AI SpeedUp: From China to the Global Market

Last Friday, AI Speedup and SQ Collective hosted a session that brought together founders, GTM leaders and infrastructure leaders to discuss the reality of scaling globally in 2026.

• Key Speakers: David (Wavespeed AI), Jack Chen (Akool), Lusha Chen (Dify), Ivan Tang (Zilliz), and Sarah Wang (Moonshot AI/Kimi) shared insights on enterprise video, open-source ecosystems, and vector infra.

• Panel Discussion: “Where AI Globalization Actually Breaks — or Scales” featured a candid discussion with Derek Wang (Google Cloud), Andy Lee (Alibaba Cloud), Yang Kan (BytePlus), and Yuze (NVIDIA), moderated by Wei Wu (Unique Research).

We all know 2026 will accelerate. Not just in the sense of "another model release," but the next wave crashing on you before you've even adapted to one wave.

At this AI Speedup Launch session, speakers from Chinese applications, platforms, and infrastructure made one thing crystal clear:

• AI generation (images/videos/code) is transitioning from "toys" to "production tools."

• Going global is no longer about "translating (Chinese) products into English."

• The moat for startups isn't some toolchain, it's whether you can consistently deliver value and trust.

This blog distills the entire session into a 6 takeaways for "building AI products for the global market."

1) 2026 is when AI transitions from "Showcase" to "Production"

The earliest signals actually come from the most pragmatic metrics: money, efficiency, and ROI.

In e-commerce, AI-generated assets significantly boost conversion rates.

In web series/content production, script, storyboard, and asset generation are becoming standard workflows.

In advertising, generative content drastically reduces production costs.

In short: Generative AI is no longer just "more fun”, it's also become "more cost-effective."

This will trigger a chain reaction. Businesses no longer just ask "Can it be done?" They’ll start asking:

• "Can you deliver consistently?"

• "How is data security guaranteed?"

• "Can it integrate with my existing systems?"

2) Stop building "big, comprehensive platforms": Going global requires "vertical depth + partnership"

Speakers noted that Chinese entrepreneurs often gravitate toward building "big platforms" that aim to cover everything. This is a habit that developed from the market characteristics of China.

But overseas, what many of the speakers have realized is, particularly for the enterprise market, this is often a more difficult path.

A more realistic approach is:

• Go deep. Target a specific scenario and optimize results to production-ready standards.

• Build and rely on a partnership model. Don't try to do everything yourself. At Akool, here’s how they leveraged partnerships:

  • RTC: Find partners.

  • Find industry experts for knowledge bases.

  • Use the optimal combination of third party models, vector libraries, and workflows.

You're not "building the universe." You're building a solution that can be procured, deployed, and operated.

3) "Collaboration" isn't just a slogan: The real leverage for global expansion is channels and local partners.

One phrase kept surfacing throughout this event: Act Local.

But "localization" isn't just swapping UI languages or advertising in subway stations. It's about building trust with the local buyers.

What matters most is:

• Do you have local distribution channels?

• Do you have local delivery partners (SIs, MSPs)?

• Do you have "on-site support" that instills customer confidence?

Many enterprise customers aren't lacking tools.

What they lack is: someone who can piece the fragments together and take responsibility when things go wrong.

So here's a hard-hitting piece of advice for going global:

• Go global together. Collaborate with outstanding peers to build solutions, share customers, and leverage channels.

• Find local partners. Make "localization" scalable.

4) Overseas markets don't value "price wars". They prioritize stability, security, and long-term value

There's a quote I love, and its logic is brutally honest:

Customers may pay for a 10% savings, but they won't take on uncontrollable risks for half the price.

Within China, markets are won through speed, and price wars are common. Overseas enterprises however, approach procurement with a different mindset:

• Prioritize stability.

• Data security comes first.

• Long-term value comes first.

  
  

If you start by touting "ultra-low prices" as your selling point in global markets, it often sends a different message than from in China:

• You're uncertain.

• You're unstable.

• You may not last long.

  
  

The strategy for global expansion is: price based on value, close deals through trust.

5) "There is no single best model"

Another crucial consensus is the pattern of prioritizing "switch-ability, combinability, and customizability."

• Customers will use different models: Claude, ChatGPT, Gemini, as well as Chinese models.

• Each model differs in accuracy, cost, and recognition capabilities.

• What truly determines effectiveness is often not the model name, but: data quality + RAG quality + workflow design.

Therefore, the most powerful product form will resemble:

• Model interchangeability.

• Data sources can be integrated (Teams / SharePoint / Feishu / DingTalk / WeChat / Line…).

• Visualizable, iteratible workflows.

• Permissions, auditing, and isolation (multi-tenant) are standard features.

In short: Customers want a "customized end-to-end solution," not just your model.

6) Infrastructure remains crucial: Vector databases are more than just RAG

Presentations from the vector database ecosystem also clarified a common misconception: Many assume vector databases are solely for RAG. But in real production use cases, they're also deployed for:

• Recommendations

• Multimodal retrieval (images/videos)

• Similarity search

• Security detection (malicious APKs / code signatures)

• Large-scale semantic search (multi-tenant, enterprise-grade permissions)

When you begin serving more serious clients, the value of your infrastructure becomes more apparent:

• Scalability

• Stability

• Cost

• Operations and SLAs

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Three Timeless Reminders for Entrepreneurs

Models change, paradigms shift. But I believe three things remain constant:

1. Return to business fundamentals: users, pain points, value.

   • Whose problem are you solving?

   • Why do they need to buy it now?

2. Speed: Faster than fast.

   • Every model iteration must have its own test set.

   • Rapid validation, rapid release, rapid refinement.

3. Execution: Catch the wave.

   • Not every wave can be caught.

   • But you must keep paddling.