Vietnam-based Farmnet, the trading arm of agricultural supply chain company TechCoop, has secured a US$11.75 million senior secured loan from Geneva-headquartered impact investor Symbiotics, in a deal that says as much about the country’s funding climate as it does about agritech.

While it is a financing announcement on paper, it is a sign that some startups in Vietnam are no longer waiting for venture capital to loosen up.

TechCoop claimed that the facility is the first offshore institutional loan raised by one of its Vietnam-incorporated entities.

Farmnet will use the money as working capital to support higher trading volumes with processors, co-operatives and small and medium-sized agricultural enterprises across the country.

Also Read: Techcoop CEO on scaling agritech, sustainable farming, and global expansion

That makes sense because Farmnet is not a software startup chasing growth with a burn-heavy model. It sits in the plumbing of Vietnam’s farm economy: buying, moving, and selling agricultural commodities across a fragmented supply chain that often struggles to access reliable financing.

In simple terms, Farmnet helps connect the people growing and processing farm produce with the buyers who need it, while helping finance the movement of those goods along the way. It trades products including cassava, coconut, cashew, durian, coffee, fresh fruit, and processed goods and says it operates in 20 locations nationwide, serving more than 641 co-operatives and agricultural enterprises.

There is nothing flashy about that business. That is precisely the point.

Why a loan, not another venture round?

For a company like Farmnet, debt can make more sense than equity.
Commodity trading is a working-capital business. Companies need cash upfront to buy produce, pay suppliers, manage inventory, and settle transactions before revenue comes back in. That is very different from the typical venture-backed pitch built around user growth, product development and long-term optionality.

A loan fits that operating model more neatly. It gives Farmnet capital for buying and moving goods without forcing TechCoop to dilute shareholders before it needs to. The company has already said the financing is part of a broader capital strategy that includes a planned Series B equity raise later this year, suggesting the debt is not replacing venture funding entirely but complementing it.

The choice also reflects the harsh reality of fundraising in Vietnam. Raising venture capital has become more difficult for many startups, especially outside consumer internet and pure software plays. Investors remain active, but they are more selective, more valuation-sensitive and far less willing to fund growth at any cost than they were during the peak years of 2021 and early 2022. That has pushed founders towards structures that are more disciplined and more closely tied to cash flow.

So, yes, the tougher VC market is part of the story. But it is not the whole story. Farmnet’s debt raise also appears to be a rational financing decision for a business whose growth depends on trade flows, not just product milestones.

Why Symbiotics and TechCoop fit together

The loan also highlights a straightforward commercial alignment between lender and borrower.

Symbiotics specialises in impact investing, with a long history of backing financial inclusion and businesses that serve underserved parts of the real economy. Vietnam’s agricultural supply chain aligns well with that mandate. Agriculture and fisheries accounted for 11.86 per cent of Vietnam’s GDP in 2025, according to the National Statistics Office, yet large parts of the sector remain underfinanced and structurally fragmented.

Around 70 per cent of farms in Vietnam operate on plots smaller than 0.5 hectares, which makes aggregation, logistics and financing more difficult. In that environment, a trader with distribution reach and established relationships can become a key market enabler.

Also Read: Techcoop secures US$70M in one of Vietnam’s largest agritech funding rounds

That is where the synergy sits.

For Symbiotics, the deal offers exposure to a business tied to real-economy activity, rural livelihoods, and supply chain efficiency — all areas that align with impact objectives, while still being anchored in a revenue-generating trading model.

For TechCoop, the benefits are equally clear. It gains access to offshore institutional capital, adds balance sheet strength, and receives external validation from a specialised lender. That should help it finance larger trading volumes and deepen relationships with processors, co-operatives and agricultural SMEs that need dependable counterparties.

In other words, Symbiotics gets measurable impact with commercial structure. TechCoop gets capital that matches how its business actually works. Everyone avoids pretending a commodities platform is just another venture-backed app.

What Farmnet plans to do with the money

The immediate use of proceeds is working capital, but that should not be read as routine housekeeping.

For Farmnet, working capital is what allows the engine to run faster. The company said the money will support increased trading activity across its network of processors, co-operatives and small and medium-sized agricultural enterprises. In practical terms, that means greater capacity to purchase commodities, manage transaction cycles, and serve counterparties that may not have strong access to financing.

That could be especially important in sectors where timing matters. Agricultural trade is full of cash-flow mismatches: growers and processors need payment certainty, while buyers often operate on different terms. A better-capitalised intermediary can reduce friction in that chain.

The facility should also strengthen TechCoop’s platform ahead of a broader regional push. The company has said parent firm TechCoop Investment & Technology, headquartered in Singapore, plans to expand into Cambodia, Laos and Thailand in 2026.

How common are loans and venture debt in Vietnam?

Not very, at least not yet.

Debt financing and venture debt remain relatively niche among Vietnamese startups compared with traditional equity rounds. Most early-stage founders still rely on angel money, seed funds, venture capital or, where possible, bank lending. The trouble is that banks often want collateral, profitability or longer operating histories, which many startups do not have. Venture debt providers, meanwhile, are fewer in number and tend to focus on businesses with stronger revenue visibility.

That leaves a financing gap.

For startups with real cash flow, repeat customers and tangible operating cycles, debt is becoming more attractive. It is particularly relevant in sectors such as fintech, B2B commerce, agritech and supply chain infrastructure, where capital is often needed to finance transactions rather than speculative customer acquisition.

But it would be a stretch to call venture debt mainstream in Vietnam today. The market is still developing, and founders remain more familiar with equity than structured credit. Farmnet’s transaction stands out partly because such deals are still uncommon, especially from offshore institutional lenders.

How much capital has TechCoop raised so far?

Based on the information publicly disclosed in this announcement, US$11.75 million is the latest and most clearly stated financing amount tied to TechCoop through Farmnet, and it marks the first offshore institutional borrowing by a Vietnam-incorporated TechCoop entity.

TechCoop has also said it is preparing a Series B equity round later this year. However, the company has not detailed in the source material the full amount of capital it has raised to date or the exact number of previous rounds. What is visible is a business now combining debt and equity as part of a more layered capital strategy.

That is notable in itself. Startups tend to signal maturity when they stop treating financing as a one-lane road.

Vietnam’s startup market is still cautious

Farmnet’s raise lands at a time when Vietnam’s broader startup investment market remains under pressure.

The country is still one of Southeast Asia’s more promising digital economies, but capital deployment has been slower, dealmaking more selective and late-stage funding harder to secure than during the boom period. Investors are spending more time on unit economics, governance and margins. Large cheques are rarer. Bridge rounds, structured financing and alternative capital have become more relevant.

Also Read: A new era of impact: Beyond the bottom line in Southeast Asia’s tech revolution

That does not mean Vietnam is out of favour. It means the bar is higher.
Against that backdrop, Farmnet’s loan looks less like an exception and more like a preview. Startups tied to essential sectors, with visible revenue and financing needs linked to actual transactions, may find lenders increasingly receptive — especially when the business supports supply chains that are critical to the wider economy.

For TechCoop, the message is simple: if equity is expensive and banks are not built for startup realities, debt from the right institutional partner can be the fastest way to keep goods moving.

And in Vietnam’s agricultural economy, moving goods is still where the real money gets made.

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For more than a decade, the landscape of student devices has been dominated by two categories: Chromebooks and tablets. Both are affordable, easy to manage, and good enough for the standard classroom toolkit — note-taking, online research, and structured learning platforms. They solved the budget problem. What they couldn’t quite solve was the capability ceiling.

A new entrant may quietly shift that balance.

The MacBook Neo, with a starting price around $599 and roughly $499 with student pricing, brings something historically absent at this price point: a full laptop running a desktop operating system within the cost range typically occupied by Chromebooks and entry-level Windows devices.

That doesn’t automatically make it the right device for every student. But it introduces a genuinely new option in the education technology conversation — and the implications for how we think about student computers are worth examining.

Four philosophies of student computing

To understand what the Neo offers, it helps to understand what each major device category was actually designed to do.

