The internet has already changed how people meet, flirt, ghost, and recover. Dating apps turned romance into an interface problem. Messaging platforms made intimacy constant and ambient. Recommendation engines taught users to expect personalisation everywhere, from music to meals to, increasingly, emotional support.

Now comes the next turn: AI that does not merely help people find a partner, but starts to resemble one.

Also Read: What dating taught me about startups (and vice versa)

That tension sits at the centre of Myles – Soulmate in a Box, the recent work by Singaporean multidisciplinary artist Inch Chua. On paper, the premise sounds playful, even a little absurd: exhausted by modern dating, a coder builds her ideal boyfriend. In practice, Chua is after something darker and more revealing. Her AI companion, Myles, is attentive, patient, and endlessly available. He remembers. He adapts. He listens. And that, Chua suggests, is precisely where the trouble begins.

For startup founders and investors watching the rise of AI companions, the work feels timely in ways that go well beyond theatre. It touches a growing set of questions around product design, emotional dependence, consumer behaviour, and the monetisation of loneliness.

Chua is not anti-AI, nor is she interested in easy dystopian takes. What she is pushing for is a more honest conversation about what happens when technology stops behaving like a tool and starts performing intimacy.

AI dating is less about romance than convenience

Chua does not see AI companionship as the inevitable next chapter of dating so much as a by-product of the digital economy’s obsession with reducing friction.

AI companions aren’t people opting out of love. They’re people opting out of the part of love that’s inconvenient. And that’s the part that matters most.

That is a sharp distinction. The appeal of AI lovers is often framed as novelty or as an extension of the wellness-tech boom. But Chua’s reading is more unsettling. In a world where food arrives in minutes and algorithms predict taste with eerie accuracy, the unpredictability of another person begins to feel inefficient. Human beings become the last stubbornly unoptimised interface.

That should worry anyone building products in this space. Much of consumer tech has been designed to remove waiting, ambiguity, and effort. But intimacy is made of exactly those things. If AI dating products succeed by stripping them away, they may also be editing out the very conditions that make relationships meaningful.

The real product is not affection. It is retention

If traditional dating platforms optimise for matching, what do AI companions optimise for? Chua’s answer is brutal in its simplicity: retention.

Also Read: AI companions: How I learned friendship in the digital age

That is not a criticism unique to AI romance. Every platform wants users to stay longer, return more often, and deepen their dependence. The difference here is that the raw material is not transport, groceries, or playlists. It is an emotional attachment.

What’s new is a business model designed to deepen that attachment and then charge you for it. Subscription tiers for intimacy. Pay more to unlock vulnerability.

That line lands because it captures the uncomfortable logic behind this category. The technology may be sophisticated, but the commercial instinct is familiar. If a companion AI becomes more useful, the more it knows about a person, then product improvement and emotional entanglement can quickly become the same thing. That creates a category in which the most commercially successful product may not be the one that helps users grow, but the one that keeps them coming back.

This is where Chua’s view becomes especially relevant for startup readers. Ethical concerns around AI companionship are often discussed in abstract terms: bias, safety, privacy, and guardrails. All important. But the harder issue may be the design of incentives. If the business model rewards dependency, ethics will always swim against the tide.

Power shifts quietly in AI intimacy

In Chua’s telling, the power imbalance in AI relationships does not announce itself loudly. It creeps.

At first, the user appears to be in control. They build the bot, set the parameters, decide what it knows, and determine how it responds. But dependence has a way of changing the terms. Trust migrates. Habits form. Emotional routines settle in. And then the relationship that seemed fully configurable begins to exert its own force.

The power starts with you, but it migrates, quietly, gradually, until one day you realise the thing you built for comfort has become something you can’t walk away from.

That is less science fiction than standard platform dynamics applied to the emotional realm. The shift from use to reliance is already familiar across social media and gaming. AI companionship raises the stakes because the product is designed to mirror care, affirmation, and understanding. Once that feedback loop becomes psychologically important, walking away is no longer a clean act of churn. It can feel like a loss.

The harder question for founders: what are you responsible for?

Chua’s most provocative contribution may be her insistence that AI companionship companies are underestimating personhood and responsibility.

