Singapore-based healthtech startup Zeya Health has raised US$575,000 in pre-seed funding to expand its AI-native healthcare administration platform across the Asia-Pacific region.

The round was led by Antler, with participation from a group of strategic angel investors.

Also Read: Profit with purpose: Bridging the digital divide in healthcare

The funding comes amid mounting pressure on Southeast Asia’s healthcare systems. The regional healthcare market is projected to reach US$5 trillion by 2030; yet providers are grappling with a structural inflexion point marked by rising patient volumes, growing operational complexity, and an acute shortage of healthcare professionals.

Southeast Asia anticipates a shortage of 4.7 million healthcare workers by 2030, part of a global deficit nearing 10-18 million, driven by ageing populations and pandemics. Countries like Indonesia, Cambodia, Vietnam, and the Philippines have low doctor-to-patient ratios below 1 per 1,000, far under Singapore’s 2.46. This gap burdens low- and middle-income nations, prompting migration and tech interventions.

Founded to address this administrative capacity gap, Zeya Health offers an AI-powered front desk that integrates directly with existing Electronic Medical Record (EMR) systems and communication platforms such as WhatsApp. The solution automates routine but time-consuming tasks, including appointment reminders, follow-ups, and rescheduling, operating around the clock without requiring clinics to overhaul their core systems. According to the company, providers can go live in under 48 hours following a scan of existing workflows.

Since August, Zeya Health claims to have achieved over 20x growth in clinic onboarding and is sustaining a 2x month-on-month expansion rate. The startup is currently working with AcuMed, a leading healthcare provider in Singapore, to pilot its platform across a multi-clinic environment.

“From day zero, the Zeya team has executed with speed and discipline,” said Winnie Khoo, Partner at Antler. “They are addressing a deeply entrenched problem in healthcare: operational and administrative overhead while earning trust from providers who are cautious about adopting new systems.”

Zeya Health was co-founded by CEO Agastya Samat, who previously deployed digital health solutions for the UK’s National Health Service, and CTO Pasindu Wijesena, who founded his first AI startup five years before the launch of ChatGPT. “We’ve both seen firsthand how care teams end up spending more time fighting systems than caring for patients,” said Samat. “We started Zeya to remove that bottleneck, so providers can grow without burning out their teams.”

The startup currently serves healthcare providers across specialities such as physiotherapy, paediatrics, and primary care, and plans to expand into additional care models and regional markets in 2026.

The newly raised capital will be used for continued product development and scaled deployments across private healthcare providers in Singapore and the wider Asia-Pacific region. To support this growth, Zeya Health is actively hiring Forward Deployed Engineers and Clinical Deployment Specialists.

Also Read: The most-funded healthtech startups in Southeast Asia: A decade in review

Zeya Health’s approach aligns with a broader shift towards AI-enabled healthcare in Southeast Asia. AI revolutionises the region’s healthcare space by improving diagnostics, predicting patient deterioration, and enabling remote care to offset staff shortages. Success stories include Singapore’s Changi General Hospital using AI wearables for vital sign monitoring and complication prediction with over 90 per cent accuracy, Thailand’s Siriraj Hospital as a 5G AI smart hospital for diagnostics, and VinBrain’s DrAid X-ray tool deployed in 100+ hospitals regionally.

By positioning itself as a foundational AI layer rather than a replacement system, Zeya Health aims to help healthcare organisations scale sustainably without adding further complexity. In the company’s own framing, it acts as a “digital lubricant for the rusted gears of healthcare administration”, smoothing the friction of scheduling and paperwork so clinical teams can focus on patient care rather than process.

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Indonesia has taken another step towards institutionalising its digital asset market after the Financial Services Authority (OJK) officially granted a business licence to International Crypto Exchange (ICEx).

The licence was issued to ICEx’s operating entity, PT Fortune Integritas Mandiri. The approval positions ICEx as a key pillar in Indonesia’s evolving digital financial asset framework, which has seen crypto assets transition from commodity status to regulated financial instruments under OJK oversight.

Also Read: Southeast Asia’s crypto race heats up: Can Indonesia stay ahead?

The regulatory milestone is accompanied by a US$70 million strategic funding round, backed by a consortium of shareholders and industry players. Investors include PT Aethera Inovasi Digital, PT Finora Integrasi Nusantara, PT Regnum Sukses Utama, PT Volaris Visi Karya, and PT Vita Nova Global, alongside ecosystem participants such as FLOQ, Mobee, OSL Indonesia, Reku, Samuel Kripto, Tokocrypto, Triv, Upbit Indonesia, and Nanovest.

According to Pang Xue Kai, CEO of ICEx and founder and former CEO of Tokocrypto, the launch signals the country’s ambition to position itself as a hub for regulated digital assets. He stated that the exchange aims to deliver infrastructure that is inclusive, transparent, and aligned with institutional standards, thereby enabling healthy competition and sustainable innovation.

Beyond facilitating crypto trading, ICEx has been mandated to operate as a self-regulatory organisation (SRO). In this role, it will oversee trade reporting, market integrity monitoring, and member supervision, working closely with the OJK. Pang noted that this responsibility “reinforces public trust in the digital financial asset and crypto asset industry while opening space for innovation in new product development, including tokenised assets (RWA) and other regulated crypto products”.

Also Read: Indonesia’s digital index rises again, regional gaps narrow

From the regulator’s perspective, the introduction of additional exchanges is designed to strengthen the ecosystem. Hasan Fawzi, Executive Head of Financial Sector Technology Innovation, Digital Financial Assets, and Crypto Assets at OJK, said that having multiple licensed exchanges is essential for building a “healthier and more sustainable national ecosystem”. He added that the US$70 million capital injection reflects strong alignment between investors, regulators, and industry participants in balancing innovation with prudent supervision.

ICEx’s licensing comes amid rapid growth in Indonesia’s crypto market. As of October 2025, the country recorded 19.08 million crypto investors, representing roughly 6.7 to 6.9 per cent of its population of around 280 million. This marks a steady rise from an estimated 4.5 per cent adoption rate in 2021, driven largely by Millennials and Gen Z, who account for more than 60 per cent of users. Industry projections suggest the market could reach 25 to 27 million investors by the end of 2026, supported by high mobile and internet penetration.