Rather than asking which device is “best,” the more useful question is: which design philosophy fits the student in front of you

Chromebook: The web-first model

Chromebooks became popular in education because they solve several practical problems simultaneously. They are inexpensive, lightweight, easy to manage at scale, and tightly integrated with the cloud productivity tools that now define most classroom workflows — essays in Google Docs, assignments on learning platforms, collaboration through shared documents.

For this kind of work, Chromebooks are perfectly adequate.

The trade-off emerges at the edges. More advanced computing tasks — running development environments, compiling programs, experimenting with system-level tools — are more constrained in ChromeOS than on traditional desktop systems. For most students, this may never matter. But for those who grow curious about how software actually works, the ceiling eventually becomes visible.

iPad: The touch-first learning model

Tablets take a different angle entirely. Rather than prioritising keyboards and file systems, they emphasise touch interaction, digital handwriting, and creative applications.

For many subjects, this is genuinely powerful. Students can annotate documents, sketch diagrams, record voice notes, and interact with educational apps in ways that feel immediate and natural. The iPad ecosystem excels at note-taking, drawing, and multimedia creation in ways that no laptop quite replicates.

The constraint, again, is at the boundary. Tablets are built around mobile operating systems. When students need to move beyond app-centric workflows — learning to program, running technical tools, working within a traditional file system — the environment can feel more limited than the task demands.

Also Read: Why AI literacy is the new core skill for 21st-century educators

Surface Go: The portable Windows PC

Microsoft’s Surface Go occupies an interesting middle ground. It offers a full Windows environment in a highly portable device, typically paired with a detachable keyboard.

This means students can run the same software ecosystem common to many professional and academic settings, including Microsoft Office, development environments, and specialised research tools. The Surface line makes an important argument: some students benefit meaningfully from access to a full operating system rather than a purely app-based environment.

The honest trade-off is hardware performance. At this price tier, the Surface Go’s specifications are modest, and battery life and processing speed can vary. But the philosophy it represents — full OS, real portability — is a sound one.

MacBook Neo: Full desktop computing at a lower price

The MacBook Neo is interesting because it does something that previously required a substantially larger budget.

For years, macOS laptops were positioned firmly as premium devices. Students who wanted access to the macOS ecosystem needed a MacBook Air or Pro — both significantly more expensive than entry-level education hardware. The Neo changes this equation.

At roughly $499 with student pricing, it places a macOS laptop in a price band historically occupied by Chromebooks and basic Windows machines. That matters because macOS is not just another operating system — it provides a full desktop computing environment with a Unix-based terminal, native development tools, and broad compatibility with professional applications across software engineering, data science, and design.

A student curious about programming, data analysis, or systems work can experiment with the same environment used widely across industry and academia, without a premium-device budget.

The Neo achieves this price point through deliberate compromises. The base configuration includes 8GB of memory, and connectivity options are more limited than those of higher-end models. For typical student workloads, neither limitation is likely to bite. But they are real and worth acknowledging before purchase.

The chip inside the Neo also deserves a moment’s attention. Rather than the M-series silicon found in the MacBook Air and Pro, the Neo runs on Apple’s A18 — the same chip family that powers the iPhone. This is not a downgrade so much as a deliberate economic move. Apple is leveraging iPhone-scale manufacturing to bring down the cost floor of laptop computing: a classic disruption from below, using existing platform economics to enter a new market tier. The A18 is not a weakened M-chip; it is a different optimisation entirely. Its 16-core Neural Engine — capable of on-device AI inference — is arguably over-specified for today’s classroom workflows. But not for tomorrow’s. As AI tools become embedded in how students research, write, and code, having capable edge inference in the palm of a student’s hand will stop looking like overkill.

Also Read: AI integration field notes for tech startups and scale-ups: Software engineering, product, and beyond

Side-by-side comparison

Each device prioritises a different dimension of the learning experience. The table doesn’t declare a winner — it maps the trade-off space.

One cost the table doesn’t capture: the external mouse. Apple’s trackpad ecosystem is also unusually strong. Because hardware, firmware, and operating systems are designed together, MacBook trackpads tend to behave consistently across models. In practice, many users find they no longer need to carry an external mouse — something that is less consistently true across the fragmented Windows laptop ecosystem.

The creator-consumer spectrum

One productive way to think about these devices is along a spectrum.

At one end are devices optimised for consuming and interacting with content: reading, writing, watching, and participating in structured lessons. Tablets and web-first laptops excel here, and for the majority of student workflows today, this is precisely what is needed.

At the other end are devices designed to make it easier to create, experiment, and explore computing more deeply — writing code, analysing data, running development tools, and understanding how operating systems behave. These tasks require a full computing environment.

The MacBook Neo becomes significant because it lowers the cost of entry into the second category. It doesn’t eliminate the trade-offs, but it moves the price barrier.

Longevity and capability

There is a subtler consideration that device comparisons rarely surface: students keep their primary device for several years, and the demands on that device tend to grow.

There is also something worth naming that spec sheets never say. As a parent of school-going children, I find myself asking a different question entirely: what kind of relationship with computing am I putting in my child’s hands?

A Chromebook is an excellent device for a child who uses the web. A MacBook Neo, with its Unix terminal and native development tools, is a different kind of invitation — for the child who wonders how the web works. That is not a hierarchy of worth; many students will not need or want to peer under the hood. But for the ones who might, the device either opens a door or quietly closes it. A terminal matters. A file system you can navigate and modify matters. The ability to run a local server, experiment with Python, or compile something matters — not because every student will do those things, but because the ones who will should not be penalised by the hardware they happened to start on.

Also Read: Malaysian SMEs grapple with a growing “confidence gap” in AI adoption

A system that handles Year 1 comfortably may feel genuinely constrained by Year 3, when coursework involves Python for data analysis, statistical tools, machine learning libraries, or small software projects. A more flexible computing environment doesn’t just serve current tasks — it preserves optionality as interests and requirements evolve.

Not a replacement , a new option

No single device category will dominate all educational contexts, nor should it.

Chromebooks remain excellent for web-centric learning environments. Tablets continue to shine wherever handwriting, sketching, and multimedia creation are central. Portable Windows machines offer compatibility with a wide range of existing software. Each philosophy addresses a real set of student needs.

What the MacBook Neo introduces is a fourth option that previously didn’t exist at this price: the combination of laptop simplicity and full desktop OS capability, accessible without a premium-device budget.

A subtle shift

The most interesting thing about the MacBook Neo may not be its specifications. It is the fact that a desktop-class laptop has entered a price range historically defined by lightweight web devices.

Whether this translates into widespread adoption in schools remains to be seen. Institutional purchasing decisions are slow, and the Chromebook ecosystem has deep roots.

But the Neo quietly unsettles an assumption that has shaped education computing for a decade: that affordability and capability must be traded against each other. For the student who is not just learning with a computer, but learning about computers , that unsettling may matter more than any benchmark.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.

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After years of expansion and strong funding, Southeast Asia’s startup environment has shifted. Capital is tighter, investor scrutiny is higher, and startups face increasing pressure to demonstrate value and sustainable growth.

The region remains one of the world’s most dynamic innovation markets. Companies across AI, fintech, SaaS and climate technology continue to launch and scale.

In the early stages, a company’s story is often simple. Founders focus on solving a specific problem for a defined market. But as startups scale — expanding across products, markets, funding stages — clarity can fade. Over time, the company become harder to understand.

In a crowded ecosystem, with thousands of companies competing for the attention of investors, partners and customers, narrative clarity becomes a strategic advantage.

Growth multiplies complexity

As startups expand, organisational and communication complexity often grows faster than leadership teams anticipate. Products launch, markets expand, teams scale and investor expectations evolve. Over time, messaging can fragment:

• One narrative is used for investors, another for customers
• Sales teams describe the value proposition differently across markets
• Product updates shift how the company is perceived
• Website content falls behind the actual business
• Marketing campaigns emphasise different messages each quarter

None of this is intentional. It’s a natural by-product of growth.

