For over a decade, Sony Acceleration Platform has quietly supported more than 1,000 business development cases through Sony’s internal innovation arm. Its newest initiative, the Boundary Spanning Service, extends that experience across borders, connecting Japanese corporations seeking practical innovation partners with Singapore’s fast-moving startup ecosystem.

Developed in collaboration with e27, Boundary Spanning Service reflects a broader shift in how Japanese enterprises are approaching open innovation: not as a scouting exercise, but as a long-term, trust-based collaboration. e27 spoke with Sony Acceleration Platform team about what is driving this initiative, and what it means for founders on both sides of the corridor.

e27 sat down with the Sony Acceleration Platform leadership to discuss the vision behind Boundary Spanning Service and what it means for Singapore founders.

The vision and context

Could you share a little about what led to the creation of the Boundary Spanning Service – what need or opportunity did Sony Acceleration Platform observe that this initiative is designed to address?

The creation of the Boundary Spanning Service was driven by a strategic need to address a critical structural issue in business development: the tendency for promising projects to ‘run out of time’ before they can fully scale.

Drawing on over 12 years of experience supporting more than 1,000 business development cases within the Sony Acceleration Platform, we observed that one of the reasons why new businesses often fail is not lack of viability, but due to rigid corporate constraints.

To bridge this gap, Boundary Spanning Service was established to act as a ‘Boundary Spanner’. Sony’s own history is defined by absorbing external knowledge to drive growth; thus, facilitating open innovation is a natural extension of our DNA. Through the Boundary Spanning Service, we would like to provide a structured framework that connects Japanese corporations facing specific innovation bottlenecks with Singapore’s agile and highly capable startup ecosystem. By crossing organisational and geographic borders, Boundary Spanning Service lowers survival costs and accelerates real-world deployment, ensuring valuable business developments are not prematurely terminated.

From Sony Acceleration Platform’s perspective, what makes Singapore a meaningful starting point for this initiative? We’d love to understand what Sony Acceleration Platform sees in the Singapore ecosystem that feels relevant to Japanese corporates.

Singapore is uniquely positioned as our starting point because of its exceptional alignment with the strategic needs of Japanese enterprises. The Singapore ecosystem offers a rare combination of advanced technological capability, a highly robust and predictable regulatory environment, and seamless English-language business operations.

For Japanese corporations looking to mitigate risk and operational uncertainty in cross-border ventures, these factors provide an incredibly stable and efficient platform. Singapore’s startup community is not only highly innovative but also operates with global compliance and agility, making it the ideal counterpart for Japanese enterprises seeking reliable, fast-paced co-creation.

Also Read: e27 expands AI-powered business matchmaking with Sony Acceleration Platform collaboration

When Japanese corporations come to the Boundary Spanning Service, what kinds of challenges or aspirations are they typically bringing with them? Are there particular themes or sectors you’ve seen emerge?

Japanese corporations are not coming to Boundary Spanning Service for abstract technology scouting or passive trend-watching. Instead, they bring highly defined, practical operational bottlenecks and specific innovation challenges. They are actively seeking practical, market-ready solutions that can be integrated into their existing value chains.

While the technical fields vary, the underlying theme is the need for rapid digital transformation, advanced automation, and niche technological capabilities that can be fast-tracked for real-world, commercial deployment. They come with a genuine urgency to solve immediate business bottlenecks by leveraging the agility of external partners.

The nature of Japan-Singapore collaboration

How would you describe the spirit of collaboration that Boundary Spanning Service is designed to enable? What does a meaningful, productive engagement between a Japanese corporate and a Singapore startup tend to look like in practice?

Boundary Spanning Service is designed to move far away from low-value, one-off “transactional procurement”. A truly productive engagement must be grounded in mutual trust and reciprocal value creation.

In practice, this means establishing a collaborative framework where both parties act as equal partners. The Japanese corporate provides deep operational resources, industry expertise, and market access, while the Singapore startup provides the agility, speed, and disruptive technology needed to overcome the bottleneck. We foster an environment where cultural and organisational differences are structurally bridged, transforming potential friction into collaborative synergy.

Could you share a sense of what success looks like for both the Japanese corporate and the Singapore startup that comes through the Boundary Spanning Service? Even in broad terms, what outcomes feel meaningful to Sony Acceleration Platform?

