The Singapore Fashion Council (SFC) has invested US$300,000 in Loom Carbon, a local climate tech startup, as part of its inaugural accelerator programme, The Bridge Fashion Innovator (TBFI) Scale Up.

Loom Carbon will receive tailored mentorship, enhanced investment readiness support, and access to a curated network of investors, corporate partners, and government stakeholders through the TBFI programme.

The startup will also benefit from pilot opportunities across Singapore and Southeast Asia.

Also Read: Climate tech’s shift from doing good to doing well

About 92 million tonnes of textile waste are landfilled or incinerated annually. Loom Carbon aims to solve this massive textile waste challenge using technology.

The company utilises a proprietary, science-led approach that adapts proven pyrolysis technology. Its modular pyrolysis system converts mixed discarded textiles into high-value circular materials. These resultant materials include bio black and renewable oil, which can then be utilised as low-carbon fuels or precursors for new textile production.

During conversion, Loom Carbon removes per- and polyfluoroalkyl substances (PFAS) and microplastics. The modular systems are deployable at the source and designed to scale rapidly.

Benjamin Tan, Senior Director of Innovation & Technology at SFC, said: “Textile waste is one of the fashion industry’s most persistent and overlooked challenges. Innovations like Loom Carbon are crucial for advancing real, science-based solutions that move us closer to a truly circular economy. Their impact-driven approach aligns strongly with SFC’s vision of building Asia into a vibrant hub for responsible fashion.”

To achieve its scale-up ambitions, Loom Carbon is collaborating with world-leading research and academic institutions in Singapore, the US, and South Africa. The company is targeting commissioning its first commercial plant in Singapore, which is expected to have the capacity to process more than 20,000 tonnes of textile waste annually.

Ryan Wiener, co-founder at Loom Carbon, added. “SFC is playing an important role in promoting sustainability and innovation across Southeast Asia… we align perfectly with Singapore’s Green Plan 2030, and now with the SFC on board, we are well positioned to deliver impact at home and across the region.”

Also Read: Korean brothers’ startup Nibertex develops chemical-free fabric for sustainable textiles

The TBFI Scale Up, launched in 2025, is SFC’s dedicated accelerator for growth-stage ventures in fashion, beauty, and fashion-tech, offering personalised, one-on-one mentorship rather than a conventional cohort-based programme.

Filipino startup Phinix is another player in this segment. This startup runs a recycling centre that collects textile wastes and transforms them into higher valued products such as footwear, fashion accessories and lifestyle pieces.

Recently, Nibertex, a Singapore- and Philippines-based deeptech startup specialising in waterproof breathable membranes, closed a US$7 million Series A funding round led by TNB Aura. The startup develops PFAS-free membrane solutions for the textile industry.

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Autonomous delivery vehicles are quickly becoming the future of logistics, with companies racing to harness the potential of self-driving tech to speed up deliveries, cut costs, and improve efficiency.  But these vehicles will face challenges far tougher than the smooth, controlled test environments they’ve been trained in—especially when it comes to unpredictable roads and extreme weather.

Take suburban roads. Narrow, full of potholes, sometimes not even paved. No lights, no clear markings. A human driver wouldn’t blink at rolling over a few fallen branches or debris. But for an autonomous vehicle? That may be a problem. These delivery vehicles are learning to “see” and “assess” their surroundings. Traditional object detection systems tell the vehicle what an obstacle is—but not whether it’s safe to drive over.

Leading industry players are increasingly adopting occupancy networks instead of just identifying objects. These systems collectively assess whether a vehicle can safely pass, which is critical for handling unpredictable roads, especially when visibility is low. At Cainiao, for instance, we apply these networks to manage mixed road conditions in our pilot programmes, ensuring that obstacles like fallen debris or uneven surfaces don’t derail an entire delivery schedule.

Then there’s the challenge of navigating real-world traffic laws. Following rules is easy when every sign is clear, and every traffic light works perfectly. But what happens when a truck blocks a signal? When road markings are so faded they’re barely visible? A self-driving vehicle can’t afford to hesitate.

To tackle this, many logistics innovators are turning to graph neural networks to help vehicles read not only traffic signals but also how other cars behave, analysing patterns to make an educated guess about what’s happening.