But when positioning becomes inconsistent, the result is friction — internally and externally.

Internally, unclear positioning slows decision-making and dilutes marketing effectiveness. Externally, customers, partners and investors may struggle to understand what the company represents.

Also Read: Avoiding costly mistakes: How cognitive biases can affect entrepreneurs

What differentiates firms is how clearly they communicate their value across corporate, technology, product and customer levels.

Southeast Asia’s most successful technology companies demonstrate this clearly. Companies such as Grab, Sea Group and Gojek built powerful narratives around financial inclusion, digital commerce and the transformation of everyday services. Their positioning helped shape how markets, investors and consumers understood their role in the region’s digital economy.

Narrative clarity is more than a tagline

Narrative clarity is often misunderstood as branding or messaging. In reality, it sits deeper within a company’s strategy.

It is the disciplined articulation of how a company defines itself in the market — the clear, consistent explanation of the problem it exists to solve, the unique approach it brings, and why it matters.

At its core, narrative clarity answers three fundamental questions:

• What important problem exists, and why is it becoming urgent now?
• How does our company uniquely solve it?
• Why are we the right company to lead this shift?

When these questions are answered clearly and repeated consistently, the company’s story becomes easier for investors, customers, partners and employees to understand — and easier for the market to remember.

It shapes investor narratives, website content, marketing campaigns, sales materials and conversations, media commentary and executive thought leadership.

Instead of each team creating its own version, the organisation operates from a shared narrative. Clarity creates coherence. Coherence builds recognition. Recognition builds trust.

Also Read: Value creation: The compression principle — How to edit your pitch down to its atomic core

Why narrative clarity accelerates growth

When positioning is clear and consistent, its impact compounds across teams, channels and markets.

• First, it aligns internal teams. Marketing, sales, product and leadership operate from the same narrative framework, allowing campaigns and resources to reinforce a consistent message.
• Second, it strengthens market recognition. Buyers and partners encounter brands through multiple touchpoints — media coverage, LinkedIn, industry events and analyst commentary. When each interaction reinforces the same narrative, recognition builds. And recognition builds trust.
• Third, it strengthens PR and thought leadership. Journalists and industry stakeholders gravitate toward companies with a clear point of view. When a company consistently speaks about a specific challenge or industry shift, it becomes associated with that conversation.
• Finally, it supports regional expansion. Southeast Asia is not a single market. Regulatory environments, buyer maturity and competitive dynamics vary across Singapore, Indonesia, Vietnam, Thailand and the Philippines. A strong narrative core allows companies to adapt locally without losing strategic coherence.

Why narrative clarity matters now

Southeast Asia’s startup ecosystem is challenging. Investors are evaluating companies more carefully in a tighter funding environment. Customers are comparing vendors across borders. Talent is increasingly drawn to organisations with clearly defined missions and direction.

Startups that establish narrative clarity early gain an advantage. They build investor confidence, shape industry conversations, attract strategic partners, and stand out in crowded markets.

As the region’s innovation economy grows, the companies that scale most successfully will not simply be those with strong technology.

They will be the ones the market understands — and remembers.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

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Asia is witnessing a proliferation of some of the world’s fastest-growing digital economies. On the continent, internet usage is rising. According to data from the International Telecommunication Union, referenced by Our World in Data, in East and Southeast Asia, more than half of the population in many countries have gone online in the last three months. Such a high rate of connectivity presents startups with untapped growth opportunities. 

The downside to fast growth is that many startups face unnecessary pitfalls in their bid to capitalise on available digital opportunities. Having created multi-million-dollar campaigns for both Asian and international startups and organisations, I have identified a number of common pitfalls that many startups face in their bid to grow digitally. Avoiding these pitfalls can help your company grow faster and succeed instead of failing.

Overlooking local context and culture

The assumption that Asia represents one market is a common mistake. Asia is a patchwork of hundreds of languages, belief systems, and cultural practices. Marketing copy that is merely translated from a Western model is likely to get things wrong. It can fail to include local words and phrases and can be oblivious to cultural nuances.

For example, what represents prosperity in China represents mourning in another country. What makes a startup laugh in Singapore might fail to do the same in Vietnam. Startups should strive for copy that resonates locally and culturally. When thinking about regional marketing campaigns, startups should segment by country and language rather than assuming a single message will work for the entire region. Localisation is not only good for engagement but also for showing cultural respect.

Neglecting mobile‑first experience

In most Asian countries, internet usage occurs mainly through smartphones. In emerging markets like Asia, the percentage of desktop internet users is relatively lower compared to smartphone users. A website or application that is not optimised for different screen sizes or internet speeds will not provide a good user experience.

A website that does not load quickly or has fonts that cannot be read, or a checkout procedure that is complex, will have high bounce rates. A responsive website or a progressive web application will help a website work on different devices and internet speeds. 

Also Read: QR payments are shaping Asia’s crypto adoption curve

In addition to that, a website must also consider different payment options for different countries. For instance, in Indonesia, users prefer bank transfers or mobile wallet payments over credit card payments. In China, QR code payments are the most popular mode of payment. If a website does not allow these modes of payment, then conversion rates will be affected.

Focusing solely on paid advertising

While paid digital advertising can provide instant traffic and initial traction for a startup, relying solely on this method can be a gamble. The costs of bidding fluctuate over time. Startups can end up spending a fortune on poorly targeted advertising without a strong foundation in place. 

Startups should create their own channels, such as blogs and communities. They should also invest in search engine optimisation (SEO) from the very start. Content creation can help a startup reduce its dependence on paid advertising. It can help create compounding returns over time. Pairing paid advertising strategies with a strong content strategy can help ensure that all clicks have a relevant landing page and that users have a reason to come back.

Ignoring data and analytics

The beauty of digital marketing is that it is measurable. The sad thing is that many startups are either overwhelmed by data or choose to ignore it entirely. The metrics that many marketers focus on are not particularly helpful for driving any kind of revenue-generating activities. A key performance indicator (KPI) is something that needs to be identified for each business, such as cost per acquisition or customer retention rates. 

Tools like Google Analytics, customer data platforms, or even marketing automation tools can bring all the data together from ad sources, websites, etc. The key to data is not collecting it but analysing it. Without a data-driven marketing approach, it is all guesswork.

Underestimating content quality

The audience has an endless number of options for information and entertainment. The mediocre content will simply sink in the sea of noise. Startups may resort to posting generic blog posts or social media updates as a way to fill the gaps on the content calendar without offering any value. 

Also Read: From idea to impact: Startups redefining what’s possible in Southeast Asia

Content that is of high quality will educate, entertain, and inform. For B2B audiences, case studies, how-to articles, research-based articles, podcasts, and webinars will be effective. For consumer markets, storytelling, influencer collaborations, and videos will work. Thought leadership articles that prove your expertise and address the pain points of the audience should be the core of your strategy. In a crowded space, quality will always trump quantity.

Treating public relations as an afterthought

The traditional practice of public relations (PR) has evolved from traditional press releases to digital media. Search engines prefer those brands that have acquired decent links and mentions from authentic sources. Good digital PR combines the art of telling stories with acquiring links and reaching out to influencers. Asian startups often prefer hiring PR firms for emergencies or product launches. 

This creates a missed opportunity for them to establish a steady relationship with the media. A startup must include a digital PR strategy in its product development roadmap. They must share stories that interest people, share data-driven insights, and establish a connection with media influencers in their industry. A great brand image helps them attract investors or hire new talent.

Failing to respect data privacy and compliance

The regulations in Asia have become more and more stringent. The Personal Information Protection Law in China, the Data Privacy Act in the Philippines, and the Personal Data Protection Act in Singapore require a high level of diligence in collecting, storing, and processing personal data. Startups that do not pay heed to these regulations face severe financial penalties. 

Also Read: Why startups fail at offshore expansion (and how to fix it)

The management of consent should be an integral part of all digital touchpoints. The privacy policies should be transparent and easily accessible. While using third-party tools, the data should be secure and should comply with regulations while being transferred. Privacy should be treated as a differentiator for your business. Customers are more likely to engage with a brand that respects their data.