Meaningful success is achieved when the collaboration translates into a viable, long-term business outcome. For the Singapore startup, this means successfully scaling their operations and entering the Japanese market backed by the massive distribution networks and credibility of a major corporate partner. For the Japanese corporate, it means successfully resolving a critical business bottleneck while absorbing the entrepreneurial agility and speed of the startup.

For Singapore founders

For a Singapore startup founder who is curious about Boundary Spanning Service, what qualities or characteristics tend to make for a strong and rewarding collaboration with Japanese corporate entities? What do you find matters most?

The most critical asset a founder can bring is a commitment to mutual alignment and long-term planning. Japanese corporate partners place an immense premium on quality standards, operational stability, and meticulous planning.

Instead of viewing these requirements as bureaucratic delays, successful founders recognise them as the very foundation required to achieve sustainable, enterprise-grade scalability. A willingness to understand these operational values, combined with transparent communication and professional patience, is what truly secures a rewarding, high-yield partnership.

Also Read: Global expansion is no longer about reducing information costs, it’s about reducing trust costs

What would a founder’s journey through the Boundary Spanning Service look like from start to finish – from the initial application through to the first conversation with a Japanese corporate? What should they expect in terms of timing and engagement?

We have structured the journey to be as seamless and high-probability as possible. Through our joint effort with e27, startups can apply through a highly streamlined, low-friction application process.

From late September, Sony Acceleration Platform will start sharing and recommending the startup’s profile to the participating Japanese companies who are interested in connecting with Singapore companies.

Is there anything you’d like to say to Singapore founders who may be open to this kind of collaboration but are perhaps unfamiliar with how Japanese corporates typically work or what they value in a working relationship?

It is important to understand that the thoroughness of Japanese corporate decision-making—which often involves extensive internal consensus-building—is a structural characteristic, not a personal hurdle.

While this front-loaded alignment process takes time and structured engagement, the payoff is unparalleled. Once a Japanese corporate commits to a partner and establishes mutual trust, that relationship translates into exceptionally stable, deeply committed, and highly scalable long-term support. We encourage founders to focus on building a robust foundation of quality and trust from day one.

Looking ahead

Looking ahead, what does Sony Acceleration Platform hope the relationship between Japanese corporate innovation and Singapore’s startup ecosystem will look like over time? What would feel meaningful to you personally?

Our ultimate vision is to see cross-border co-creation transition from a “special project” into a standard, daily operational model. Personally, it would be deeply rewarding to see this corridor become the default pathway for global-scale business development.

We highly encourage forward-thinking founders to leverage the Boundary Spanning Service to position themselves at the very forefront of this evolving bilateral corridor.

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The post Bridging boundaries: Sony’s blueprint for Japan-Singapore innovation collaboration appeared first on e27.

Southeast Asia’s startup story is usually told through ride-hailing, fintech, and e-commerce. But a quieter, stranger, and potentially more consequential sector is taking shape in the region’s labs, farms, and hospitals: biotech.

Founders are using fermentation to turn waste into biomaterials, growing seafood and fat from cells, building AI tools for cancer care and heart scans, engineering crops for tougher climates, and developing diagnostics designed specifically for Asian populations. It is not an easy sector to build in; biotech demands patient capital, deep technical talent, complex regulatory navigation, and long commercialisation cycles.

Also Read: Asia’s biotech boom: Innovation, investment, and a new era of discovery

Yet the sheer breadth of companies now emerging from Singapore, Malaysia, Indonesia, Thailand, Vietnam, and the Philippines suggests the region’s life-sciences ecosystem has moved well past the experimental stage, and is beginning to challenge assumptions about where deeptech gets built.

Below is a list of 27 biotech firms that are redrawing the region innovation map:

RWDC Industries (Singapore)

RWDC ferments used cooking oil into PHA, a fully biodegradable biopolymer that’s meant to replace single-use plastic in straws, cutlery and packaging.

Protenga (Singapore/Malaysia)

Protenga runs “Smart Insect Farms” that turn organic waste into black soldier fly protein for aquaculture, animal feed and pet food.

Engine Biosciences (Singapore/US)

Engine Biosciences combines AI with wet-lab biology to map gene interactions and speed up cancer drug discovery.

Us2.ai (Singapore)

Us2.ai uses AI to automate the reading of echocardiograms, cutting a process that takes cardiologists many minutes down to under two.
Founders: James Hare, Dr Carolyn Lam, Dr Yoran Hummel and Paul Seekings

AMILI (Singapore)

AMILI runs Southeast Asia’s first gut microbiome bank, building an Asia-specific database to power diagnostics and personalised nutrition.