The broader regulatory overhaul has also tightened compliance standards. Under OJK supervision, licensed platforms are subject to capital requirements, anti-money laundering controls, consumer protection rules, and restrictions on crypto usage as a payment instrument. OJK recognises 29 licensed platforms as of late 2025, with Indodax and Tokocrypto dominating by trading volume and user base. Other leading ones are Pintu, Upbit Indonesia, and Balderton Capital-backed Luno.

Also Read: Robinhood makes bold Indonesia bet as it acquires local brokerage and crypto trader

By combining regulatory authority with institutional funding and industry participation, ICEx is expected to play a central role in shaping Indonesia’s next phase of digital asset development. As Pang put it, the exchange intends to operate with “institutional integrity and in accordance with global standards”, marking what could be the beginning of a more mature and trusted era for Indonesia’s crypto markets.

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Markets opened the week on a note of cautious optimism, even as US exchanges remained shuttered for a holiday on January 12, 2026. The momentum carried over from the previous Friday, when the S&P 500 notched a record close at 6,966.28, buoyed by unexpectedly strong US jobs data that tempered fears of imminent and aggressive Federal Reserve rate cuts. That resilience in equities spilt into Asian trading hours, where regional benchmarks were poised to gain, reflecting renewed investor confidence in macroeconomic stability.

Geopolitical fault lines began to crack open beneath this surface calm. Escalating protests in Iran injected fresh volatility into commodity markets. Brent crude edged toward US$64 a barrel as supply disruption fears mounted, while gold, long the ultimate refuge in times of uncertainty, soared past US$4,563.61 per ounce, setting a new all-time high. The move underscored how even modest shifts in global risk perception can rapidly redirect capital flows toward safe-haven assets, especially when compounded by expectations of future monetary easing from the Fed.

Currency markets mirrored this tension. The US dollar softened notably after Federal Reserve Chair Jerome Powell disclosed that the central bank had received grand jury subpoenas from the Justice Department, a revelation that stirred unease about the Fed’s operational independence. Against this backdrop, the euro held steady near US$1.1635, while the Japanese yen slipped to its weakest level in a year, signalling divergent policy trajectories and shifting safe-haven dynamics.

Also Read: Wallets, not smart contracts, were crypto’s biggest risk in 2025

Meanwhile, the crypto market staged a modest but meaningful rebound, climbing 1.16 per cent over the past 24 hours. This advance marked a reversal of a broader 30-day downtrend and aligned with a nascent 7-day uptick of 0.17 per cent. Three converging forces drove this recovery: institutional validation through real-world asset tokenisation, technical breakthroughs on leading Layer 1 blockchains, and speculative optimism about potential US tax reform.

Ethereum and Solana emerged as clear leaders in the Layer 1 resurgence. Ethereum’s price action placed short sellers at heightened risk, with over 11 per cent of positions vulnerable, while Solana exhibited healthy alignment across exponential moving averages, a classic signal of sustained momentum. Together, they lifted the entire Layer 1 sector by 1.22 per cent, generating US$44.75 billion in trading volume, a staggering 66.34 per cent above the broader market average. This rotation into established, high-conviction assets suggested that investors were not chasing speculative narratives but rather reallocating toward foundational protocols with proven network effects and liquidity depth. The critical levels to watch now are Ethereum’s US$3,200 support and Solana’s US$140 resistance. Both will serve as barometers of whether this rally has staying power.

Equally significant was the Depository Trust & Clearing Corporation’s confirmation of progress in tokenising US Treasuries on the Canton Network. This development transcends mere technological experimentation. It represents a watershed moment in the integration of traditional finance with blockchain infrastructure. With US$300 billion in daily volume already flowing through Canton-based applications and the native token surging 13.27 per cent, the market interpreted this as a de-risking event. By anchoring sovereign-grade assets to a permissioned yet distributed ledger, institutions signal that blockchain is no longer a fringe experiment but a viable rails upgrade for core financial operations. Such validation compresses the perceived regulatory risk premium that has long shadowed crypto markets, potentially unlocking tranches of conservative capital that have been previously sidelined by compliance concerns.

Also Read: Crypto’s ticking time bomb: 5 events that will decide the 2026 bull run

Adding fuel to retail sentiment was unconfirmed but credible chatter from the White House about eliminating transaction-level taxes on cryptocurrency. Though legislative outcomes remain uncertain, the mere discussion shifted market psychology. The Fear & Greed Index climbed to 41, still in neutral territory but a marked improvement from last month’s reading of 29, which reflected deep-seated fear. If such reforms materialise, they could dramatically enhance crypto’s utility as a medium of exchange, moving it beyond speculation and into everyday economic activity.

Despite these tailwinds, participation remains restrained. Open interest across derivatives markets sits at US$600 billion, down 25 per cent from a month ago, indicating that traders are approaching this rally with discipline rather than exuberance. The absence of excessive leverage suggests that any pullback would likely be orderly rather than catastrophic.

In sum, the confluence of macro stability, geopolitical stress, institutional adoption, and regulatory hope has created a fragile but promising inflection point. The path forward hinges on two variables: whether Ethereum can defend its key support amid broader market volatility, and how quickly DTCC’s tokenisation initiative transitions from pilot to production. If both hold, this rebound may mark more than a technical bounce. It could signal the beginning of a new phase where crypto’s value proposition shifts from speculative yield to infrastructural utility.

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AI models are getting smarter by the week, but for most teams, the real struggle isn’t intelligence, it’s fragmentation. Too many tools, overlapping subscriptions, messy workflows, and no clear way to know what actually works.

In Part 1 of e27’s interview with Patrick Linden, co-founder of Iterative- and Antler-backed i10X, which enables users to access the world’s most powerful AI models through a single platform, we unpack why the Singapore-based startup is betting on a neutral AI meta-layer instead of building yet another model, how it crossed 100,000 users at pre-seed, and why retained, habitual usage — not hype — defines success in the next phase of AI adoption.