Overlooking social commerce and messaging apps

Asia has a unique character when it comes to social media. For instance, Line dominates Thailand, KakaoTalk dominates South Korea, and WeChat dominates China. These services include not just messaging, but also payment systems and e-commerce. A startup that limits its marketing efforts to these global services like Facebook or X may be missing a sizeable part of its audience.

One might consider reaching out to these unique services for a campaign opportunity. There are also social listening services that can help a startup identify new trends. Customer support services integrated into these messaging services can also be beneficial.

Lacking a crisis response plan

The digital world amplifies both the plaudits and the crap that gets heaped at you. One mistake in a product, an ad, or a security lapse can spark a viral attack. There are many startups that aren’t ready for this and end up being defensive and all over the place. Having a plan in place for crisis communications is a must.

Also Read: How tech startups can transform the supply chain in Southeast Asia

Identify potential scenarios for crises and draft holding statements. Monitor social conversations to identify potential issues. When a crisis strikes, own up to the mistake, talk about what you’re doing about it, and use the channels your customers use. Transparency can turn a potential crisis into an opportunity to show that you’re a company of integrity.

Conclusion: Building sustainable growth

“Digital marketing is not a magic pill that will get you instant fame,” but it is a good way to give your startup a big boost. The blunders that are being highlighted in this case, such as not considering local markets, not considering mobile marketing, relying on paid advertising, not considering data, underestimating content marketing and PR, not considering compliance, not considering social commerce, and not being prepared for crises, are all avoidable blunders that can be easily avoided.

“More people are coming online, but startups that win will be those that can create strong connections with their audiences, respect their users’ privacy, tell compelling stories, and be agile in response to changes.”

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The post Digital growth in Asia: How startups can avoid costly pitfalls and win big appeared first on e27.

SBOM has become one of those ideas that sounds obvious in a board presentation and messy the moment it reaches a real plant. In theory, it is simple. Ask every supplier what sits inside the software you run. In practice, OT estates are made up of PLCs with opaque firmware, SCADA stacks that have grown over the years, historians with connectors and plug-ins from different eras, and vendor appliances that were bought for uptime rather than transparency. The modern OT now looks much closer to IT than it once did, yet it still carries unique performance, reliability, safety, and change control constraints. That is why SBOM in OT is possible, but it has to be framed as an operational risk tool, not as a purity exercise.

The stronger question for the energy sector is not whether every OT product can produce a perfect SBOM tomorrow morning. The stronger question is whether operators can get enough component visibility to make faster decisions on patching, isolation, procurement, and incident response before they are forced into blind trust. That is also where policy is heading.

It is becoming common for manufacturers of products with digital elements to identify and document components, including by drawing up an SBOM in a commonly used, machine-readable format covering at least the top-level dependencies, and to provide it to market surveillance authorities where needed for compliance checks. At the same time, explicit focus is put on refining data fields, automation support, and operational practices so that SBOMs are scalable and interoperable rather than theoretical.

Why OT makes SBOM harder

The software world often assumes continuous deployment, short release cycles, and an environment where change is routine. OT does not work like that. Change management is paramount in OT, that software changes must be thoroughly tested and rolled out carefully, that outages may need to be scheduled days or weeks in advance, and that many OT environments still rely on older operating systems and firmware that may no longer be supported by the vendor. That changes the value of SBOM. In enterprise IT, it can be a speed tool. In OT, it is first a decision confidence tool.

Also Read: How to navigate the investment opportunity in climate tech sector

This is why many operators still hesitate. They hear SBOM and imagine a flood of component data that creates work without reducing plant risk. That fear is reasonable if the programme is designed badly. A raw component list that is disconnected from asset criticality, patch windows, vendor support, and engineering ownership is not a control. It is an admin. The answer is not to reject SBOM. The answer is to define what useful visibility looks like in an industrial setting.

What SBOM should really mean

For PLCs, the industry needs to be honest. Most operators are not going to get perfect software transparency for every controller any time soon. But that does not mean nothing can be done. A practical PLC SBOM starts with the firmware image, the communications stack, the engineering workstation software used to configure the controller, and any embedded third-party components that materially affect exposure or patching decisions. In OT terms, that is already meaningful progress because it ties software transparency to the assets that can change physical behaviour. The software and firmware inventory, version numbers, vendor details, and SBOM information belong inside an accurate asset inventory and risk management practice.

Historians and SCADA systems are where SBOM adoption should move faster. These platforms are usually closer to standard operating systems, databases, application servers, remote access layers, and commercial software components. In other words, they are part of OT where component transparency is more achievable and more immediately useful. If operators are serious, this is where they should begin, because the effort is lower and the payoff in vulnerability management is more visible. SBOM data improves the speed and efficiency of vulnerability response, helps identify end-of-support components earlier, and becomes far more powerful when integrated into vulnerability management and asset management tools already in use.

Vendor appliances are the real test. These are the black boxes that every site depends on, and very few teams can fully inspect. They are also where operator frustration is highest. It is suggested that buyers seek manufacturers who include hardware and software bills of materials with product delivery and who commit to timely remediation. That matters because procurement is often the only moment when the operator has real leverage. If an appliance supplier still treats component transparency as optional, that is no longer a technical footnote. It is a signal about how seriously they take lifecycle accountability.

Also Read: What big tech won’t show you about the future of AI

The mistake is treating SBOM as a file rather than a workflow

The market still talks about SBOM as though the job ends once a JSON or XML file has been generated. That is far too narrow, especially in OT. SBOM includes workflows for acquisition, management, and use, while its sharing work distinguishes between authors, consumers, and distributors across the lifecycle. SBOM is only data until it is consumed and converted into insight that can drive action. That is the right way to think about OT. A plant does not need more documents. It needs better decisions.

This is also why SBOM without VEX will disappoint many operators. A component list tells you what is inside. It does not tell you whether a newly disclosed vulnerability is actually exploitable in your deployed configuration, or whether the vendor has already assessed the exposure differently. VEX can be used alongside SBOM to improve prioritisation and effectiveness. In OT, that matters enormously because patching is costly and often disruptive. The real value is not finding every theoretical issue. It is knowing which issues deserve scarce outage time.

Can we actually do SBOM in OT

Yes, but it needs a sequence that respects operational reality.

First, use procurement to shape the future estate. Regulations are moving in that direction, and buyers should use that momentum. New PLC platforms, historians, SCADA systems, remote access products, and industrial appliances should be bought with explicit expectations around SBOM, update support, vulnerability disclosure, and version control. This is the easiest part of the OT estate to improve because it relies more on commercial discipline than plant retrofit heroics.

Also Read: How to unlock possibilities through data privacy enhancing technologies

Second, treat legacy products differently from new builds. Binary decomposition of software installation packages is recommended to generate SBOMs where no vendor-supplied SBOM is available, including for legacy software, where technically and legally feasible. When software already exists, binary analysis tools can use increasingly accurate heuristics and datasets to infer underlying components. That does not solve every appliance or controller, but it creates a realistic middle path for brownfield environments.

Third, connect SBOM to asset inventory and criticality from the start. The accurate inventory of vendor, model, firmware, operating system, and software versions is central to identifying and remediating vulnerabilities. SBOM disclosures should be aligned with asset inventories for risk exposure and criticality calculations. That is the step that turns software transparency into plant relevance. Without it, SBOM remains a software artefact. With it, it becomes part of operational risk management.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

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Consumers across Southeast Asia still experience e-commerce as a bargain-hunting paradise: flash sales, free shipping, vouchers, cashback, livestream discounts, and endless price competition. But behind that cheerful promotional theatre lies a harsher truth. The economics are getting tougher for merchants, and the ecosystem is increasingly built on a tension that may not be sustainable in the long term.

According to Ecommerce in Southeast Asia 2026 by MomentumWorks, platform take rates continue to rise across the region, with Shopee reaching a GAAP take rate of 13.5 per cent in the fourth quarter of 2025.