KYAN Technologies (Singapore)

KYAN applies “small data AI” to match cancer patients with the most effective drug-dose combinations, developed with NUS and UCLA.

ImpacFat (Singapore)

ImpacFat cultivates omega-3-rich fish fat from stem cells, aimed at alt-meat, cosmetics and supplements.

Qarbotech (Malaysia)

Qarbotech makes QarboGrow, a carbon-quantum-dot photosynthesis enhancer that boosts crop yields without genetic modification.

NLYTech Biotech (Malaysia)

NLYTech develops biodegradable, plastic-free packaging materials made from natural ingredients as an alternative to single-use plastics.

Vulcan Augmetics (Vietnam)

Vulcan builds affordable, modular robotic prosthetics designed to click together like building blocks.

Teora (Singapore)

Teora develops biologics that manage disease in agriculture and aquaculture without relying on chemical pesticides.

KINNVA (Singapore)

KINNVA is a synthetic-biology company using fermentation to turn waste streams into biochemicals for food, feed and cosmetics.

Sinhke (Vietnam)

Sinhke builds AI-powered hardware that measures shrimp larvae health before farmers commit to large-scale cultivation.

Virdalis (Singapore)

Virdalis is building a cultivation and data platform around duckweed, the world’s fastest-growing flowering plant, as a soy alternative for animal feed protein.

Allozymes (Singapore)

Allozymes runs an ultra-high-throughput microfluidics platform that screens millions of enzyme variants a day, effectively an “enzyme discovery engine” for pharma, food and chemical industries.

FathomX (Singapore)

FathomX is an NUS/NUHS spin-off building AI to improve the accuracy of mammograms, particularly for dense breast tissue common among Asian women.

REVIVO BioSystems (Singapore)

An A*STAR spin-off building “organ-on-a-chip” 4D human skin models to replace animal testing for cosmetics and pharma compounds.

Advanx Health (Malaysia)

Malaysia’s first consumer DNA-testing company, offering genetic reports on health risk, nutrition and fitness traits.

KosmodeHealth (Singapore)

An NUS Food Science spin-off extracting proteins and fibres from food-processing waste to formulate functional foods and biomedical bio-ink.

Imagene Labs (Singapore)

A subsidiary of Asia Genomics offering saliva-based DNA testing for personalised nutrition, skincare and fitness products across Asia.

Meatiply (Singapore)

Meatiply is a multi-cell-type cultivated meat company that produced Asia’s first cultivated smoked duck breast.

Singrow (Singapore)

An agri-biotech firm that cross-bred and gene-edited the world’s first tropical-climate strawberry, grown in an indoor vertical farm.

Dendrotonics (Philippines)

Develops biodiversity-restoration technology to make degraded land ecologically and commercially productive again.

QuikPath (Singapore)

Built a self-administered RT-PCR Covid-19 screening technology designed to scale rapid, accurate infection monitoring.

ETBio (Singapore)

Harnesses microalgae to build next-generation air filtration solutions.

Ternion Biosciences (Singapore)

Provides high-throughput cardiac safety screening assays used in preclinical drug development.

CloudSeq (Singapore)

CloudSeq runs an NRF-backed cloud platform built to handle big data for healthcare and agricultural genomics.

The post The 27 SEA biotech firms betting on cells, fermentation, and code appeared first on e27.

Something strange is happening in Vietnam’s engineering hiring market right now. Companies report talent shortages. Candidates report rejection rates higher than ever. Both are telling the truth.

The gap between them isn’t a supply problem. It’s a definition problem, a fundamental mismatch between what companies say they need, what their hiring processes actually select for, and what the engineers who will matter most in the next three years actually look like.

I’ve spent a decade placing engineers across Southeast Asia. I’ve seen this kind of misalignment before. I haven’t seen it this structural.

The shift nobody fully prepared for

Eighteen months ago, the hottest debate in engineering circles was whether “Vibe Coding”, the practice of generating code entirely through natural language prompts to AI, was a legitimate workflow or a shortcut for junior developers. That debate is now over.

It turns out both sides were right, and both sides missed the point.