Excerpts:

AI tools are exploding everywhere. Why did you believe now was the moment to build a meta-layer instead of yet another model or agent?

Models are improving rapidly, but teams still lose time on the basics: identifying what works, integrating tools, and paying for too many overlapping subscriptions. We felt the bigger bottleneck was fragmentation, not raw intelligence.

Also Read: i10X nets US$1M to unify the world’s leading AI models

So we focused on a unified AI workspace: discover the right model or agent, use it in one place, and then connect agents into workflows as the next step. That’s also why our roadmap starts with Discovery (live) and moves to orchestration (what we call the “Agent Graph”) next, instead of trying to out-model the model providers.

At what point did you realise fragmentation, not intelligence, was the real bottleneck in AI adoption?

People weren’t blocked by “AI can’t do it”, but were blocked by:

• “Where do I even start to find what’s out there?” (too many agents, no trusted guide)
• “Which of the agents/tools actually works specifically for my needs?”
• Tool chaos and context switching
• Cost sprawl from lots of subscriptions.

Even the best models don’t help if the workflow is messy. That’s the problem we built around.

This is when realised fragmentation was the real bottleneck.

Many platforms aggregate models. What’s the most complex technical or operational problem i10X has solved that outsiders underestimate?

Aggregation is not the hard part. The hard part is making an all-in-one AI workspace really useful and reliable at scale, which includes:

• building out reliable cross-model and cross-agent memory so users don’t have to repeat context
• keeping the catalogue usable as the number of agents grows
• learning from real usage, which agent works best for a task in practice
• dynamically orchestrating the right agents/tools in our upcoming workflow engine.

If OpenAI, Anthropic, or Google were to build a unified workspace tomorrow, what would still protect i10X?

Two things: neutrality and breadth. i10X is built to help users pick the right agent for the job, not to push a single vendor’s ecosystem. Our ideal customer profile is SME owners, power users, founders and freelancers. Their goal is to find the best AI for a specific task, say a customer support chatbot or an AI sales development representative. They don’t really care in which ecosystem the solution lives. i10X sits as a neutral metalayer above individual ecosystems.

Also Read: The AI-first era: Why the model is the new runtime and how Asia can lead

Compounding usage data: Every task run in i10X teaches the Agent Graph what works best in which environment. That feedback loop improves results over time and is hard to copy without the same usage.

You’ve crossed 100,000 users at pre-seed. What metric matters more to you right now than user count? How much of that usage is habitual versus experimental, and what signals tell you i10X has become ‘mission-critical’?

We’re experiencing exponential growth in all key metrics across the board, including our paid user base. User count is nice, but we focus more on retained usage and repeat behaviour.

The metric that matters most is how many users return weekly and complete real tasks, not just browse. We look for signals like:

• repeat sessions without prompts from us
• users relying on i10X as their default place to try and run AI
• paid users staying even after the initial “AI exploration” phase
  teams consolidating multiple tools into one subscription.

What’s the most common reason users churn, and what does that reveal about the current limits of AI workspaces?

Our current churn rate is within industry standards, in line with the foundational model providers. It has improved by three times compared to where we started six months ago, mainly thanks to a laser focus on rapid improvements on the product side.

The most common churn is simple: some users come in expecting a single tool to instantly solve a vague problem. If they don’t have a clear use case, they won’t stick.

What that reveals about the current limits of AI workspaces is quite clear: the gap isn’t intelligence, but rather operational reliability – fast discovery, predictable outcomes, and an easy path from experimentation to daily use.

At US$25 a month, i10X is aggressively priced. Is this a wedge strategy or a long-term pricing belief? How do you prevent becoming a ‘thin-margin middleman’ between powerful AI providers and end users?

At US$25 per month, the intent is straightforward: make i10X an everyday “default tab”, not a high-friction procurement decision. So yes, it’s a wedge in the sense that it lowers adoption friction, but it’s also a long-term belief that AI should be priced like infrastructure, because it’s becoming part of daily work.

Also Read: The AI revolution in emerging markets: Local models, global impact

The “thin-margin middleman” framing doesn’t really fit i10X, because we’re not selling access to someone else’s product; we’re building the AI workspace where the user lives. The value compounds at that layer:

• We own the user relationship: users start with i10X to get work done; providers sit behind the interface.
• All in one space: discover, use, and orchestrate agents in a single workspace: one login, one subscription.
• Discovery that’s actually trusted: finding what works across all agents without trial-and-error.
• The Agent Graph: every task run improves indexing and recommendations, so results get better with usage.
• Workflow orchestration next: moving from “individual agents” to running repeatable multi-agent workflows.

Pricing stays simple: plans scale with credits and depth of access, and for B2B, we have seat-based pricing. The goal is strong unit economics from retention and consolidation, not from marking up tokens.

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The rise of deepfakes has evolved from a fringe technological curiosity to one of the most pressing cybersecurity concerns heading into 2026, according to new predictions from Kaspersky. As AI adoption accelerates across the Asia Pacific (APAC), the region is becoming both a proving ground for innovation and a testing arena for increasingly sophisticated cyber threats.

With 78 per cent of professionals in APAC using AI at least weekly, compared with 72 per cent globally, the scale and speed of adoption are amplifying the risks associated with synthetic content, forcing businesses and governments to rethink digital trust and resilience strategies now. For business owners and policymakers, this means prioritising AI risk assessments and embedding deepfake awareness into national and corporate cybersecurity roadmaps.

Deepfakes are no longer limited to manipulated videos of public figures; they are becoming a mainstream technology encountered by employees, consumers and organisations alike. Kaspersky notes that awareness of deepfake risks is growing, with companies increasingly training staff to recognise synthetic content and reduce the likelihood of fraud.

As deepfakes appear in more formats—video, images, voice and text—they are becoming a “stable element of the security agenda,” requiring structured policies rather than ad hoc responses. Leaders should respond by formalising internal training programmes, updating incident response plans and mandating verification processes for sensitive communications.