Yet sellers interviewed by MomentumWorks said their real all-in costs (including commissions, advertising, logistics, payment charges, affiliate fees, and platform services) often exceed 30 per cent of GMV.

Also Read: Shopee, TikTok, Lazada: Three ways to win and no easy way in

That gap between official take rate and lived merchant experience tells the real story of Southeast Asian e-commerce in 2026.

The published number is not the merchant’s number

A 13.5 per cent take rate sounds manageable, especially in a region where e-commerce platforms are still in growth mode. But sellers do not pay only the published commission. They pay for traffic. They pay for conversion. They pay to join campaigns. They subsidise consumers. They pay logistics and fulfilment fees. They pay affiliates. They often absorb operational leakage and returns as well.

MomentumWorks cites seller feedback suggesting that platform fees alone can approach 25 per cent even before a merchant includes its own shipping costs and affiliate spend. In some cases, the total drain on revenue approaches half the sale value before product cost is even counted.

This explains one of the report’s most striking observations: sellers are squeezed, but they cannot leave.

Platform dependence is the real moat

Why do merchants stay when margins are deteriorating? Because in Southeast Asia, platform demand is still overwhelmingly dominant.
MomentumWorks estimates that non-platform ecommerce GMV in the region totalled US$27.8 billion in 2025, against platform GMV of US$157.6 billion. That means roughly 85 per cent of e-commerce in Southeast Asia still flows through the major platforms. Social commerce, brand-owned websites, multi-brand retail sites, and chat-based transactions are growing, but they remain secondary.

For merchants, this creates a painful asymmetry. They dislike rising costs, yet they remain dependent on the platforms’ traffic and conversion machinery. Exiting a platform is not just a channel decision. It can feel like voluntary invisibility.

That dependence gives leading platforms enormous room to keep shifting economics in their favour, at least until behaviour changes at scale.

The paradox of cheap e-commerce

Perhaps the most provocative argument in the report is that Southeast Asia’s e-commerce has not yet reached its “true price floor”. That sounds counterintuitive in a market obsessed with discounts. But the report’s point is sharp: today’s affordability is often artificial. It is driven by subsidies funded by platforms, brands, and sellers—not by structurally lower supply-chain costs.

In plain English, prices look low to shoppers because someone else is carrying the burden.

If merchant economics are deteriorating while platforms still need vouchers and incentives to drive price competitiveness, then Southeast Asia has not yet produced a fully efficient discount retail model. It has only produced a heavily subsidised one.

That matters because the region still contains a large, highly price-sensitive consumer base that remains underpenetrated in e-commerce. If a platform can eventually redesign the supply chain rather than merely subsidise the transaction, the market could open much further.

The Temu question hangs over the region

This is where the report raises a question that should make every incumbent uncomfortable: Can a Pinduoduo or Temu-like model really emerge in Southeast Asia?

Also Read: Why quick commerce is really about frequency, not speed

The answer is not obvious. The region is more fragmented than China, with different languages, customs regimes, payment behaviours, logistics costs, and regulatory environments. But the demand side is compelling. Large parts of Southeast Asia remain highly price-sensitive. If a structural cost advantage can be unlocked through sourcing, inventory, logistics, and product design, the addressable market may be larger than current platform models suggest.

Cross-border flows offer a clue. In the Philippines, cross-border e-commerce GMV surpassed US$0.1 billion, with SHEIN and Temu driving significant parcel volume and freight tonnage. Thailand has tightened import oversight, and Vietnam continues to increase scrutiny. But demand has not disappeared. It is adapting.

The danger for incumbents is that they may be fighting over subsidised middle-income consumers while a deeper value segment remains only partially served.

Sellers are becoming multi-platform by necessity, not ambition

MomentumWorks notes that multi-platform operations are no longer optional for sellers. That is a critical shift. Merchants are not diversifying because it is an elegant strategy. They are doing it because platform dependence is risky, algorithmic visibility is unstable, and any one channel can suddenly become too costly.

This could reshape the e-commerce service landscape. Merchant software, cross-platform inventory tools, ad optimisation platforms, social commerce enablement, and direct customer retention solutions all become more relevant when sellers need to spread risk across channels.

The rise of affiliate-driven commerce compounds this. As platforms push more content-led discovery, brands and sellers have to spend more not just on logistics and platform fees, but on attention itself. Discovery is becoming both more expensive and more fragmented.

Regulators are entering the picture, but not to save sellers

Several Southeast Asian governments are tightening e-commerce rules, especially around imports, competition, and platform accountability. Thailand has abolished its de minimis exemption on imported goods. Vietnam has passed a new e-commerce law that places more responsibility on platforms to regulate sellers. Indonesia remains politically sensitive to the dominance of foreign-linked platforms and Chinese product inflows.

Also Read: SEA’s e-commerce giants hit profitability: What it means for region’s digital future

But regulation may not directly improve merchant margins. In fact, it could further entrench the biggest players by increasing compliance costs and favouring platforms with the scale to manage them.

That means sellers should not expect public policy to restore balance quickly. The structural tension will likely persist.

The next wave of opportunity may sit outside the transaction

For founders and investors, the lesson is clear. The biggest opportunities may no longer be in competing for the transaction itself, but in reducing friction for sellers trapped inside high-cost ecosystems. That includes better analytics, AI-enabled content production, customer retention, financing, embedded software, and tools that help merchants understand true profitability by channel.

Southeast Asia e-commerce still looks like a consumer success story. But underneath, it is becoming a merchant stress test. And when the people funding the discount machine start to crack, the whole system can change very quickly.

Cheap e-commerce, in this region, is getting expensive.

The post Why sellers can’t escape the e-commerce platforms that squeeze them appeared first on e27.

Global financial markets present a fascinating picture of resilience and shifting capital flows as we navigate April 2026. Investors find themselves at a crossroads of geopolitical relief and strong domestic economic indicators. The major United States indices reflect optimism among market participants today. The S&P 500 gained 18.33 points, a 0.26 per cent increase, closing at a record 7,041.28. The Nasdaq Composite rose 86.69 points, or 0.36 per cent, reaching 24,102.70 and hitting a historic all-time high.

This movement marks the 12th consecutive positive session for the Nasdaq. Analysts note this represents the longest winning streak for the technology index since 2009. The Dow Jones Industrial Average added 115.00 points, equivalent to a 0.24 per cent rise, finishing the trading session at 48,578.72.

A significant driver behind this market rally involves impactful developments on the geopolitical front. President Trump announced a 10-day ceasefire between Israel and Lebanon. This agreement became effective at 5 pm Eastern Time on April 16. This diplomatic breakthrough provided relief to investors who spent weeks watching regional instability threaten global trade routes.

Market sentiment improved drastically after new reports indicated that discussions between the United States and Iran were ramping up. These diplomatic conversations bring strong prospects of extending a separate two-week ceasefire. This potential de-escalation allows market participants to actively price a lower risk premium for equities across the board.

The energy sector tells a conflicting story right now. Brent crude climbed 4.7 per cent to US$99.39 a barrel as ongoing disruptions in the Strait of Hormuz push oil prices higher.

The domestic economy shrugs off these severe commodity shocks. Recent economic data signals robust resilience across multiple vital sectors. The Philadelphia Fed business index shattered expectations. It surged to a remarkable 26.7, easily beating the consensus expectation of 10.0. Initial jobless claims fell to a low of 207,000. These figures paint a definitive picture of a hot labour market. This economic heat provides the foundational support for the record stock indices we observe closing today.

The corporate earnings landscape offers a nuanced view of this economic resilience. Technology companies continue leading the charge. TSMC reported a 58 per cent jump in quarterly profit. The semiconductor giant confidently raised its 2026 revenue growth forecast to above 30 per cent. This upward revision validates the capital investments flowing rapidly into artificial intelligence infrastructure.