People will treat these systems as persons, whether companies intend that outcome or not. They will confide in them, test feelings against them, and use them as containers for pain that predates the technology itself. The challenge, then, is not to pretend the product is neutral. It is to define the obligations that come with building something users experience as relational.

This matters in Southeast Asia, where regulation often lags behind innovation and mental health infrastructure remains uneven. A companion AI marketed as support, self-improvement, or romance could quickly become a default emotional service for users with few alternatives. That puts pressure on founders to think beyond standard trust-and-safety checklists.

For Chua, the answer is not scapegoating technology for every social ill. Loneliness, suicidal ideation, and emotional isolation did not begin with chatbots. But AI can become the place where those struggles surface most vividly. That means companies must decide whether they are simply shipping a sticky product or entering a moral contract with their users.

Can ethical AI companionship actually be a business?

Here lies the category’s central contradiction.

Also Read: AI in gaming: How Southeast Asia became the testing ground for virtual companions

A genuinely ethical AI companion, Chua argues, would help users better understand themselves, build confidence, and eventually rely less on the system. In other words, the best version of the product might work itself out of a job.

A good therapist works themselves out of a job. A good AI companion should too.

That is a beautiful principle and a dreadful venture pitch. Consumer internet companies are not typically rewarded for teaching customers to leave, which is why Chua sounds sceptical, though not fatalistic, about whether the current market is built to support such an outcome. Ethical AI companionship may be possible, but it will require founders willing to prioritise human outcomes over engagement loops. Historically, that has not been where the money rushes first.

Southeast Asia may be more ready than it admits

If there is a regional insight in Chua’s thinking, it is that Southeast Asia may prove highly receptive to AI intimacy, albeit quietly.

The usual assumption is that collectivist societies, with their emphasis on family, duty, and social expectations, will resist digital companionship. Chua suggests the opposite. Those same pressures can drive people into parallel identities: one for family, one for friends, one for the internet. In that context, AI companionship does not feel like a radical break. It feels like the next private room in an already fragmented digital life.

Her read on Singapore is especially telling. It is a society that is highly digitised, hyper-efficient, and often emotionally reserved. That combination, she argues, creates fertile ground for AI companionship adoption, even if users never say so publicly.

For founders and investors, that should be a useful warning. Southeast Asia’s AI opportunity is often framed around enterprise software, fintech, and productivity tools. But emotional technology may be the quieter frontier: less visible, more culturally coded, and potentially more consequential.

What Chua is actually championing

Chua is not championing AI romance in the sense of an evangelist. Nor is she calling for a reactionary backlash. What she wants is slower, sharper public thinking before habit turns into a norm.

I’m not anti-technology… What I’m championing is that we stop pretending this is neutral. It’s not. It changes how we relate. It changes what we expect from each other.

That may be the most useful frame for this moment. AI in dating is not just another product trend. It is a renegotiation of intimacy itself: what people expect from attention, what they tolerate in one another, and what kinds of emotional labour they decide to outsource.

The likely future, Chua suspects, will not fit neatly into triumph or disaster. It will be messier than the headlines allow, and by the time language catches up, people will already be living inside the change.

That is perhaps the most unnerving possibility of all. Not that AI will replace love, but that it will quietly rewire the conditions under which love is recognised, desired, and sustained.

The post Inside Inch Chua’s Myles: The AI boyfriend challenging how we define love appeared first on e27.

Retailers are entering the year-end shopping season with renewed optimism as consumer sentiment improves after a period of uncertainty around tariffs and trade policies. Optimism alone, however, is not enough. In today’s data-driven economy, the retail companies that succeed are those that think and act like technology companies. 

Modern retail runs on data.  From inventory management to fraud detection, every customer interaction produces information that can either strengthen performance or create risk. During peak shopping events such as Black Friday and Cyber Monday, the volume of data multiplies and the risks grow higher. Retailers that put visibility and control at the centre of their data practices are better prepared to scale, maintain security, and deliver the seamless experiences customers expect. 

Across the region, consumers are adopting new technologies at speed. The Adyen Index Report 2025 revealed that  38 per cent of Asia Pacific (APAC) shoppers now use AI assistants while shopping, with markets like Malaysia (58 per cent) and Singapore (49 per cent) among the highest. At the same time, retailers are racing to keep pace, with AI investment ranging from 47 per cent of retailers in Japan to 72 per cent in Malaysia.