Also Read: Our voyage of innovation: Reshaping global maritime logistics

And they don’t just react in the moment; these evolving systems can use past data to stay consistent, even when the situation gets messy. In our experience, layering in additional contextual information–such as congested traffic conditions or regional driving norms–helps our vehicles maintain stable navigation under unpredictable scenarios.

And then we have the wildcard: other drivers, cyclists, pedestrians—unpredictable, constantly moving objects. A self-driving delivery vehicle needs to do more than just recognise them; it needs to understand their size, speed, and trajectory in real-time. Across the industry, companies are deploying multi-frame, multi-task, multi-modal sensor fusion approaches — combining data from various sensors to build a detailed, continuously updated model of everything moving around them.

They process large numbers of moving objects in fractions of a second, balancing near-range precision with long-range awareness to ensure safe, stable navigation in crowded environments. This level of real-time perception is what makes safe autonomous navigation possible.

The same principle applies to weather. Rain, snow, fog—bad enough for human drivers, but a serious challenge for autonomous systems. LIDAR can get blinded by fog, cameras blur in the rain, and radar struggles with fine details. No single sensor can handle everything. Accordingly, top providers integrate multi-sensor fusion to let different sensors cross-check each other, enabling fallback options if one sensor becomes compromised by adverse weather.

One emerging industry best practice: built-in LIDAR cleaning systems. If rain or snow starts blocking the sensor, the vehicle slows itself down to below 25 km/h, ensuring it stays stable and safe. These small details make all the difference in making autonomous delivery actually viable.

And what’s more important these vehicles aren’t just running on static programming. Reinforcement learning means they improve with every mile they drive. The more real-world data they collect, the better they get at making smart, split-second decisions. In many pilot programmes worldwide, companies have tested such vehicles on semi-closed roads to sharpen decision-making under real-world conditions. Over time, they can master the chaos of real roads.

Also Read: Electrifying Southeast Asia: Unleashing the radical potential of electric vehicles

As one of the developers and producers of autonomous delivery vehicles, Cainiao applies these same industry-wide concepts to real-world deployments. Recent industry deployments on open roads and sold to real-world clients, mainly courier stations and parcel pickup stations, playing a key role in major sales promotions—saving labor costs during peak seasons. This experience underscores Cainiao’s belief that no technology is perfect, and autonomous delivery vehicles still have a long way to go.

That said, with every new challenge–whether it’s unmarked suburban roads or a sudden downpour–these vehicles are getting better at handling the chaos of the real world. Ultimately, the entire logistics sector is progressing toward a future where autonomous delivery is not only feasible but optimised for various road and weather conditions.

So, the real question isn’t if autonomous delivery vehicles can be ready for all conditions — it’s when. Through collective innovation by multiple players that “when” will come sooner rather than later.

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The global trade landscape is undergoing a seismic shift. The imposition of substantial tariffs, such as the US’s 145 per cent levy on Chinese imports, has led to a significant decline in US-China trade volumes, with container shipments plunging by up to 40 per cent in April 2025.

This disruption has accelerated the diversification of supply chains, positioning Southeast Asia (SEA) as a pivotal player in global logistics.

Trade: From complexity to clarity

The acronym TRADE today feels heavy. It could easily stand for:

• Tariffs
• Retaliation
• America-first policies
• Deficits
• Export controls

This version of Trade reflects a zero-sum mindset. It’s transactional, reactive, and often exclusionary. But what if we could reframe Trade to represent a more hopeful, collaborative, and future-ready paradigm?

Let’s consider a new framing:

• Trust: Confidence in secure and fair trade
• Resilience/RCEP: Shock-proof supply chains and regional unity
• Agility: Rapid response to change and disruption
• Digitisation: Seamless, data-driven, paperless trade
• Empowerment: Using trade as a lever for economic inclusion and growth

This new interpretation underscores how the ASEAN region can lead global efforts in rebuilding the fractured scaffolding of trade—from fragmentation to federation, from defensiveness to design.

Also Read: How is the UK-US trade deal shaping cryptocurrency and stock market trends?

The six flows of supply chains, a new operating system

To effectively rethink trade, we must move beyond viewing it solely through the lens of physical goods. Today’s global supply chains are governed by six interrelated flows:

• Product/cargo flow: the traditional movement of goods.
• Data flow: critical for real-time visibility, regulatory compliance, and automation.
• Money flow: financing, payments, and risk mitigation.
• Value flow: tracking where value is created and captured across the chain.
• Risk flow: mapping geopolitical, cyber, and climate-related disruptions.
• Carbon flow: understanding the emissions footprint of each logistical leg.