The threat is compounded by rapid improvements in deepfake quality and accessibility. While visual deepfakes are already highly convincing, Kaspersky predicts major advances in realistic audio, a key enabler of voice-based scams and impersonation fraud. At the same time, the barrier to entry is falling sharply, with non-experts now able to generate mid-quality deepfakes in just a few clicks.

Also Read: AI’s biggest bottleneck isn’t intelligence but fragmentation: i10X co-founder

This democratisation of creation tools means cybercriminals no longer need advanced skills to launch convincing attacks at scale. To counter this, organisations should invest in multi-factor authentication, out-of-band verification, and stricter approval workflows for financial and executive-level requests.

Efforts to label AI-generated content are expected to intensify in 2026, but progress remains uneven. There is still no unified or reliable system for identifying synthetic content, and existing labels can be easily removed or bypassed, particularly in open-source environments. As a result, Kaspersky anticipates new technical and regulatory initiatives aimed at addressing the challenge, though enforcement will lag behind innovation. Policymakers should collaborate across borders to establish minimum standards for AI content labelling, while businesses should not rely solely on labels and instead adopt layered detection and verification controls.

More advanced forms of deepfakes, such as real-time face and voice swapping, will continue to evolve, even if they remain tools for technically skilled attackers. While widespread use is unlikely in the near term, Kaspersky warns that risks will grow in targeted scenarios, including executive fraud, espionage and political manipulation. Increasing realism and the use of virtual cameras will make these attacks harder to detect and more persuasive. High-risk organisations should conduct threat modelling for targeted deepfake attacks and limit the public exposure of executive audio and video data wherever possible.

The growing use of open-weight AI models is also blurring the line between legitimate and malicious applications. As these models approach the capabilities of closed systems in cybersecurity-related tasks, they offer more opportunities for misuse due to weaker safeguards. At the same time, AI-generated phishing emails, fake websites, and synthetic brand assets are becoming increasingly indistinguishable from legitimate content, especially as companies themselves adopt AI in their marketing and communications. Businesses must strengthen brand protection, monitor for impersonation and educate customers on official communication channels to reduce fraud risks.

“Attackers are using it to automate attacks, exploit vulnerabilities, and create highly convincing fake content,” said Vladislav Tushkanov, research development group manager at Kaspersky. “At the same time, defenders are applying AI to scan systems, detect threats, and make faster, smarter decisions.”

Also Read: The ASEAN AI rush: Why “move fast and break things” is a dangerous strategy for risk

For the APAC region, the stakes are particularly high. “Asia Pacific is setting the global pace for AI adoption,” said Adrian Hia, managing director for Asia Pacific at Kaspersky. “This momentum is creating tremendous opportunity, but also redefining how cyber threats emerge and scale.”

As deepfakes cement their place as a top cybersecurity concern of 2026, resilience will depend on preparation rather than reaction.

Kaspersky recommends regular data backups, isolated from networks, and the use of advanced security platforms to detect and neutralise complex threats. These steps, which policymakers and business leaders alike must champion, are crucial to safeguarding trust in an AI-driven economy.

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The lead image in this article is AI-generated.

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The Southeast Asian startup ecosystem is currently experiencing a “Great Divide” in its capital allocation strategy.

While total regional funding saw a modest 7 per cent rise to US$5.2 billion in 2025, this growth was entirely top-heavy. As detailed in the “SEA Tech Annual Funding Report 2025” by Tracxn, late-stage funding witnessed a meteoric 194 per cent rise, reaching US$3.9 billion. This surge in the upper echelons of the market suggests that investors are doubling down on proven winners rather than betting on new ideas.

Also Read: Jakarta trails as Singapore tightens its grip on tech capital

Conversely, the environment for fledgling startups has become increasingly hostile. Seed-stage funding plummeted by 57 per cent to just US$214 million, while early-stage funding (Series A and B) dropped by 64 per cent to US$1.1 billion. This creates a precarious situation for the region’s innovation pipeline, as the foundation of the ecosystem is shrinking even as the top becomes more robust.

The data regarding “first-time funded” companies is particularly alarming for those hoping for a new wave of entrepreneurs. The number of companies receiving their first round of capital fell 62 per cent, from 283 in 2024 to just 107 in 2025. Investors are clearly operating with a “flight to quality” mindset, favouring companies with clear paths to profitability and established market presence.

This shift is further evidenced by the return of the mega-round. 2025 witnessed nine funding rounds of US$100 million or more, a slight increase from the seven seen in 2024. High-profile deals for firms like Airwallex, which raised US$330 million in a Series G round, and MiniMax, which secured US$300 million, have become the primary drivers of the region’s capital totals.

Also Read: From US$107M lows to a US$491M finish: SEA’s volatile 2025

The Southeast Asian funding landscape has evolved into a high-stakes arena where only those who have already breached the walls can find shelter, while the gates remain firmly shut for newcomers outside.

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Thailand has formally entered Southeast Asia’s high-stakes semiconductor race, unveiling its first national roadmap aimed at transforming the country from a backend electronics hub into a strategic producer of high-value chips over the next 25 years.

The roadmap, approved on Wednesday by the newly constituted National Semiconductor Board, chaired by Deputy Prime Minister and Finance Minister Ekniti Nitithanprapas, sets phased milestones for 2030, 2040, and 2050. At its core is an ambition to reposition the country as a critical node in the regional and global chip supply chain, moving decisively beyond basic assembly into design-led and upstream manufacturing.

Also Read: Spectral is breaking Nvidia’s monopoly — one line of CUDA code at a time

Competing and complementing Singapore and Malaysia

Thailand’s strategy places it in a complementary rather than confrontational position against regional leaders Singapore and Malaysia, both of which already occupy entrenched roles in the global semiconductor ecosystem.

Singapore commands roughly 10 per cent of global wafer fabrication and chip design, underpinned by world-class R&D infrastructure and deep integration with multinational firms. Malaysia, meanwhile, dominates the outsourced semiconductor assembly and testing (OSAT) segment, accounting for 13-15 per cent of global market share.