Yes, Vibe Coding accelerated output. A GitClear analysis of over 211 million lines of changed code found that AI-assisted workflows boosted boilerplate writing by 25–50 per cent. Yes, it also introduced a technical debt crisis: refactoring rates dropped from 25 per cent in 2021 to under 10 per cent in 2024, while duplicated code quadrupled. Over 40 per cent of junior developers admitted to deploying AI-generated code they hadn’t read.

By early 2026, Andrej Karpathy, one of the people who popularised the Vibe Coding concept, had already moved on. He began describing what comes next: Agentic Engineering. Not writing code, not prompting AI to write code, but orchestrating autonomous AI agents: setting specifications, auditing outputs, managing feedback loops, and owning architectural decisions.

The role of a software engineer is shifting from executor to decision-maker.

That shift has a direct consequence for anyone responsible for hiring.

The talent gap is real, but it’s not the gap most people think

Vietnam’s numbers are striking. The country now has 530,000–600,000 software engineers in a workforce of over 1.2 million ICT professionals. Universities produce 55,000–60,000 IT graduates per year. On paper, this looks like abundance.

In practice, demand for new technology positions exceeds 500,000 roles annually, a structural mismatch approaching 10x. And that gap is widening, not closing, for two compounding reasons.

Also Read: Vietnam’s healthtech boom has a talent problem nobody is talking about

• First, traditional industries entered the race. Banking, retail, and manufacturing have accelerated digital transformation, competing directly with tech companies for the same engineering talent. The pool didn’t grow; the number of teams fishing in it multiplied.
• Second, semiconductors arrived. Both Ho Chi Minh City and Hanoi are now running significant semiconductor and chip-design initiatives; HCMC alone is targeting 3,000 specialist engineers, backed by programmes at ĐHQG and SHTP. Vietnam’s national target is 50,000 semiconductor engineers at university level by 2030, supported by government scholarships worth 1,300 billion VND (US$49.4 million) annually for approximately 30,000 learners.

The consequence? The best STEM graduates are no longer choosing software development as their default. The pool of candidates that tech companies relied on for the past decade is being redirected upstream.

The result: average time-to-fill for a Senior offshore engineer has stretched to 45–60 days. Retention for engineers over two years has fallen from 78 per cent in 2023 to roughly 65 per cent in 2026. Senior IT salaries have risen 50–70 per cent compared to 2024, with significant variation depending on specialisation and language ability.

The two mistakes companies are making right now

Mistake one: Hiring for the old role

Most job descriptions I see in 2026 are still optimised to find Task-Based Coders, engineers who execute well-defined tickets, follow established patterns, and stay in their lane. The interview process tests syntax, algorithms, and framework knowledge.

But the engineers who will deliver the most value in an Agentic Engineering environment are evaluated on completely different dimensions: system design judgment, the ability to audit AI-generated outputs, risk assessment, and the capacity to make independent technical decisions under pressure. These skills don’t show up on a LeetCode score.

The irony is that the very engineers companies need most are often screening out of traditional hiring pipelines, because they’ve spent recent years developing meta-skills rather than memorising framework internals.

Mistake two: Trusting language credentials over language capability

Vietnam’s tech talent market has a well-documented phenomenon I call the Paper Certificate Trap.

Language certifications, TOEIC 850+, JLPT N2, TOPIK 5, are treated as proxies for communication ability. In practice, they measure test-taking performance under controlled conditions. I have interviewed engineers with near-perfect TOEIC scores who go completely silent the moment a client asks a follow-up question in a technical meeting.

This matters because language ability is one of the strongest economic multipliers in Vietnam’s engineering market. Engineers with professional English (B2–C1), Japanese (N3–N1), or Korean (TOPIK 4–6) command salaries 30–50 per cent higher than peers with equivalent technical experience but limited to Vietnamese. A Senior AI/ML engineer with strong English can realistically earn US$3,800–US$6,000+ per month, a meaningful difference driven entirely by the ability to negotiate architecture directly with international clients.

Companies that can’t reliably identify genuine bilingual capability are paying a premium for a credential that doesn’t reflect reality, while missing engineers who have real cross-cultural communication skills but modest exam scores.

Also Read: Great talent is what happens after AI creates the first draft

What actually works

Move to skills-based sourcing

Replace credential screening with competency screening. Define the actual decisions and judgment calls the role requires, then design your process to surface those directly.