Any attempt to strengthen ASEAN’s trade posture must acknowledge these six flows. Digitalisation, especially, underpins them all—without interoperable data systems, secure cross-border documentation, and smart contracts, trade slows and trust erodes.

This is where Southeast Asia must distinguish itself—not just with competitive pricing and infrastructure, but with digitally harmonised, data-driven, and climate-conscious logistics ecosystems.

Technology: The enabler of agility and resilience

In navigating this complex trade environment, technology has become the single most important enabler of supply chain agility and resilience.

Artificial Intelligence (AI), Internet of Things (IoT), blockchain, and cloud-based platforms are empowering companies to rewire their operations, increasing visibility and responsiveness across global networks. Predictive analytics allow businesses to anticipate disruptions, optimise routing, and manage inventory dynamically.

IoT enables real-time tracking of goods, enhancing control and quality assurance. Meanwhile, blockchain provides a secure and immutable digital ledger, which helps build transparency and trust across suppliers, logistics providers, and regulators.

Importantly, digital tools are not just about optimisation—they’re about resilience. They allow Southeast Asian economies to manage complex interdependencies, improve compliance, and reduce manual friction in customs, trade documentation, and multi-party coordination.

The China+1 strategy and Southeast Asia’s critical role

The China+1 strategy is no longer just a buzzword—it’s a survival tactic. In a world defined by trade unpredictability and geopolitical rivalry, multinational companies have accelerated efforts to diversify their supply chains beyond China, creating multiple production and sourcing bases to hedge against concentration risks.

Southeast Asia has risen to the top of the list. Vietnam, Thailand, Indonesia, and Malaysia offer competitive labor costs, improving infrastructure, and a growing base of skilled workers. In addition, many of these countries are part of trade-friendly frameworks like the Regional Comprehensive Economic Partnership (RCEP), offering broader market access and policy stability.

Also Read: Navigating market volatility: Bitcoin Hits US$99K, US stocks rally amid trade talks and fed decisions

Yet diversification comes with its own complexities. Take Vietnam, for example. While it has been a top beneficiary of diverted investment flows, the country is also vulnerable to tariff fallout as its own exports come under scrutiny for Chinese-origin components.

Recent studies have warned of potential GDP impacts of up to six per cent for some ASEAN economies, underscoring that supply chain relocation is not a zero-sum game—it requires deeper structural readiness.

The opportunity for Southeast Asia lies not just in being a substitute manufacturing base, but in positioning itself as a regional value-added hub, deeply integrated and digitally enabled.

ASEAN’s path forward: From buffer zone to builder zone

The solution doesn’t lie in isolation or duplication, but in regional coordination. ASEAN economies must strengthen their collective response—not just at the diplomatic level but through aligned investment in trade tech infrastructure, logistics corridors, and digital trust ecosystems.

Public-private partnerships should be encouraged, particularly in building digital ports, trusted e-commerce zones, bonded warehouses, and intelligent trade corridors. The ASEAN Smart Logistics Network, already in motion, could benefit from integrating a digital trust overlay—making goods traceable not just physically but across ownership and compliance checkpoints.

Multilateral Development Banks (MDBs) and Development Finance Institutions (DFIs) can play a catalytic role here, funding not just infrastructure but the digital public goods needed for smart, secure, and inclusive trade ecosystems.

Singapore: A trusted trade and supply chain hub

Singapore stands as a case study of how small economies can punch above their weight by combining physical logistics excellence with digital trust infrastructure. Ranked first in the World Bank’s 2023 Logistics Performance Index, Singapore leads in infrastructure, customs efficiency, and international shipments.

But it’s the integration of digital trade enablers—like AI-driven port systems, just-in-time customs clearances, and partnerships with industry on traceability platforms—that has turned Singapore from a transshipment giant into a trusted trade & supply chain hub.

Rather than merely promoting pilot solutions, Singapore scales innovation through collaborations. The Advanced Remanufacturing and Technology Centre (ARTC), for instance, accelerates industry R&D and commercialisation in supply chain solutions. At the same time, national initiatives like SBF’s COFTI (Center of Future Trade & Investment) exemplify Singapore’s push to shape the future of digitally enabled, rules-based trade.