Not all corporate giants share in this euphoric market rally. Netflix shares plummeted nearly 10 per cent in after-hours trading. Management issued a soft Q2 revenue outlook, disappointing Wall Street. Netflix also announced that co-founder Reed Hastings will step down from the board in June. The financial and consumer staples sectors highlight a complex macroeconomic environment that requires careful navigation.

Also Read: The double-edged sword of AI in crypto trading

Charles Schwab shares fell seven per cent after the firm narrowly missed revenue expectations. The financial firm simultaneously announced plans to launch cryptocurrency trading for its client base. Consumer staples giants face their own unique challenges. PepsiCo successfully beat analyst expectations with an adjusted earnings per share of US$1.61. Management warned investors about a volatile macroeconomic environment lying ahead despite the positive earnings beat.

European markets reacted with enthusiasm to the diplomatic news earlier in the week. Indices like the DAX and the CAC 40 surged 5.1 per cent and 5.0 per cent, respectively, as traders anticipated lower energy costs. Asian markets opened notably lower on April 17. Regional traders weighed warnings that the United States-Iran conflict could persist for months, despite temporary ceasefire agreements dominating Western headlines.

The global financial ecosystem increasingly bridges the gap between traditional equities and digital assets. The cryptocurrency market currently sits at US$2.55T, representing a 1.02 per cent gain over the past 24 hours. This upward trajectory shows a strong 75 per cent correlation with the S&P 500. The global liquidity forces lifting traditional stocks actively drive this shared macroeconomic move. An institutional endorsement serves as the primary catalyst for this crypto market strength.

Citigroup published a landmark study on April 16 endorsing Bitcoin and gold as essential portfolio diversifies. The study definitively shows that adding both Bitcoin and gold to a traditional bond-and-equity portfolio increased returns without increasing risk over the past 10 years. This vital data provides a powerful narrative for institutional capital allocators managing trillions of dollars. Industry experts expect this research report to trigger fresh capital inflows into core digital assets.

Market participants must watch for sustained net inflows into United States spot Bitcoin exchange-traded funds. These investment vehicles recently saw their total assets under management rise to US$97.24B. This capital absorption proves that traditional finance treats digital assets as a permanent fixture.

The underlying technical indicators for the cryptocurrency market scream bullish momentum. The 7-day relative strength index currently sits at 74.76. This metric confirms the aggressive buying pressure dominating the order books. Speculative capital actively chases outsized returns in smaller capitalisation tokens.

Investors rotate capital into high-beta sectors in search of massive gains. Top gainers like SIREN skyrocketed by 125.84 per cent over a short period. ORDI posted an astonishing 133.51 per cent gain during the same timeframe. Investors rotate their profits from Bitcoin into riskier assets. They search for asymmetric upside in digital narratives such as the Binance Ecosystem.

Also Read: The alarming reason crypto now moves like gold but falls like stocks

The broader digital asset market has not yet entered a full-on altcoin frenzy despite these explosive moves. The Altcoin Season Index currently sits at a neutral 37. A sustained rise above 50 would confirm a comprehensive alternative coin rally. The immediate path for the cryptocurrency market hinges on ongoing institutional behaviour and upcoming regulatory catalysts.

Technical analysts identify key overhead resistance at the 127.2 per cent Fibonacci extension level. This technical level aligns with the US$2.63T total market capitalisation mark. Breaking above this ceiling requires sustained buying pressure from major financial institutions.

The overall market must securely hold the 23.6 per cent Fibonacci support level residing at US$2.49T. Losing this support level could trigger a cascade of profit-taking across all digital assets. Fundamental catalysts will determine which direction the market breaks next. The Securities and Exchange Commission scheduled a vital roundtable discussion covering the CLARITY Act for April 16. This regulatory event could provide the directional cue the market needs right now.

My perspective as an active investor suggests that the current market dynamics represent a fundamental shift. We witness traditional finance capitulating to the mathematical reality of digital assets. The Citigroup study and fund inflows clearly evidence this institutional shift.

Traditional equities simultaneously exhibit remarkable resilience to geopolitical shocks and soaring crude oil prices. The strong correlation between cryptocurrency and major stock indices proves modern investors treat all global assets as interconnected vessels of systemic liquidity.

The current bullish case rests heavily on continued economic resilience among American consumers. Market participants must remain vigilant. Prudent investors must carefully balance the excitement of record index highs against the lurking risks of sudden geopolitical deterioration or unexpected regulatory headwinds.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The post Crypto at US$2.55T: Bull market confirmation or trap for retail investors? appeared first on e27.

Southeast Asia’s e-commerce story has long been framed as a consumer triumph: cheap prices, endless deals, and frictionless convenience. But this model is beginning to show strain where it matters most: at the merchant level.

What makes the current moment interesting is not just rising platform costs, but the growing disconnect between headline metrics and lived reality. A 13.5 per cent take rate sounds manageable until sellers account for advertising, logistics, and incentives that can push total costs beyond 30 per cent. At that point, scale becomes less about growth and more about survival.

Yet merchants remain locked in. Platforms still control demand, and leaving them often means losing visibility altogether. That dependence is the real moat, and the real risk.

The bigger question is what breaks first: seller margins or the subsidy-driven pricing model. If the ecosystem cannot transition from incentives to structural efficiency, the current equilibrium may not hold.

For founders and investors, the opportunity is shifting. The next wave may not be about owning transactions, but about helping merchants survive them.

Regional

SEA merchants trapped in a high-cost e-commerce squeeze: While Shopee’s GAAP take rate hit 13.5%, sellers report all-in costs exceeding 30% of GMV; yet platform dependence, with 85% of regional commerce flowing through major players, makes exit feel like voluntary invisibility.

Shopee, TikTok Shop, and Lazada now control SEA e-commerce: Platform GMV in Southeast Asia reached US$157.6B in 2025, up 22.8%, but Shopee, TikTok Shop, and Lazada now command 98.8%of regional platform commerce, leaving no room for another large horizontal marketplace.

Quick commerce is a fight for frequency, not just speed: MomentumWorks argues that platforms like Shopee, Grab, and Lazada are using instant delivery not to win a logistics race, but to build habitual urban demand; the platform that wins habit wins far more than any single basket.

Vietnam’s Farmnet secures US$11.75M institutional loan: TechCoop’s trading arm raised a senior secured loan from impact investor Symbiotics, the first offshore institutional borrowing by a Vietnam-incorporated TechCoop entity, to scale agricultural commodity trading across 641 co-operatives nationwide.

Indonesia’s Baskit raises US$9.9M to take supply chain model regional: The profitable AI-enabled distribution startup, backed by Cento Ventures and HSBC Innovation Banking, is expanding into the Philippines after three years mastering Indonesia’s fragmented offline trade channels.

Choco Up launches US$30M private credit facility for APAC SMEs: Partnering with tech-driven credit specialist CHUAN, Singapore’s Choco Up is targeting Asia’s US$2.5T SME funding gap with AI-powered underwriting that promises approvals in hours, not months.

Animoca Brands secures Hong Kong stablecoin licence: Through its joint venture Anchorpoint, with Standard Chartered and HKT, Animoca is one of only two entities out of 36 applicants to receive an HKMA stablecoin issuer licence, gaining a regulated settlement rail for digital assets.

eFishery founder faces 10-year jail term in Indonesia: Prosecutors asked the Bandung District Court to sentence Gibran Huzaifah after he admitted to inflating the aquaculture startup’s revenue, with alleged losses exceeding 69B rupiah and investor confidence severely damaged.

TikTok disables 780,000 underage accounts in Indonesia: TikTok became the first platform to report compliance action under Government Regulation No. 17/2025, disabling accounts held by users under 16, while Roblox failed to fully comply due to lingering stranger-chat features.

Indonesia’s e-commerce child safety rules spark industry confusion: Ministerial Regulation 9 of 2026 requires platform self-assessments to set child access limits, but industry players are questioning whether high-risk classifications were assigned to major marketplaces before those assessments were even completed.