For senior roles in an Agentic Engineering environment, the relevant competencies are: Can this person write a system specification and defend it? Can they review a diff they didn’t write and identify the architectural implications? Can they set up a feedback loop between AI agents and quality gates?

None of these appears on a CV. All of them can be assessed in a structured technical conversation.

Implement live communication audits

For any role requiring cross-timezone collaboration or direct client contact, add a real-time communication component early in your process, not a written English test, but an actual technical conversation under mild pressure.

A 20-minute session where a candidate explains a system they’ve built, fields two or three unexpected questions, and works through a hypothetical trade-off out loud will reveal more than any certification score. Done well, this eliminates the majority of candidates who present strong paper credentials but lack genuine communication fluency, before you’ve invested weeks in technical rounds.

Match your hiring model to your actual risk profile

Not all talent gaps require the same solution, and the mid-2026 environment punishes generic approaches.

Early-stage teams prioritise flexibility over headcount permanence; access to senior expertise without long-term fixed cost is often more valuable than a full-time hire at a moment when product direction is still shifting. Growth-stage companies typically benefit from a hybrid structure: a stable core for culture and IP continuity, with flexible capacity to absorb demand spikes. Vietnam’s tech market has consistent biannual attrition cycles, with July historically the highest-churn month as mid-year reviews conclude and bonuses are paid, predictable volatility that hiring plans rarely account for.

Larger enterprises and foreign-invested companies face a different constraint: the gap between standing up a dedicated engineering function and actually integrating it. Whatever structure is chosen, the critical implementation principle is the same. Cultural and operational integration (shared tooling, CI/CD pipelines, daily standups) must begin from Day 1, not at the point of handover. Teams that delay this until a later phase consistently experience attrition at precisely the moment continuity matters most.

Also Read: Great talent is what happens after AI creates the first draft

The bigger picture

The scarcity that talent leaders are experiencing in 2026 is not a temporary supply shortage. It reflects a structural reclassification of what engineering capability means and a transition period where the market hasn’t yet developed reliable signals for identifying the new kind of engineer.

The companies that hire well in this environment will be the ones that invest in building those signals themselves: clearer definitions of what “decision-ready” means for their specific context, better processes for detecting genuine bilingual capability, and hiring models flexible enough to absorb the volatility of a market where the best people have more options than ever.

The companies that don’t will spend the next 18 months paying premium salaries for engineers who looked right on paper, watching their technical debt compound quietly in the background.

I’ve seen both outcomes. The difference is almost always made before the offer is signed.

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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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The post Vietnam’s tech talent market is broken and most companies are still hiring the wrong way appeared first on e27.

Thai founders sometimes ask why a Vietnamese startup with a comparable product or level of traction can appear to raise a larger funding round.

The answer is rarely that one startup is inherently better than the other.

Venture capital reflects the company being financed, but it also reflects the market surrounding it. Investors consider the size and growth of the domestic economy, the availability of follow-on capital and the likelihood of eventually selling their shares.

On these measures, Vietnam currently benefits from a stronger growth narrative.

This does not mean Vietnamese startups always raise more than Thai companies. Southeast Asian funding data remain incomplete, many transactions are undisclosed, and a few large deals can distort national totals.

But a broader distinction is visible: investors are often more willing to finance Vietnamese startups against expected growth. Thai founders are more frequently required to demonstrate regional scale before receiving comparable backing.

Investors price future growth

Venture capital is a wager on what a company could become several years from now.

That makes national economic expectations important, even when investors are evaluating an individual startup.

Vietnam’s economy expanded by 8 per cent in 2025, while the World Bank expects growth of 6.8 per cent in 2026. Thailand, by comparison, is expected to grow by about 1.6 per cent in 2026.

Economic growth does not determine whether a particular software, healthcare or logistics startup will succeed. But it affects the assumptions investors place around that company.

Vietnam offers a population of more than 100 million, rising household incomes, manufacturing expansion and growing demand for digital services. An investor can reasonably expect some companies to expand alongside the economy.

Thailand is wealthier and has stronger infrastructure in many areas. It is also home to sophisticated banks, retailers, telecommunications groups and industrial companies.

These are valuable assets for startups seeking customers and partnerships. But they can also make the venture case more difficult.

A Thai startup may need to displace established companies in a relatively mature market. A Vietnamese company may be able to grow by serving demand that is still being created.

As a result, the Vietnamese startup can sometimes receive more credit for future scale, even when the Thai company has stronger revenue today.