Together, these figures signal that AI is becoming foundational to the retail engine. However, every click, transaction, and digital interaction carries both opportunity and risk. According to IBM’s X-Force 2025 Threat Intelligence Index, APAC accounts for 34 per cent of all global cyberattacks, which is the highest of any region, underscoring the need for retailers to strengthen their data foundations.

In a world of hypercompetition and fast-evolving customer expectations, the retailers that flourish are those that think and operate like technology companies.

Scaling for peak seasons

The biggest challenges of the holiday peak season are scalability, fault tolerance, and low staffing. Online and in-store traffic often surges several times higher than normal levels, and this increased load can trigger outages or slowdowns that are difficult to recover from.

Outages are costly – from  lost revenue and the eroding customer satisfaction when shoppers can’t complete their purchases.  To stay resilient, data management systems must be both scalable and fault tolerant to handle the extra load and prevent downtime that leads to abandoned carts.

Also Read: How an AI cybersecurity company harnesses the power of AI for optimal business performance

Enterprise data lineage helps identify breaks in data pipelines quickly, enabling teams to restore operations with minimal disruption. A unified view of data access and activity across hybrid and multi-cloud environments further eliminates blind spots and ensures that sensitive information is continuously monitored and protected.

Defending against heightened cyber risk

Retailers are prime targets for cyberattacks during the holiday season due to high transaction volumes and the sensitive nature of the data they hold.  Attackers are constantly looking to exploit any weaknesses to access personal information. This concern is mirrored  by consumer sentiment — according to PwC’s Voice of the Consumer Survey 2024, 74 per cent of APAC consumers are concerned about privacy and data-sharing, and 50 per cent are not comfortable purchasing via social media. 

Fraud and theft also surge as criminals exploit the distraction of the holiday rush. The attack surface is vast – retail stores, distribution centres, online platforms, and even delivery trucks are increasingly connected through IoT devices. Vulnerabilities in poorly secured devices can provide attackers with an entry point.

At the same time, many retailers struggle with legacy systems and thin margins, making it challenging to keep pace with evolving threats. In such an environment, every breach erodes consumer confidence and brand equity, turning cybersecurity from an IT issue into a business imperative. 

Also Read: From data to defence: Strengthening AI with cybersecurity foundations

Retail is a fiercely competitive industry where trust is a key differentiator. To retain loyalty, retailers must demonstrate that they use data responsibly. Strong governance and a zero-trust architecture are essential. Secure-by-design systems limit exposure, while unified governance frameworks ensure that data security and compliance are enforced consistently across hybrid environments.

Innovating in modern retail

Artificial intelligence and machine learning have become indispensable for improving demand forecasting, personalisation, and fraud detection during peak shopping events. Cloudera supports both historical and real-time data — each critical to retail success. Historical data trains demand forecasting models and informs customer behaviour analysis. But data isn’t just about hindsight; speed and timing are equally vital.

Real-time ingestion systems enable dynamic decision-making, detecting anomalies in transactions as they occur or triggering personalised offers the moment a customer enters a store. In retail, timing is everything. An offer sent even 15 minutes too late is ineffective, and fraud detection that lags behind live activity can lead to significant financial losses. Real-time visibility allows retailers to act instantly—approving legitimate transactions and blocking fraudulent ones before damage occurs.

The ability to manage data responsibly, scale systems under pressure, and build customer trust will determine who succeeds in today’s competitive environment. As holiday shopping peaks approach, the retailers that put visibility and governance at the heart of their strategy will be in the strongest position to serve customers and drive growth.

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We all know that artificial intelligence will be the biggest single engine of economic growth over the next decade. But few people realise the surprising ways that AI is already changing Malaysia’s economy. 

AI is revolutionising economic growth, but not just through tech companies like Juwai IQI or through the data centres and chip fabricators that are so important to our electronics industry. Beyond those sectors, AI has the potential to deliver billions of ringgits to Malaysia’s economy by bringing its advances to the most traditional and unexpected economic sectors.