Singapore is increasingly functioning as a “control tower”—orchestrating flows of data, money, value, risks, and carbon remotely—while physical goods may bypass Singapore entirely. This positions the country as a leading offshore and wholesale trade node, anchoring trust and governance in global trade networks.

Increasingly, regional players like Indonesia, Malaysia, and Vietnam are also looking to such digital models, adapting them to local contexts while striving to create more trustworthy and connected ecosystems.

Also Read: Book Excerpt: Why successful fundraising begins with understanding your company’s needs

TTTT: Trade, transport, technology, and trust – A new framework for the region

To thrive in today’s volatile trade environment, Southeast Asia must adopt a new paradigm—TTTT: Trade, transport, technology, and trust.

• Trade: Southeast Asia must go beyond traditional FTAs and focus on digital trade enablement. Simplifying origin rules, integrating regulatory tech (RegTech), and enabling real-time compliance checks will be critical to stay competitive.

• Transport: Multimodal logistics corridors—from dry ports in Vietnam to high-speed cross-border rail between Laos and China—need better integration. Investment in inland connectivity, last-mile digitisation, and cross-border logistics data exchange will ensure that physical goods keep flowing seamlessly.

• Technology: Smart warehousing, AI-based forecasting, and end-to-end supply chain digitisation must become the norm. Governments should facilitate SME onboarding onto digital platforms and fund sandboxing and cross-border pilots for logistics tech and supply chain visibility tools.

• Trust: This is the newest and arguably most important dimension. Whether it’s trust in origin, compliance, data integrity, or contractual execution, digital trust is the currency of modern trade.

Platforms that ensure tamper-proof documentation, trade authentication, and traceability—such as digital certificate exchanges or secure interoperability frameworks—will be essential.

While early-stage efforts like the Infocomm Media Development Authority (IMDA)’s TradeTrust have laid a foundation, the region now needs interoperable frameworks that allow for shared, verifiable, and cross-certified trade data between countries and across private sector systems.

Conclusion: From shock to strategy

The US tariffs are not just a policy shock—they are a wake-up call. Southeast Asia must now take strategic ownership of its position in the global supply chain map.

By embracing the TTTT framework—Trade, transport, technology, and trust, recognising the six flows of supply chains, and reframing Trade as a tool for inclusion and empowerment, the region can shift from a reactive to a resilient trade powerhouse.

More than just a manufacturing alternative to China, Southeast Asia can emerge as a trusted, technologically empowered, and interconnected supply chain hub—a cornerstone of tomorrow’s global trade system.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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The world’s bracing for a slowdown.

US tariffs on Chinese imports have surged to historic highs — the average rate now sits at 22.5 per cent, the highest in over a century. New levies of up to 145 per cent are hitting everything from electronics to everyday consumer goods.

The result? Panic.

US$6.6 trillion in global market value was wiped out in just two days. Bloomberg called it a “market meltdown.” The Straits Times put it bluntly: “a tariff nightmare.”

Economists now warn of a possible U.S. recession, with up to 2 million jobs at risk. Former Treasury Secretary Larry Summers estimates average household income could fall by as much as US$5,000 if escalation continues.

And yet, in the thick of all this chaos, a Singapore startup is quietly thriving.

Not because it’s chasing hype. But because it’s doing the exact opposite.

The startup that chose the road less scalable

While the rest of the tech ecosystem is busy spinning up AI agents, launching crypto loyalty tokens, or building the next vertical SaaS for pets — NNIO decided to make… fans.

Not smart fans. Not WiFi-enabled fans. Just really good ones.

Fans. Vacuum cleaners. Shower heaters. Air fryers. That’s the NNIO playbook.

It’s not the kind of business you’d expect to see in a pitch deck. But that’s precisely what makes it work.

Also Read: Bitcoin, S&P 500, Nasdaq surge amid strong manufacturing data and trade hopes

Designing for real life, not demo day

NNIO was co-founded by Beng Kwee (BK) Tan, an industry veteran with over three decades in the appliance sector. He’s seen all the waves: smart homes, IoT, app-integrated everything.

But here’s what stuck:

“Most people don’t want to download an app to turn on their fan,” BK says. “They just want something reliable, affordable, and decent looking in their home.”

That insight is at the heart of NNIO’s product philosophy: strip away the fluff, double down on what matters. No bloated feature sets. No app-for-the-sake-of-an-app integrations. Just minimal, essential functionality – built to work, and built to last.