Thailand is charting a different course. Rather than directly competing in advanced front-end fabs or cutting-edge R&D, it is targeting power electronics, automotive semiconductors, sensors, analog, photonics and discrete chips. These segments are closely aligned with its existing industrial strengths in electric vehicles, medical devices, AI data centres and smart manufacturing.

Lower operating costs, aggressive incentives and specialised industrial clusters are expected to give Thailand an edge in mid-tier, high-growth segments.

The roadmap: From assembly to fabrication

The National Semiconductor Strategy is structured around five strategic pillars:

1. High-potential products: Prioritising power, sensor, photonics, analog and discrete chips critical to Thailand’s industrial base.
2. Short-term strengthening: Consolidating Thailand’s existing leadership in OSAT and integrated circuit (IC) design over the next five years.
3. Long-term upstream ambition: Gradually entering wafer fabrication, the most complex and capital-intensive stage of chipmaking, while nurturing “local champions” to reduce reliance on foreign technology.

Also Read: Asia rises in the AI chip race: China to outgrow US by 30 per cent by 2030

1. Talent development: Allocating billions of baht to workforce training, with targets ranging from 17,500 to over 200,000 engineers by 2030 through partnerships with global universities and industry.
2. Ecosystem building: Developing specialised semiconductor clusters in regions such as Lamphun and Lampang, backed by guaranteed clean energy, water security, streamlined regulations and semiconductor-specific trade agreements with the US, UK and EU.

The Board of Investment (BOI) is offering 15-year tax holidays, long-term low-interest financing, fast-track visas, land incentives within the Eastern Economic Corridor (EEC) and green-energy access via direct power purchase agreements. Around 70 semiconductor projects worth nearly THB 300 billion are already awaiting approval.

Why semiconductors matter to Thailand

Semiconductors are foundational to the country’s broader technology ambitions. Electronics already account for over 25 per cent of Thai exports, generating more than US$50 billion annually. As global supply chains realign– accelerated by US-China decoupling — Thailand sees chips as essential to sustaining growth and avoiding stagnation in traditional manufacturing.

Without deeper participation in semiconductors, Thailand risks being locked into low-margin assembly work while demand for chips surges across EVs, AI, IoT, data centres and advanced automation. The roadmap is also central to the government’s “Thailand 4.0” vision, which seeks to shift the economy toward innovation-led, high-value manufacturing and boost GDP growth to 2 per cent in 2026.

A sector on the rise

Thailand’s semiconductor and electronics sector has expanded rapidly over the past decade. The market grew from US$4.88 billion in 2023 to US$8.46 billion in 2025, and is projected to reach US$11.79 billion by 2030, with annual growth ranging between 7.6 and 20 per cent.

Also Read: Semiconductors at risk: The invisible threats that could break global supply chains

Between 2018 and late 2025, the country recorded 1,748 electronics investment applications worth THB 1.17 trillion (US$34.4 billion). Global heavyweights such as Infineon, NXP, Murata, Foxconn (Fiti) and others have expanded or established significant operations, reinforcing Thailand’s status as a key OSAT and automotive semiconductor hub.

The long game

While figures around US$73.5 billion in investment likely reflect broader multi-decade ambitions rather than near-term commitments, the intent is unmistakable. As BOI secretary general Narit Therdsteerasukdi noted, the semiconductor industry is on track to become a US$1 trillion global market by 2030, and Thailand intends to be more than a passive consumer.

Thailand’s journey is less about overtaking Singapore or Malaysia, and more about filling strategic gaps in Southeast Asia’s chip ecosystem. Like a master craftsman moving from assembly to design, the country is laying the groundwork to own more of the semiconductor value chain—patiently, pragmatically, and with an eye on long-term competitiveness.

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Rather than treating cloud spend as a back-office responsibility, leading organisations are starting to manage it as an operational discipline. This aligns teams around shared data, enabling clearer decisions on infrastructure, scaling, and performance and making cloud investments easier to forecast and optimise as the business grows.

Drawing from its work with enterprises across the region, Elite Cloud observes that multi-cloud adoption is accelerating faster than visibility and cost governance. As workloads spread across providers to support resilience, compliance, and performance, leadership often loses clarity on actual usage, cost drivers, and emerging inefficiencies.

While Elite Cloud’s cloud savings report is currently AWS-first, Elite Cloud already delivers end-to-end multi-cloud consulting, optimisation, and cloud operations across AWS, Google Cloud, Azure, Alibaba Cloud, and Tencent Cloud. This regional, provider-agnostic perspective reflects how ASEAN enterprises actually operate today.

In fast-growing markets, cloud visibility is central to resilience, forecasting, and operational control — but it is only the starting point. The real advantage comes when insight is translated into continuous optimisation. As a result, organisations can expand without cloud complexity becoming a drag on growth.

The new risks created by unseen cloud waste

The cloud computing market is predicted to surpass $1 trillion by 2028. (Source: Precedence Research). As ASEAN enterprises scale across multiple cloud platforms, inefficiencies often accumulate unnoticed, frequently driven by well-intentioned teams adopting tools and services in pursuit of productivity.

According to Flexera 2025 State of the Cloud Report, up to 30% of cloud spending is wasted each year. This includes money paid for idle or under-utilised resources that rarely deliver business value. This silent leakage quietly erodes margins. Meanwhile, cloud bills continue to grow, especially as organisations chase innovation and expansion.

Unpredictable billing compounds the problem. Without clear visibility into usage and cost drivers, engineering, finance, and leadership struggle to forecast budgets or align roadmaps. Leadership tightens controls, while teams lack the data needed to justify decisions, slowing progress on both sides.

Also read: Is the future of AI decentralised? Cloud computing holds the key

Why visibility is quickly becoming the backbone of cloud governance

For enterprises looking to expand across ASEAN markets, this is more than a back-office issue — it’s a strategic risk. When leaders can’t see what they’re spending or why, cloud waste becomes a barrier to disciplined growth.