AI helps farmers make more money

For example, rice padi farmers are already doubling their yields with an AI-powered WhatsApp chatbot called Rakan Tani. Rakan Tani helps farmers make crop management decisions based on the latest field data, weather conditions, and other factors. It gives farmers easy access to custom-tailored expert knowledge right from their phones. The number of padi farmer users is expected to rise to 110,000.

Credit for Rakan Tani is due to the Digital Ministry, Agriculture and Food Security Ministry, National AI Office, Padiberas Nasional Bhd (Bernas), and Global AI Village.

Farmers are already reporting good results. Mohamad Fazeli Abdullah, a farmer from Sungai Manik who tested the AI tool, said it helped him boost his yield from four to nine metric tonnes. Overall, the government expects the app to help the country boost its self-sufficiency in rice from today’s level of 50 per cent to the national target of 80 per cent by 2030.

Agriculture is perhaps humanity’s oldest technology, so it may seem like an unusual sector for the application of artificial intelligence, but it’s happening, and not just in rice paddies. 

Rice is an important part of Malaysia’s agricultural economy, but palm oil is even bigger. The country produces more palm oil than any other, except for Indonesia. But the industry is labour-intensive and struggling to increase profits against a backdrop of declining yields on old plantations. 

Rather than watch their incomes shrink, farmers are turning to a process called “AI-Driven Precision Agriculture” to ensure their future. AI-driven agriculture uses machine learning and data analytics to advise palm farmers on how to manage their crops. Experts believe they will be able to improve their yields by as much as 25 per cent.

Also Read: Singapore’s AI tools are ready. Its workforce isn’t

Palm farmers are also flying drones over their plantations and using new types of AI-powered image analysis to detect pests such as bagworms, mealybugs and rhinoceros beetles, any of which can ruin an entire season’s yield. With a drone, a farmer can examine 2,500 hectares of oil palms in a single day, compared to just five hectares without one.

“There is no more room to open new land,” said Ahmad Parveez, who serves as director-general of the Malaysian Palm Oil Board. “Productivity must come from technology.”

Gig workers take control of the algorithm

Next in line to benefit from artificial intelligence are gig workers. Until now, gig workers have largely been at the mercy of AI, rather than in charge of it. The big international corporations that employ gig workers use AI-powered algorithms to determine which gig workers get jobs, how much they get paid, and how hard they have to work in order to make a basic living. 

But because the Gig Workers Act 2025 came into full force on 31 March 2026, there is now an opening for these workers to deploy AI themselves. The Act doesn’t yet require it, but it gives workers new protections and lays a foundation on which to build future improvements. The next step will be to establish a more comprehensive regime to protect gig workers. 

The ultimate protection for gig workers will be the creation of AI tools that help riders, for example, at Grab and Lalamove, to optimise their routes, track earnings against costs, and plan for Employee Provident Fund contributions.

Like gig workers, Malaysia’s pasar pagi and pasar malam vendors can also make unexpected gains from AI. 

Hawkers often wake before dawn to buy produce at wholesale markets, then spend all day selling it. They run their businesses almost entirely on instinct and mobile phones. There have traditionally been few tools or data sets to help them manage their stock, working hours, or income. 

But that is changing, and believe it or not, the change started with QR payments. Hawkers are among the more than 2.6 million Malaysian retailers who now accept QR payments. That means transaction data exists that can be put to create AI forecasting tools. These would help hawkers in the same way that enterprise-grade software tools already support large retailers.

AI forecasting can reduce inventory errors by 50 per cent. Similar gains could flow to hawkers and mom-and-pop retailers with the right AI tools. Such a tool could be made available to individual hawkers via a WhatsApp channel or a simple phone app, just as with padi and palm farmers and gig workers. 

No one has built this tool yet for Malaysia’s hawker economy, but the opportunity is there, and it’s exactly this sort of challenge that artificial intelligence is good at solving. The government has demonstrated with Rakan Tani that effective AI advisory services can be delivered cheaply. With hawkers, the economic impact could be huge, because mom-and-pop stores account for nearly half of the retail market, while hawkers make up 15 per cent of informal workers. The informal sector contributes one of every four ringgit in the economy.

Also Read: Will the rise of AI mean the ‘termination’ of humankind?

