use tools, while D.R.A.F.T. solves how to make AI a part of the team's process. Starting with process diagnosis to find the real bottlenecks, the final delivery is a sustainably operating workflow and knowledge base, not just a list of tools.

**Q: Our team has never used AI before. Is it suitable to implement it directly?**
A: Very suitable. Teams starting from scratch can build cleaner processes. We recommend starting with a P1 Feasibility Assessment ($30,000) to clarify the value in one meeting and get a Go/No-Go recommendation.

**Q: What AI tools are covered? What if the tools update too quickly?**
A: Common tools include ChatGPT, Midjourney, D5, Notion AI, Runway, etc. The core value lies in the process strategy rather than the tools themselves. The architecture is not bound to specific software; when tools become obsolete, we simply replace the nodes. Monthly retained clients also receive a monthly trend report.

**Q: How do you measure the effectiveness of AI implementation?**
A: During the Fine-tune phase, we establish a KPI Dashboard tracking proposal time, rework rate, content cost, and communication efficiency. Past cases have shown a 30-70% improvement in proposal efficiency and a 25-40% drop in rework rate.

**Q: What about data security and confidentiality?**
A: NDAs can be signed for all services. Enterprise data is never used for third parties. Execution only begins after signing a formal contract and paying a deposit.

**Q: Is there a limit on the number of trainees?**
A: We recommend under 30 people to ensure interaction quality. Exceeding this requires separate evaluation. It can be conducted online (Google Meet or Zoom); travel and accommodation are charged separately for locations outside Taipei.

**Q: Can we run a small-scale trial first?**
A: Absolutely. We offer a free 30-minute consultation with no sales pressure. 50% of the entry-level consultation fee can be applied toward subsequent services, allowing you to clarify the direction before deciding to deepen the engagement.

**Q: Are quotes tax-inclusive? What are the payment methods?**
A: All amounts are excluding tax. A 5% business tax will be added upon legally issuing an invoice. The starting price is a base quote; project-based engagements will be formally quoted separately based on scale.

FAQ

What is the D.R.A.F.T. methodology?

It is a unique approach that resolves business process bottlenecks and builds sustainable workflows, rather than just teaching AI tool usage.

How are the implementation results measured?

We create a KPI Dashboard tracking proposal time, rework rates, etc., aiming for a 30-70% improvement in proposal efficiency.

Can a team with no prior AI experience adopt this?

Yes. Starting from scratch allows for cleaner processes, and an initial feasibility assessment helps clarify the direction.