Also Read: Inside SEA’s AI gold rush: The 20 investors writing the biggest cheques

Market size changes the fundraising conversation

Vietnam’s population is significantly larger than Thailand’s. This gives consumer-facing companies a broader domestic market from which to build.

A Vietnamese startup can often present domestic expansion as a venture-scale opportunity. A Thai startup in the same category may be asked almost immediately about Indonesia, Vietnam, Malaysia or the Philippines.

Thailand’s market can produce substantial companies. But venture funds are not simply looking for good businesses. They need a small number of investments to generate unusually large returns across a portfolio in which many companies will fail.

This pushes investors towards businesses that can reach large markets.

For Thai founders, the result is an execution discount. Investors may believe that the domestic business is sound while assigning limited value to regional growth that has not yet been demonstrated.

This is why the first customer outside Thailand can matter so much. It shows that the company’s opportunity is not restricted by the size or maturity of its home market.

Capital follows other capital

The composition of the investor ecosystem also influences funding rounds.

Vietnam attracted nearly 150 active venture investors in 2024, according to the Vietnam Innovation and Private Capital Report. Funds from Singapore and Japan were among the most active international participants.

Funding remains difficult. Vietnamese technology startups experienced a sharp decline in investment after the global venture boom, and national private-capital figures often include large buyouts that are unrelated to early-stage startups.

The important point is not that Vietnam has unlimited capital. It is that a growing number of regional investors already include the country in their investment strategies.

Also Read: Inside Singapore’s startup boom: The 21 firms investors can’t stop funding

Venture capital depends on networks.

A seed investor wants to know who might lead the next round. A Series A investor considers whether growth funds will be available later. Every investor eventually asks who might acquire the company or purchase its shares.

When many funds already follow a market, investors know the potential co-investors, corporate buyers and later-stage funders. This makes rounds easier to assemble.

Thailand does not lack capital. It has independent funds, family offices, government programmes and a substantial corporate venture sector.

Large Thai companies can provide startups with distribution, customers, regulatory knowledge and technical expertise. Yet corporate venture capital is not always a substitute for independent institutional funding.

Corporate investors may prioritise strategic alignment over financial returns. They may avoid companies that compete with another group subsidiary or require several layers of internal approval before investing.

They may also be willing to join a round without leading it.

A lead investor sets the terms, conducts extensive due diligence and gives other investors confidence to participate. Without one, a startup may receive interest from several organisations but still fail to close a substantial round.

The shortage of investors able and willing to lead larger early-stage rounds remains one of Thailand’s most important financing constraints.

The exit question begins early

Founders often discuss exits as a distant issue. Investors consider them before making the first investment.

A venture fund earns its return when it can sell its shares through an acquisition, a secondary transaction or a public listing.

Thailand has a large stock exchange and some of Southeast Asia’s most powerful corporate groups. Yet the country has not developed a predictable exit path for venture-backed technology companies.

This can create a cycle.

Limited exits attract smaller funds. Smaller funds write smaller cheques. Startups then have less capital to expand regionally, making large exits even less likely.

Vietnam’s exit market is not mature either. Its improving public-market narrative does not yet provide a reliable listing route for technology startups.

However, Vietnam’s role in regional manufacturing, trade and supply chains gives strategic investors several reasons to acquire local technology, logistics and enterprise businesses.

Thailand has similar strengths in tourism, healthcare, food, energy, automotive manufacturing and services. The challenge is to connect these sectors to regional buyers rather than treating acquisition by a domestic conglomerate as the only possible outcome.

What Thai founders can control

Founders cannot change Thailand’s demographics, economic growth or fund structure. They can change how dependent their company appears to be on the domestic market.

Regional expansion must be presented as an operating plan, not a collection of flags in a pitch deck.

A Thai software company might follow an existing corporate client into Malaysia. A hospitality platform could expand through Thai hotel groups operating abroad. A healthcare startup could target countries with similar private hospital systems.

Internationally comparable metrics are also essential. Recurring revenue, retention, gross margin, customer acquisition costs and contribution margin help investors compare the company with businesses in other markets.

Thai founders should also approach regional investors before they urgently need capital. A fund that has followed a company for a year can evaluate its progress more confidently than one receiving a pitch shortly before the runway expires.