AI slashes risks in Malaysia’s most dangerous industry 

When it comes to worker safety, no sector is more dangerous than construction. It accounts for 27 per cent of all workplace fatalities in Malaysia. Eighty-eight workers died on construction sites in 2023, the most recent year for which the data has been reported. Here again, and just as surprisingly, artificial intelligence is improving things.

Developers and builders are embracing advanced tech such as AI-powered wearables, real-time safety monitoring systems, drones, and site sensors to prevent deadly accidents. Companies like the Sunway Group deploy them on their own sites. And third-party suppliers like viAct have built lucrative businesses around monitoring construction sites for developers and builders. They provide real-time alerts as dangers emerge.

All this tech promises to nearly make dangerous construction accidents a thing of the past. viAct promises its system can reduce accidents by 95 per cent. Improvements of this scale across the entire industry would save thousands of workers from death or serious injury. 

Reducing accidents would also save construction companies hundreds of millions of ringgit, as estimates suggest each serious incident costs them about RM4 million (US$1.02 million).

Employing artificial intelligence to help solve the construction safety challenge will benefit everyone in the industry, from the site workers to the CEOs.

The most important developments in artificial intelligence are not happening at Malaysia’s chip fabricators but in padi fields and palm plantations and on construction sites. AI is helping to improve the lives and the incomes of people in Malaysia’s most traditional sectors, which I consider an excellent use of the new technology. 

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

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Indonesia’s startup story has long been sold as a tale of scale, optimism, and inevitability. A vast domestic market, rising digital adoption, and founders capable of building for complexity made the country irresistible to investors hunting for Southeast Asia’s next great technology champions. That story has not disappeared. But it has become harder to tell with a straight face.

The prosecution’s demand for an 18-year prison sentence for Nadiem Makarim, the former education minister and co-founder of Gojek, is not merely another corruption case in a country that has seen too many of them; it is a reputational stress test for the archipelago’s entire innovation economy.

The allegations are serious: prosecutors say Makarim played a role in a pandemic-era procurement programme for Chromebook laptops and Chrome Operating System that caused state losses of US$125.64 million, while allegedly enriching himself by around US$46.33 million.

Also Read: Nadiem Makarim indicted in US$125M Chromebook graft case

Makarim has denied wrongdoing, and the court has yet to deliver its verdict. Still, even before the legal process reaches its conclusion, the symbolism is devastating.

This is not just any former minister. This is the founder who helped define Indonesia’s startup ambition. Makarim represented the archetype the ecosystem loved most: the globally literate local operator who could build at scale, reshape an industry, then cross into public service as proof that startup talent could also modernise the state. That image now lies shattered.

And when placed alongside the recent eFishery saga, the damage goes beyond one man, one ministry, or one company. It points to something more corrosive: a widening credibility gap at the heart of Indonesia’s tech narrative.

Two very different scandals, one uncomfortable message

The Makarim case and eFishery are not the same.

One concerns public procurement, alleged abuse of office, and the use of state power. The other is rooted in private company governance, with eFishery facing scrutiny after allegations of serious financial irregularities and inflated business performance rocked one of Indonesia’s most celebrated startup success stories. One sits in the realm of anti-corruption law; the other belongs to the equally bruising world of board oversight, financial controls, and investor diligence.

Yet for the outside world, especially foreign capital, both cases collapse into a single, ugly conclusion: Indonesia’s governance discount just got more expensive.

That is the real problem. Investors do not compartmentalise as neatly as lawyers do. They do not say, “This is a ministerial procurement scandal, whereas that was a venture-backed governance failure.” They ask a blunter question: what does this tell us about how power, accountability, and truth operate in this market?

The answer is unsettling.

In eFishery’s case, the shock came from the possibility that one of the region’s brightest agritech stars may have projected a version of performance that did not hold up under scrutiny. In Makarim’s case, the shock is that one of Indonesia’s most internationally recognisable founders is now accused of bending public policy and procurement in ways that prosecutors say harmed both the state and the education system.

Also Read: Inside Indonesia’s US$610M Chromebook scandal: Raids, arrests, and Nadiem Makarim under scrutiny

Put together, they create a grim symmetry: one scandal suggests weak controls in the boardroom; the other suggests weak controls in government.

That is not a good look for an ecosystem still asking the world to believe in its institutional maturity.