Nadiem questions Chromebook corruption loss calculation: A LinkedIn post by Gojek co-founder Nadiem Makarim argued that trial testimony, including from resellers and procurement officials, challenges the 1.5T rupiah state-loss figure cited by prosecutors, noting two independent audits found no markup.

Singapore businesses hit an AI automation wall: A HubSpot survey of 700+ local business leaders found that while nearly two-thirds use AI daily, only 18% have deployed fully autonomous agents, with data quality and legacy integration gaps becoming more acute, not less, as organisations scale up.

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Interviews & Features

From chatbots to creators: Indonesia’s AI startups to watch: A new wave of Indonesian startups is applying AI across finance, healthcare, content, and commerce, highlighting how local innovation is shaping practical, scalable solutions in Southeast Asia’s evolving digital economy.

Share2Inspire founder: your CV isn’t failing, it’s being misread: Samuel Rolo, a veteran of Deloitte and AstraZeneca, built a career intelligence platform that scores CVs against applicant tracking systems — arguing most rejections stem from formatting and presentation failures rather than lack of capability.

A founder built an AI agent for himself, then turned it into a micro-SaaS: What started as a personal productivity tool called Seraphina, handling content, replies, and community management, grew to 2,000 users and became a layered business model spanning SaaS, education, and consulting.

Southeast Asia’s GameFi markets each play different roles in Web3: A Vietnamese expat living in Manila argues that the Philippines is a consumer-amplifier, Indonesia a scale-user market, and Vietnam a builder hub, with the 2026 gaming market projected at US$14.86B and maturing toward fun-first, stablecoin-integrated models.

Singapore’s AI adoption gap: from tools to real-world impact: Experts from AI Singapore, JJ Innovation, and Knovel Engineering say adoption lags not from reluctance but from poor data readiness, cultural resistance, and a critical need for “plus-skilling” — upskilling existing roles rather than wholesale retraining.

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International

OpenAI to spend over US$20B on Cerebras chips over three years: The deal, which could give OpenAI warrants for up to a 10% stake if spending hits US$30B, reflects surging demand for AI inference computing and a US$1B commitment toward funding new data centres.

Some OpenAI investors question its US$852B valuation: After two product roadmap shifts in six months and a recent US$122B raise, backers worry the enterprise and coding pivot could weaken ChatGPT’s position against Anthropic and a resurgent Google ahead of a potential IPO.

Perplexity’s revenue jumps 5x to US$500M: CEO Aravind Srinivas announced the revenue leap, from US$100M, alongside 34% headcount growth, with the AI search startup targeting a further 2x revenue increase in 2026 using the same lean team and its Computer product.

SoftBank raises US$3.6B in high-yield bonds amid AI debt surge: The sale, comprising US$1.5B in dollar notes and €1.8B in euro bonds, came as its AI investment push drove borrowing costs higher, with its 10-year dollar coupon at a record 8.5% and shares down 35% since November.

Snap cuts 1,000 jobs as AI takes over code generation: With AI now producing over 65% of new code, Snap is laying off 16% of its workforce and closing 300 open roles, expecting annualised savings of more than US$500M by the second half of the year.

Netflix co-founder Reed Hastings to exit in June: Following a failed Warner Bros Discovery merger and a stock drop of about 9%, Hastings will not stand for re-election as Netflix posts Q1 revenue of US$12.25B, up 16%, while forecasting its slowest growth in a year.

Saudi PIF raises Lucid investment with US$550M in convertible stock: The funding accompanies Uber’s additional US$200M commitment and a purchase commitment of at least 35,000 Lucid vehicles, as the EV maker expands its robotaxi fleet ambitions.

Nas Daily creator raises US$27M for AI business builder: Nuseir Yassin’s Nas.com secured the Series A round led by Khosla Ventures, with 500 Global, V Ventures, and Factorial Capital also participating, though valuation and use of funds were not disclosed.

Naver plans IPO for Naver Financial after Dunamu share swap: The deal would give Naver Financial full ownership of Upbit operator Dunamu, targeting a listing within five years, though Korea’s proposed Digital Asset Basic Act and an ongoing antitrust review could affect structure and timing.

Robotaxi market projected to reach US$168B by 2035: Counterpoint Research links the forecast to AI advances, larger fleets, and wider commercial rollouts, with the US and China accounting for most deployments, led by Waymo, Tesla, Baidu’s Apollo Go, WeRide, and Pony.ai.

India’s AI firms pursue acquisitions to build full-stack capabilities: As enterprise clients consolidate vendors and shift from trials to larger deployments, Tracxn recorded five deals in four months, including C5i’s US$45M-US$50M acquisition of UK-based Datavid.

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Cybersecurity

DeFi faces twin blows from falling yields and a US$285M hack: Lending rates on Aave have dropped below the US Federal Reserve’s benchmark, while a North Korean-linked group’s theft from Drift has shaken confidence in the US$97B sector as firms pivot toward tokenised traditional assets.

AML compliance is becoming PropTech’s biggest opportunity: With Australia’s Tranche 2 reforms bringing 80,000 real estate professionals under AML obligations from July 2026, and Singapore, Hong Kong, and Japan tightening rules, founders who build identity verification and beneficial ownership tools are entering a mandated, rapidly growing market.

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Semiconductor

TSMC expands 3nm production across Taiwan, Arizona, and Japan: The chipmaker is building new 3nm lines in Taiwan for H1 2027 mass production, with its second Arizona fab set for H2 2027 and a second Japan plant using the 3nm process targeting 2028 — all driven by AI, automotive, and IoT demand.

Nvidia CEO warns US AI export limits are backfiring: Jensen Huang argues that restricting advanced hardware forces rivals to build independent systems, framing the real technology race as a contest over energy grids and software ecosystems rather than chip speed alone.

China’s semiconductor and robotics sectors lead AI-driven hiring: Data from 51job and Zhaopin shows electronics and semiconductors drew 1.5x more applications than other sectors, robotics recruitment rose 36.6% year-on-year, and demand for AI engineers is running three times supply, pushing salaries to US$95,000 for generative AI roles.

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AI

The next AI race is being fought in the physical world: As AI expands into connected devices, wearables, and industrial systems, trust — not model quality — becomes the decisive factor for enterprise adoption, with reliability, latency, privacy, and resilience under imperfect conditions determining which companies scale.

Why founders cannot afford to outsource judgment to AI: Drawing on Gojek’s and Grab’s founding stories, this essay argues that Southeast Asia’s regulatory fragmentation and cultural complexitymean contextual judgment, which AI cannot replicate, remains a founder’s deepest moat and most durable competitive advantage.

The agentic economy needs a new management discipline: As AI agents take over entry-level tasks and hybrid workforces emerge, the author coins “H-AgR”, Human and Agent Resources, arguing that Singapore’s January 2026 AI Governance Framework sets a regulatory floor, but enterprises must build governance structures well above it.

AI adoption in APAC is a customer acquisition problem, not just an ethics one: Western-trained AI marketing tools systematically deprioritise underserved segments, which are often less saturated and more loyal once reached, making bias correction a growth strategy, not a compliance exercise, for APAC startups.

Inclusive AI isn’t optional; it’s Asia’s competitive edge: With Asia holding 60% of the world’s population across linguistically diverse and economically varied communities, AI built without inclusion baked in will not just replicate bias — it will scale it — making DEI-AI literacy a leadership imperative, not an HR function.

NTU researchers build AI-powered biochip for 20-minute disease detection: The Singapore team’s platform combines nanophotonic structures with AI image analysis to simultaneously detect three disease-linked microRNAs, achieving over 99% accuracy in lab tests without requiring PCR amplification.

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Thought Leadership

Why Southeast Asian startup founders should flow, not force: Drawing on psychology, Daoism, and physics, this column argues that the most durable startups align with structural macro trends rather than force outcomes, and that founder mindset coherence is not soft advice, but operational infrastructure.

Narrative clarity is a strategic advantage in SEA’s tough market: As investors tighten scrutiny and customers compare across borders, the companies that scale in Southeast Asia will be those that articulate a clear, consistent story, not just those with the strongest technology.