Elite Cloud’s specialists see visibility as the practical starting point for disciplined cloud governance. True cloud cost visibility means a clear, shared view of cloud usage signals and corresponding costs across cloud environments. This eliminates blind spots created by fragmented dashboards and siloed teams. Rather than relying on retrospective billing reports, organisations need continuous insight to catch inefficiencies as they emerge. In short, enterprises need real-time awareness rather than annual reviews or manual audits that cost more time and resources to accomplish.

Elite Cloud applies AI-driven precision analysis to examine workload patterns across environments. It identifies idle or oversized resources and prioritising the highest-impact optimisation opportunities. Beyond cost optimisation, Elite Cloud also supports security posture checks with hundreds of checks. Thus, it helps teams prioritise high-risk and critical issues alongside efficiency improvements.

To help teams understand how optimisation translates into real outcomes, Elite Cloud surfaces a prioritised list of opportunities, with each recommendation tied to a specific action teams can implement.  But visibility alone isn’t enough. Real value comes from turning data into action so that engineering and finance can operate from the same data foundation with alignment. In practice, visibility becomes most useful when it clearly shows what can change. 

In a typical cloud diagnostic (results vary by environment and scope), Elite Cloud identifies an estimated 28.3% cost savings potential, or roughly US$24,800 in monthly savings, with clear attribution between pricing leverage and AI-driven optimisation. Drawing on insights from more than 2,000 client engagements, the company tailors savings reports that, in some cases, surface opportunities of up to 40%. Tracking these changes over time allows teams to see how cost structures evolve as inefficiencies are removed.

Also read: Coded in your DNA: How Singapore can help avert a global data storage crisis

How transparency strengthens competitiveness for fast-growing ASEAN enterprises

For fast-growing ASEAN enterprises, transparency becomes a competitive advantage when it translates directly into better decisions. Rather than applying blanket cost-cutting measures, Elite Cloud focuses on service-level optimisation. Each cloud service is reviewed individually to identify configuration or usage inefficiencies — whether that means rightsizing instances, changing instance families, applying scheduling policies, or tuning storage lifecycles — all without compromising performance.

Elite Cloud enables this by maintaining a detailed, time-stamped record of historical data and cloud activity across connected environments. This allows teams to analyse historical usage patterns and identify cost drivers with precision. This continuous logging and instant access to insights help organisations move beyond reactive cost reviews toward proactive optimisation.

Centralised visibility further reduces operational friction, especially for teams operating across markets. With shared insights and prioritised recommendations, teams can align on what to change first and implement improvements efficiently, lowering overhead and accelerating response times.

In fast-changing markets, disciplined cloud cost control becomes a form of strategic resilience. This is especially true when optimisation is embedded into day-to-day operations. Teams that operate from shared data can detect waste earlier and optimise without compromising performance.

Where Elite Cloud believes visibility-led cloud operations are heading next

In many organisations, leaders report that a significant portion of cloud spend feels wasted due to limited visibility and weak cost control. Addressing this requires solutions that surface usage patterns, cost drivers, anomalies, and optimisation opportunities in one place.

Elite Cloud’s specialised and contextual insights are designed to help organisations strengthen their cloud posture while reducing waste at the same time. The future of FinOps in ASEAN will rely on solutions that support continuous optimisation across both financial and operational risk, not just one-off cost-cutting.

At its core, Elite Cloud’s approach to smart cloud cost optimisation is about making every dollar work harder. By combining data-driven analysis with intelligent allocation and expert validation, organisations can reduce cloud spend while maximising return on infrastructure investments — without trading off performance, reliability, or security. To get started with understanding your cloud strategy, message Elite Cloud’s expert team and get your free cloud savings report.

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Southeast Asia and the Pacific region are at a critical juncture, facing unique challenges and immense innovation potential. For startups looking to build impactful and profitable ventures, focusing on problem-based solutions aligned with the UN Sustainable Development Goals (SDGs) offers a clear roadmap.

In 2026, the following 10 sectors present the most compelling opportunities.

The power of problem-based innovation

Instead of chasing fleeting trends, successful startups identify acute problems and build solutions. The SDGs provide a globally recognised framework for these problems, making them excellent targets for entrepreneurial ventures. This is not just a dry, academic-based assessment.

I live this experience daily, as I’ve spent 35 years in the region, starting, growing and exiting from 10 companies, before investing in 77 startups myself.

Top 10 SDG problem-based sector opportunities (Southeast Asia and Pacific – 2026)

• Sustainable aquaculture and ocean health (SDG 14: Life below water):

  • Problem: Overfishing, marine pollution, and unsustainable farming practices.

  • Opportunity: AI-driven precision aquaculture, sustainable feed alternatives, ocean plastics recycling tech, and mangrove restoration monitoring.

  • Actionable insight: Focus on scalable, low-cost monitoring solutions for small-scale fishers or developing alternative protein sources from sustainable marine resources.

• Resilient agri-food supply chains (SDG 2: Zero hunger and SDG 12: Responsible consumption):

  • Problem: Post-harvest loss, inefficient distribution, food waste, and climate vulnerability.

  • Opportunities: Cold chain logistics optimisation, farm-to-consumer digital platforms, food waste valorisation (upcycling), climate-resilient crop tech.

  • Actionable insight: Develop localised digital marketplaces connecting smallholder farmers directly to urban consumers, reducing intermediaries and waste.

• Decentralised renewable energy access (SDG 7: Affordable and clean energy):

  • Problem: Energy poverty in remote areas, grid instability, reliance on fossil fuels.

  • Opportunity: Microgrid solutions, pay-as-you-go solar for rural households, smart battery storage, ocean/hydrokinetic energy innovations.

  • Actionable insight: Focus on modular, easily deployable renewable energy kits for islands and remote villages, paired with innovative financing models.

Also Read: As the demand for energy soars, climate tech is here to save the day

• Circular economy for plastics and waste (SDG 12: Responsible consumption):

  • Problem: Massive plastic pollution, inadequate waste management infrastructure.

  • Opportunity: Advanced recycling technologies, alternative packaging materials (biodegradable/compostable), waste-to-energy solutions, and informal sector integration for waste collection.