Most importantly, founders need to identify which investors can actually lead a round. Interest from corporate funds and smaller investors is useful, but it may not be enough to establish the valuation and bring the full syndicate together.

An expectations premium versus an execution discount

The difference between the two ecosystems is not that Vietnamese founders consistently build better companies.

Vietnam benefits from an expectations premium. Investors see a large market, faster economic growth and a growing network of international funds. They are sometimes willing to finance the scale a company may eventually achieve.

Thailand faces an execution discount. Startups are more often expected to show regional revenue, efficient economics and clear evidence that they can grow beyond the domestic market.

Both perceptions are incomplete. Vietnam remains exposed to trade disruption, regulatory risk and limited exits. Thailand has sophisticated infrastructure, strong corporations and real competitive advantages.

But investor narratives affect how capital is allocated.

Vietnamese startups can sometimes raise against the future investors expect their market to create. Thai founders are more often required to begin building that future before investors will pay for it.

—

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.

Join us on WhatsApp, Instagram, Facebook, X, and LinkedIn to stay connected.

The post Why investors often back Vietnamese startups more aggressively than Thai peers appeared first on e27.

Southeast Asia is in the midst of a workforce transformation paradox that has quietly become the region’s most pressing business challenge.

Governments have invested billions in upskilling initiatives. Singapore alone has trained over 555,000 workers through SkillsFuture programmes. Across the region—from Indonesia’s digital transformation drive to Vietnam’s emerging tech ecosystem—organisations are spending heavily on employee development. SMEs are sending their teams to AI courses, data science bootcamps, and digital literacy programmes. On paper, the workforce has never been better prepared.

Yet when these trained employees return to their jobs, something breaks.

The CEO who approved the training gets a report that the new “AI-capable” team member isn’t delivering AI-ready outputs. The employee who completed certification feels anxious despite their credential. The hiring manager who reviewed a resume with “AI Skills Certified” discovers during the onboarding period that the candidate struggles with real-world application. Nobody is lying. Everyone invested in good faith. But the signal—the credential—isn’t predicting actual capability.

This gap between certification and demonstrable capability has become the hidden cost of Southeast Asia’s digital transformation. And for SMEs, it’s catastrophic.

The training paradox: Credentials without capability

Here’s what the data reveals: training completion is not the same as job readiness. The distinction matters more than we’ve admitted.

Researchers across multiple industries have documented this phenomenon. Cloud Range’s 2025 research on technical workforce readiness is unambiguous: “Knowledge is what you learn. Readiness is what you can perform—and those are not the same. In a live incident, the difference between knowing what to do and being able to execute in real time under uncertainty is dramatic.”

This isn’t a criticism of training programmes. It’s a description of a fundamental gap between learning and performance.

Consider Google’s experience, documented by Cornerstone OnDemand. For years, the company screened job candidates using traditional credentials: transcripts, GPAs, test scores. After hiring thousands of people, Google researchers concluded these credentials were essentially “worthless” for predicting actual job performance. Only 43 per cent of workers in STEM roles even possess STEM degrees—yet those roles are filled nonetheless, suggesting that credentials and actual capability are loosely correlated at best.

In Southeast Asia, this gap has been replicated at scale. The SHRM Global Worker Project (2025) found that globally, 37 per cent of workers hold jobs that don’t align with their skills, while 53 per cent report their roles don’t match their education and training. But the regional data is more alarming: Singapore’s Ministry of Manpower and National Trades Union Congress (NTUC) study (2025) found that hiring challenges are increasingly driven by “skills specificity rather than qualification mismatches”—meaning employers aren’t struggling to find people with credentials; they’re struggling to find people with demonstrated expertise in the specific capability needed.

Translation: The credential exists. The capability doesn’t.

Also Read: “The AI did it” is not a defence; it is a confession

The hidden cost: What credential-capability mismatch actually costs

When certification becomes divorced from capability, three cascading problems emerge for organisations, particularly for resource-constrained SMEs.