The advice trap: true stories missing their conditions: Most business advice shared on conference stages is accurate, but stripped of the market timing, team dynamics, and sequencing that made it work, meaning founders who follow maps drawn for different terrain often fail not from bad judgment, but from misapplied wisdom.

Digital growth in Asia: how startups can avoid costly pitfalls: From overlooking mobile-first design to ignoring local payment methods, neglecting data analytics, and treating PR as an afterthought, nine common digital marketing mistakes are quietly killing startups across Asia’s fast-growing but fragmented digital economies.

AI is redefining software development and CEOs must lead: Generative AI tools are accelerating development cycles and creating new roles like prompt engineers and AI workflow architects, but organisations clinging to outdated delivery models risk being outpaced by leaner competitors who have aligned leadership, talent, and process around AI.

The missing rung: how automation is quietly breaking the career pipeline: AI has not just replaced repetitive jobs; it has eliminated the entry-level roles that once served as informal training grounds, creating a generation of workers entering management without the foundational decision-making experience grunt work once provided.

Asia’s logistics startups are turning to AI to solve the last-mile puzzle: With 253M online shoppers projected by 2030 and a 15% failed delivery rate in COD markets, AI-powered route planning, demand forecasting, and dispatch automation are cutting fuel costs by 20% and improving delivery times by 30% across the region.

In the age of AI, people matter more than ever: Vietnam, Singapore, and Thailand are all investing heavily in AI literacy programmes, but the real edge for organisations lies in creating psychological safety, rewarding results over hours, and actively funding employee upskilling — not just deploying better tools.

Why founders should stop hustling and start automating: Manual workflows are a growth ceiling, not a badge of honour, and using tools already at hand like Excel, Google Sheets, and Airtable to build systems that run without the founder is what separates sustainable scaling from perpetual firefighting.

APAC’s esports broadcast innovation is rewriting the global playbook: Driven by mobile-first audiences in Indonesia and the Philippines, data-hungry viewers in Korea, and creator-led communities in India, Southeast Asia’s demand for multi-angle streams, real-time analytics overlays, and localised production is redefining what fans expect from live competition globally.

Asia’s water crisis needs blockchain, IoT, and AI, not desalination alone: With 12 of the world’s 17 most water-stressed nations in Asia and a US$800B infrastructure gap, smart water grids powered by IoT sensors and AI forecasting, combined with blockchain-enabled transparency, offer a more sustainable path than ecologically damaging desalination.

AI doesn’t talk nonsense; you just need to learn how to talk to it: Many first-time users give up on AI after receiving poor responses, but the problem is rarely the model, it is the question. Treating prompts as directions, not commands, and asking AI to critique its own output transforms the experience dramatically.

The post Ecosystem Roundup: The illusion of cheap e-commerce appeared first on e27.

Over the past two years, a flood of startups and incumbents have raced to build “AI copilots” for finance. Almost every demo shows a chatbot answering analyst questions or summarising a report. Yet despite billions in investment, adoption across financial institutions remains slow, and productivity gains are modest.

The reason is not a lack of ambition or data. It’s that most companies, founders, and technologists fundamentally misunderstand what it takes to turn AI into business value, particularly in a domain that prizes trust, precision, and accountability above all else.

The missing equation: Value and feasibility

Successful technology adoption depends on finding where business value meets real-world feasibility. Feasibility does not stop at algorithms; it lives in people, processes, and governance.

In banking and asset management, that balance is especially delicate. According to the Evident AI Index 2025, banks with the highest AI maturity, such as JPMorgan Chase, Capital One, and RBC, share one key trait. They invest as much in organisational enablement as they do in model development. These leaders report more use cases because employees trust and use their systems.

Contrast that with the many failed pilots elsewhere, where a 2025 MIT study found that over 95 per cent of generative AI pilots fail to scale because teams “avoid friction.” They chase flashy prototypes that collapse in production. Much of this friction comes from the lack of user trust and limited control over outputs.

Why finance resists the hype

Finance’s slower adoption of AI stems not from conservatism but from accountability. Every output, whether a risk score or a research summary, must be explainable, auditable, and defensible. That accountability clashes with the automation-first mindset many startups adopt. Replacing an analyst or risk officer with an opaque model erodes trust and invites regulatory risk.

As Evident Insights notes, only a few major banks, such as BNP Paribas, DBS, and JPMorgan, report both realised and projected ROI from AI projects. They succeed because they have governance and transparency frameworks that others lack. Oversight is not a bottleneck but the foundation of adoption, where the goal is not to replace human decision-making but to reinforce it through systems that enhance judgment and accountability.

Also Read: The psychology of AI adoption: How familiarity bias is quietly slowing finance down

Automation is easy, augmentation is hard

The default format of GenAI applications, the chatbot, reflects this misunderstanding. It promises frictionless automation but often creates new friction because users do not trust the answers, cannot audit the reasoning, and find the interface detached from their actual workflow.

Real progress lies in workflow-aware systems that amplify human expertise rather than replicate it — JPMorgan’s internal LLM Suite illustrates this well. It did not begin as a single grand platform but as a collection of focused, high-value tools for developers, researchers, and compliance officers. Each tool demonstrated its worth before being integrated into a secure workbench that now serves more than 200,000 employees and saves analysts and developers several hours each week.

The lesson is simple: the future belongs to systems that scale human insight, not those that try to substitute it.

The false promise of platforms

When startups pitch “AI platforms” for finance, they often repeat the same mistake that weakened earlier enterprise software. Platforms may look scalable and visionary, but they often turn into complex, cumbersome systems that users tolerate rather than appreciate.

History makes this clear. In the 2010s, tools such as Salesforce and Workday succeeded by solving one pressing problem deeply before expanding outward. Yet as they evolved into sprawling platforms, usability declined. Layers of plugins and integrations turned once-simple workflows into endless clicking and reconciliation, making them less effective the more they tried to do.

The same fatigue is now emerging in financial AI. Many products start and remain generic, from document summarisers to universal copilots and so-called AI operating systems that claim to serve every department but serve none well. The next generation of leaders will move in the opposite direction, building deep, vertical, and trust-focused systems that create real value in areas such as investment research, credit adjudication, and financial crime detection.

Why startups keep missing the mark

Many so-called finance AI startups are led by former bankers, but most come from back-office or auxiliary roles rather than the front lines of research, trading, or client-facing decision-making. That gap in operational empathy shows, as they build tools that over-automate processes, undermine trust, and overlook the reasoning that drives real decision conviction.

Each time an AI system produces an unexplainable result, it erodes credibility. In finance, credibility is currency; once it is lost, adoption disappears. Human-in-the-loop design is not philosophical but commercial. Systems that allow users to trace reasoning, correct mistakes, and feed improvements back into models create feedback loops that build trust and long-term data advantages grounded in real use, not scraped content.

Also Read: The psychology of AI adoption: How familiarity bias is quietly slowing finance down

Augmenting judgement: The middle ground

Between full automation and manual work lies a wide, unexplored space where AI can enhance human judgement and creativity. In investment research, this means helping analysts link cause and effect, such as how a policy change in Washington might influence earnings in Shenzhen, rather than merely summarising data. In portfolio construction, it means simulating alternative narratives, while in risk management, it means contextualising anomalies instead of simply flagging them.

These are challenges of reasoning and workflow, not of chatbots. Solving them requires systems that understand how analysts think and how hypotheses, evidence, and implications interrelate. That is the true frontier of progress: AI as collaborator rather than correspondent.

The way forward

The next wave of financial AI will not emerge from chatbots or generic copilots. It will come from innovators who build workflow-specific products that respect trust, auditability, and regulation. These systems will turn analysts into super-analysts, not by automating their judgment but by strengthening it.

For innovators, the challenge is to design for credibility rather than convenience. For established institutions, it is to invest in what is feasible today rather than chase distant visions. Finance will be reshaped not by replacing people but by changing how good decisions are made and scaled. Those who recognise this will define the next decade of innovation. Those who do not will continue building tools for problems that never mattered.

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