  • Actionable insight: Create platforms that connect waste generators with recyclers, or develop localised micro-factories for upcycling plastic waste into valuable products.

• Nature-based climate adaptation (SDG 13: Climate action and SDG 15: Life on land):

  • Problem: Rising sea levels, extreme weather events, deforestation, and biodiversity loss.

  • Opportunity: Ecosystem restoration tech (e.g., coral, mangrove), early warning systems for natural disasters, sustainable land use planning, carbon sequestration solutions.

  • Actionable insight: Leverage satellite imagery and AI to monitor ecosystem health and identify critical areas for restoration or protection, offering this as a service to governments or NGOs.

• Inclusive digital healthcare (SDG 3: Good health and well-being):

  • Problem: Limited access to healthcare in rural areas, shortage of medical professionals, and high costs.

  • Opportunity: Telemedicine platforms, AI diagnostics for primary care, remote patient monitoring devices, and health literacy tools.

  • Actionable insight: Develop culturally sensitive mobile health applications that provide preventative care advice and connect patients in remote areas to medical consultations.

• Water security and sanitation (SDG 6: Clean water and sanitation):

  • Problem: Water scarcity, contaminated sources, inadequate sanitation infrastructure.

  • Opportunity: Smart water management systems, affordable water purification tech, decentralised sanitation solutions, wastewater treatment innovations.

  • Actionable insight: Focus on low-cost, decentralised water purification systems adaptable for community use in areas with poor water quality.

• Future of education and skills (SDG 4: Quality education):

  • Problem: Skill gaps, unequal access to quality education, and outdated curricula.

  • Opportunity: Personalised learning platforms, vocational training for green jobs, AR/VR for experiential learning, digital literacy tools for underserved communities.

  • Actionable insight: Create engaging, gamified learning modules focused on essential 21st-century skills and sustainability topics, accessible via low-bandwidth connections.

Also Read: How to tackle climate change by choosing a career in cleantech

• Sustainable urban mobility (SDG 11: Sustainable cities and communities):

  • Problem: Traffic congestion, air pollution, inefficient public transport.

  • Opportunity: Electric vehicle charging infrastructure, micro-mobility solutions (e-bikes, scooters), intelligent traffic management, last-mile delivery optimisation.

  • Actionable insight: Develop smart routing and demand-response platforms for public transport in rapidly growing secondary cities, reducing congestion and emissions.

• Financial inclusion and digital economy (SDG 8: Decent work and economic growth):

  • Problem: Lack of access to banking, credit, and digital payment systems for informal workers and rural populations.

  • Opportunity: Blockchain-based microfinance, digital wallets, identity verification for financial services, e-commerce platforms for local artisans.

  • Actionable insight: Build simple, secure digital payment solutions tailored for informal vendors and small businesses, enabling them to participate more fully in the digital economy.

Call to action

The problems are clear, and the opportunities for impactful innovation in SE Asia and the Pacific are immense. If you’re building a solution in any of these critical SDG-aligned sectors, let’s connect.

DM me to arrange a call to discuss how your startup can capitalise on these opportunities.

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Most founders start the day the same way: clearing emails in the morning, moving through back-to-back meetings by midday, and making dozens of small decisions in between. By the end of the day, the calendar is full and the inbox is quieter and yet, progress feels harder to point to. Time is spent coordinating, catching up, and reprocessing information rather than doing the work that actually moves the business forward.

For solo founders, project managers, marketing teams, and small business owners who spend most of their day inside Google Workspace, this pattern is familiar. The tools are there, but the work often feels heavier than it should.

AI is often positioned as the answer, yet many tools feel disconnected from how work actually happens. They sit outside existing workflows or require teams to adopt new platforms just to get started. What’s missing is context. This is where Gemini takes a different approach, bringing AI directly into the tools teams already rely on.

Google Workspace supports everyone from solo founders to 50-person teams who run their businesses inside Gmail, Docs, Sheets, and Meet every day. This article looks at how those teams are using Gemini within their existing Workspace tools to reduce everyday friction with practical examples that show how work can become clearer, faster, and more focused without changing how teams operate.

Context-based operations support with Gemini

Rather than introducing a new tool to learn, Gemini is built directly into Google Workspace, working inside the same Gmail, Docs, Sheets, Meet (and more) environments teams already use every day. The interface stays familiar, as do file access, permissions, and sharing rules. What changes is how quickly teams can move through information.

Within each Workspace app, Gemini appears in a side panel that provides quick summaries, drafts, and contextual help without pulling users out of their task. It can surface key points from long email threads, suggest first drafts in documents, or help organise information in spreadsheets—all while staying anchored to the work already in progress.

For questions that span multiple tools, the Gemini app adds a broader layer of context. It allows teams to connect information across Drive, Gmail, and Docs—such as locating a specific proposal and summarising related conversations—without manually searching through files or inboxes.

For deeper work, tools like NotebookLM and Google Vids extend this support further. NotebookLM helps teams synthesise research and internal documents into source-backed insights, while Google Vids makes it easier to turn ideas and presentations into simple video content. Together, these tools position Gemini as an integrated layer across Workspace, supporting day-to-day execution as well as moments that require deeper focus.

Also read: AI for SMEs: Indonesia and Google partner on Gemini Academy

Case study #1: Addressing email overwhelm and the endless inbox battle

For most teams, this shift becomes most visible in the place where work begins and ends each day: the inbox. You step out of a meeting to dozens of unread emails—clients waiting on updates, internal threads needing replies. Half an hour goes into catching up, another into drafting responses, and by lunch, little of the work that actually moves the business forward has started. For many founders and small teams, email has become a daily bottleneck.

Gmail with Gemini reduces that friction. Instead of scanning long threads, teams can use smart summaries to surface key decisions, action items, and open questions in seconds. A prompt like “Catch me up on the Project Atlas emails” highlights what matters, with links back to the source for quick verification.

When replies are needed, Gemini supports context-aware drafts that draw from past emails, Drive files, and recent meeting notes. Responses reflect existing communication styles and are grounded in the latest information, saving time without sacrificing clarity or tone. Priority emails are easier to manage as well, with intelligent labeling, reminders, and follow-ups helping important messages rise to the top.