• First, hiring decisions fail silently. An SME manager reviews a resume showing “AI Fundamentals Certified.” The hiring process validates the credential. The candidate onboards. Within weeks, the manager realises the person can apply frameworks in training conditions but freezes when facing real systems. The hire was made on a false signal—and SMEs, lacking large HR infrastructure, often don’t have backup plans or retraining budgets.
• Second, organisational anxiety increases. When 24.3 per cent of Singapore employers report experiencing skills gaps in their workforce, and 49.9 per cent report this causes increased workload for other staff, you’re describing a system where “trained” people can’t actually perform, forcing colleagues to compensate. The trained employee feels inadequate despite their certificate. Their manager feels misled by the training system. The organisation’s confidence in development programmes erodes.
• Third, competitive advantage evaporates. SMEs are racing to adopt AI to compete with larger rivals. But if their hiring signal—the credential—doesn’t predict whether someone can actually build AI systems, deploy models, or integrate AI into operations, they’re hiring randomly and hoping. In a competitive market, hope is a business risk.

This is where the problem reveals itself as a systems issue, not an individual or training-quality issue.

The signal integrity problem: Why credentials fail in APAC

Southeast Asia’s workforce development system has optimised for measurable completion metrics rather than capability verification:

What gets measured:

• Training volume (555,000 trained annually in Singapore alone)
• Certification completion rates
• Course quality and practical components

What doesn’t get measured:

• Can the certified person actually perform on the job?
• Do credentials predict job success, retention and performance?
• Is the certification signal reliable?

The result is a market-wide problem. When 16 per cent of specialised professional, manager, executive, and technician (PMET) roles in Singapore remain unfilled for six or more months, employers specifically cite difficulty finding people with demonstrated technical expertise—not people with credentials.

The credential system hasn’t failed because the training is poor. It’s failed because certifications and actual capability are being treated as equivalent when they’re not.

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The AI-powered enterprise solution: Bridging signal integrity

This is where AI-powered enterprise solutions become the game-changer for SMEs in Southeast Asia.

Traditional hiring systems can filter for credentials. They struggle to verify capability. AI-powered assessment platforms can do what neither training programmes nor conventional recruitment can: assess demonstrated capability—not just knowledge of frameworks—at scale and with consistency.

These solutions work by distinguishing between three different assessment layers:

• First, deterministic signals: Keyword and semantic analysis identify formal qualifications and technical vocabulary. Someone who says they “trained in Python” appears here. But this doesn’t prove they can debug production code under pressure.
• Second, semantic understanding: Advanced models evaluate whether someone can explain concepts in their own words, suggesting deeper comprehension than memorisation. This is closer to capability but still incomplete.
• Third, capability assessment: This is the layer most SMEs lack access to. AI-powered capability assessment goes deeper: Can this person actually do the work? Can they apply knowledge to novel problems? Can they integrate with existing systems? Will they perform in real conditions?

For SMEs, this third layer is transformative. A small team can now make hiring decisions with the same rigour a large enterprise could afford through expensive assessment centres. An SME can distinguish between “certified” and “actually capable” before hiring. They can identify which trained employees are genuinely ready for deployment in AI initiatives.

The competitive imperative for SMEs

SMEs in Southeast Asia face a unique time constraint. Larger competitors are adopting AI faster. Regulatory environments (EU AI Act, Japan’s ¥10 trillion Trustworthy AI 2030 mandate) are tightening requirements. The window to build AI-ready capability is closing.

But SMEs can’t afford to hire and fail repeatedly. They don’t have the budget to train an entire team, discover half aren’t capable, and retrain. They need to know, before hiring or promoting, whether their team members actually have the capability that their credentials claim.

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AI-powered enterprise assessment solutions solve this by:

• Reducing mis-hire costs: Verify capability before hiring, not after onboarding failure
• Optimising training ROI: Identify which trained employees are genuinely ready for deployment
• Accelerating AI adoption: Deploy capability with confidence rather than guessing
• Building organisational trust: When capabilities are verified, teams move faster and with less anxiety

The game-changer moment

We’re at an inflection point. Southeast Asia has solved the training problem—the region demonstrates this daily with millions of course completions. What remains unsolved is the verification problem: reliably determining who actually has capability versus who has certification.

SMEs that address this first—that adopt AI-powered enterprise solutions to verify demonstrated capability rather than relying on credentials—will outcompete peers who continue hiring blindly. They’ll deploy trained talent more effectively. They’ll build confidence in their teams. They’ll accelerate their competitive position.

The credential-capability gap that seemed like a training problem is actually an assessment and verification problem. And for the first time, AI-powered enterprise solutions make that verification affordable and scalable for organisations of any size.

That’s the game-changer Southeast Asian SMEs have been waiting for.

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The post The real workforce challenge: Bridging the credential-capability gap appeared first on e27.