It’s product line reflects that approach. Branded under four categories:

• Air circulators and fans (A-Cool+)
• Cordless vacuum cleaners ( V-Clean+)
• Cooking appliances (C-Tasty+)
• Shower heaters (S-Refresh+)

Also Read: Advanced safety solutions: Supporting, not replacing, human oversight in manufacturing

Designed for performance and priced for accessibility, these products have seen strong traction across Singapore, particularly among value-conscious consumers seeking practical innovation over flash.

Betting on what doesn’t break

Unlike the blitzscale-at-all-costs playbook, NNIO took a different route.

With a strong anchor, a focus on operational discipline, and smart distribution through both modern retail and e-commerce, the company stayed lean. There’s no sky-high valuation to defend, no PR hype cycle to chase.

Just real customers. Buying real products. Month after month.

Here’s the thing about home appliances: they don’t go viral. But they do get bought, especially when budgets tighten.

The global household appliance market is massive, projected to hit US$1.11 trillion by 2032. But beyond size, its resilience is what stands out. People still need to cook, clean, and stay cool — regardless of funding slowdowns or inflation.

In downturns, essentials outperform. And that’s where NNIO quietly wins.

“Boring sells — especially when the economy doesn’t.”

The moat you didn’t see coming

While hype-driven startups are burning cash to justify sky-high growth, NNIO is building something harder to replicate: a defensible niche grounded in habit and necessity.

It’s not trying to “disrupt” your home. It’s just trying to make it more liveable: affordably, reliably, and without friction.

In an era where tech is increasingly defined by noise, simplicity might just be the sharpest edge.

And in a time of economic uncertainty, that kind of boring might just be brilliant.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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Artificial Intelligence has quickly become part of our daily routines. Whether it’s asking ChatGPT for travel recommendations, using AI to polish an email, or letting GitHub Copilot suggest lines of code, we’ve reached the point where AI feels almost invisible; it’s just there, helping us get things done faster.

But here’s the catch: in all the excitement, many people are overlooking a serious issue. Is the AI we rely on actually secure?

When convenience meets risk

Let’s take a common example. A developer runs into a tricky bug and pastes part of the company’s source code into ChatGPT or Copilot for help. Within seconds, the AI proposes a neat fix. Problem solved, right?

Not so fast.

• What happens to that code once it’s pasted into an AI tool?
• Is it stored somewhere outside the company’s control?
• Could it resurface in another response for a completely different user?
• And most importantly: how do we know the “fixed” code doesn’t contain hidden security flaws?

That single copy-paste could become a doorway for data leaks or application vulnerabilities, risks that are often invisible until it’s too late.

Companies are already waking up

This isn’t just theory. Some organisations have already moved to block risky AI use. For example, Skyhigh introduced policies to stop employees from pasting sensitive information into ChatGPT. Why? Because they recognised that what feels like an innocent productivity hack could lead to intellectual property leaks, compliance violations, or even open the door to cyberattacks.

The message is clear: AI tools are powerful, but they’re not risk-free.

Also Read: Cybersecurity in the AI age: How startups can stay ahead

The security blind spot

AI is incredibly good at giving quick answers. But it doesn’t guarantee those answers are safe. In fact, AI-generated code might:

• Introduce insecure patterns that developers don’t notice.
• Reuse snippets that contain outdated or vulnerable logic.
• Skip context-specific security checks that your team would normally apply.

This is the “blind spot”: people trust AI’s speed and convenience but rarely question its security implications.

Security for AI, security with AI

So, what’s the way forward? It’s not about avoiding AI altogether. That’s unrealistic, AI is here to stay. The real answer is building guardrails:

• Set clear policies: Define what data employees can and cannot share with AI tools.
• Educate teams: Make sure developers understand the risks of pasting code into public platforms.
• Double-check AI output: Treat AI suggestions as drafts, not production-ready fixes.
• Use AI securely: When possible, adopt enterprise AI solutions that offer stronger data privacy and security controls.

Think of it like this: AI can be your co-pilot, but you still need a seatbelt and traffic rules.

Final thoughts

AI tools like ChatGPT and Copilot are transforming how we work, but they also introduce a new category of risks that organisations can’t afford to ignore. The next time you’re about to paste something into an AI tool, pause and ask:

Would I be comfortable if this information appeared outside my company?
Do I trust this code is not just functional but secure?

AI is smart, but staying secure requires us to be smarter.

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