The impact is practical. Customer-facing teams may reduce drafting time while staying responsive. For most teams, it starts small. They begin the day by asking Gemini to summarise emails by project, let it adapt response templates for client replies, and use the Gmail side panel to quickly check context from Drive and earlier conversations. 

Ready to conquer your inbox? Explore what Google Workspace with Gemini can do for you.

Case study # 2: This meeting should have been an email (or document)

However, much of what fills the inbox starts earlier during meetings.

The morning inbox often reflects what happened the day before. Many of the follow-up emails waiting for attention are the result of meetings where decisions weren’t clearly captured. What felt like a productive call at midday shows up the next morning as more work to untangle.

Back-to-back meetings are often the source of a good problem; high productivity means meeting targets in the long run. However, as modern work requires coordination between cross-border teams, there is a need for reduced friction in communicating. Teams need to be more effective in multi tasking notes, tracking action items, and capturing decisions in real time. This reduces the need for follow-ups, and ensures that everyone is on the same page with next steps.

Google Meet with Gemini helps to reduce this friction at the source. With “Take notes for me” enabled, Gemini automatically captures key discussion points as the meeting unfolds, highlights decisions, and identifies action items. Instead of raw transcripts, teams receive structured summaries that reflect what mattered without relying on one person’s notes.

These summaries are saved directly to Drive and easy to share. For remote teams, real-time translated captions, available across more than 60 languages, help ensure everyone has access to the same information, regardless of location or language.

Where Gemini’s value compounds is often seen after the meeting. Summaries can be referenced when drafting follow-up emails in Gmail or pulled into project updates in Docs, reducing repetition and preserving context across tools. The same information no longer needs to be retyped, re-explained, or reinterpreted. 

As a result, teams spend less time documenting and more time listening. Participants stay present in conversations, knowing decisions and next steps are being captured accurately. More importantly, fewer meetings are needed to revisit or clarify decisions.

Make every meeting count. Try Google Workspace with Gemini features today.

Case study # 3: Streamlining expansion without the learning curve

To stay ahead, founders often need to expand their client base to unknown territories. Researching a new market or vendor often turns into a pile of industry reports, docs, and links. It often slows teams down because relevant information is scattered across too many sources.

NotebookLM functions as a personal research workspace built around your own materials. It helps by understanding dense material and synthesising data into actionable insights. Teams can upload PDFs, Google Docs, Slides, and web links—bringing together internal strategy documents, market research, competitor information, and customer feedback in one place. Each source can handle large volumes of text, allowing teams to work with full reports rather than summaries or excerpts.

What sets NotebookLM apart is that it stays grounded in source material. Every response is generated strictly from the documents uploaded and includes citations that link back to the original source. This makes it easier to verify insights, trace decisions to evidence, and avoid “hallucinated” conclusions. 

Multiple sources (with the processing power of up to 500,000 words per source) can be referenced together, allowing teams to synthesize insights across documents without manually cross-checking. When reading isn’t practical, NotebookLM can take its findings and convert it into an audio overview which offers a way to absorb complex material on the move.

In practice, teams use NotebookLM to speed up decision-making. During strategic planning, financial reports and market analyses are distilled into clear summaries backed by data. For vendor evaluations, RFPs, pricing, and compliance documents can be compared side by side. Sales teams turn product documentation and competitor materials into clear positioning points tailored to specific customer segments. 

The shift is subtle but meaningful. Instead of spending days moving between documents, teams move more quickly from research to interpretation. Research moves faster and decisions are made with clearer reference to evidence without adding a new workflow or learning curve.

Also read: Architecting AI Factories to solve the enterprise data paradox

Addressing the invisible tax on modern work with real results

Small implementation efforts can compound into tangible real results down the line. The progress becomes tangible as AI is integrated over time to real workflows. 

This is where Gemini operates quietly within Google Workspace. It supports the repetitive parts of work—summarising threads, drafting first passes, organising notes, and carrying context across email, meetings, and documents—while leaving judgment, creativity, and decision-making firmly with the team. Everything remains reviewable and adjustable, functioning as a faster starting point rather than a final answer.

In practice, this approach has supported organisations operating at very different scales. In the Philippines, Google Workspace helped a regional convenience store chain expand rapidly during the pandemic, enabling remote training for over 1,000 workers, supporting far-flung communities, and improving operational efficiency.

Further, a large logistics and last-mile delivery provider uses Workspace to coordinate a 24/7 network across tens of thousands of employees, maintaining security while improving daily efficiency.

Finally, an agricultural technology and irrigation equipment manufacturer connected teams across rural regions, allowing faster coordination between field staff and leadership and enabling more timely support for farmers.

Across sectors, the pattern is consistent: when work is clearer and better connected, teams move faster with less friction.

Start tomorrow with a small step

Adopting AI does not require a big shift or a new way of working. It can start with something small and immediately useful.

Three Gemini prompts to try today

• In Gmail: “Summarise the emails from [client name] this week and highlight any action items.”
• In Docs: “Write a one-paragraph blog post introduction about the importance of productivity for small teams.”
• In Meet: During a meeting, turn on Take notes for me to automatically capture key points, decisions, and next steps.

Pay attention to what changes when you recover even 30 minutes of your day.

Over time, the teams that benefit most will be the ones that integrate AI thoughtfully, using it to support how they already operate rather than replace it. With Gemini built into Google Workspace, the work remains yours—only with less friction, clearer context, and more time to focus on what matters most.

Ready to supercharge your Workspace? Gemini is available to Google Workspace customers on the Starter, Standard, and Plus plans. For teams looking to experience Gemini fully integrated across Gmail, Docs, Sheets, Meet, Drive, and more, the Standard plan offers the most complete balance of features. Visit their website to upgrade or learn more.

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The e27 team produced this article sponsored by Commission Junction

We can share your story at e27 too! Engage the Southeast Asian tech ecosystem by bringing your story to the world. You can reach out to us here to get started.

Featured Image Credit: Google, Canva Images

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