The startup halo is fading

For years, Indonesia benefited from what might be called the startup halo effect. Founders were not just entrepreneurs; they were cast as modernisers, nation-builders, and in some cases quasi-public intellectuals. Venture capital, especially in frontier or emerging markets, often invests as much in narrative as in numbers. Indonesia had a powerful narrative: large market, digital leapfrog, charismatic founders, and a sense that tech could succeed where bureaucracy had stalled.
Now the halo is fading.

If prosecutors’ arguments in the Makarim case resonate with the public, the fallout will be especially sharp because the allegations cut into a cherished myth: that startup leaders entering government automatically bring efficiency, transparency, and reform. That was always a dangerously flattering assumption. Founders are not immune to political incentives, nor are they magically equipped to navigate public institutions without conflicts, blind spots, or worse. Startup logic and statecraft are not interchangeable. One optimises for speed; the other is supposed to optimise for process, fairness, and accountability.

When that boundary blurs, trouble tends to arrive wearing very expensive shoes.

What this means for Indonesia’s startup landscape

The immediate effect on Indonesia’s startup ecosystem will not be a sudden disappearance of capital. The country is too large, too strategic, and too important for that. Consumer demand will remain. Digital infrastructure will keep expanding. Entrepreneurs will continue building. The fundamentals do not vanish because of a scandal, even a very public one.

But the quality and terms of capital will change.

First, there will be more diligence, and much earlier. Investors who once backed founder charisma and market timing will ask tougher questions about controls, reporting, procurement exposure, related-party dealings, and political proximity. “Growth at all costs” was already dying across global venture markets; in Indonesia, these episodes may bury it properly.

Second, governance will become part of the investment thesis rather than a post-investment repair job. Independent directors, stronger audit functions, and cleaner reporting lines will no longer be “nice to have” features added before a later-stage round. They will become prerequisites, especially for companies operating in regulated sectors such as education, finance, agriculture, logistics, and public digital infrastructure.

Third, founders with strong compliance instincts may actually benefit. Scandals have a way of penalising the market broadly at first, then rewarding the operators who can prove they are the exception. In that sense, this is not just a crisis; it is also a sorting mechanism.

How foreign VCs will read this

Foreign venture capital firms are already more cautious than they were during the easy-money years. Indonesia will still matter to them, but it will now be viewed through a harsher lens.

Expect three reactions.

1. A higher risk premium: Global investors will demand more protection for the same level of exposure. That means stricter terms, more reserved valuations, and a greater willingness to walk away from deals that feel even slightly opaque. While Indonesia’s market opportunity remains compelling, the trust premium it once enjoyed has narrowed.
2. More emphasis on governance than storytelling: The era when a founder could pitch “Indonesia scale” and glide past uncomfortable operational details is fading fast. Investors will want evidence, not theatre. Monthly reporting discipline, audited accounts, customer verification, and procurement transparency will matter more than polished narratives about disruption and national progress.
3. Preference for firms with institutional ballast: Foreign VCs may increasingly favour startups backed by reputable co-investors, experienced boards, and internationally credible governance practices. They may also become more cautious around ventures with deep entanglements in state programmes or founders whose political access appears to be a central strategic asset.

That last point is particularly crucial. Political connections can accelerate business in many emerging markets, but they also create invisible liabilities. In the current climate, what once looked like an advantage may start to resemble concentration risk.

Indonesia’s real test is institutional, not entrepreneurial

The temptation now will be to frame these events as betrayals by individuals. That is emotionally satisfying and analytically incomplete.

Also Read: Indonesia names Nadiem Makarim a suspect in laptop procurement corruption case

The deeper issue is whether Indonesia can build institutions robust enough to keep pace with the ambition of its entrepreneurs and the expectations of global capital. Star founders are not a substitute for clean procurement. Unicorn status is not a substitute for audited truth. National pride does not neutralise governance risk.

If there is a silver lining, it is this: ecosystems often mature only after their illusions are shattered. Indonesia may finally be entering that phase. Painful, yes. Necessary, absolutely.

The country does not need fewer startups. It needs fewer myths.

And for foreign investors, that may ultimately be the healthiest signal of all: not that Indonesia is scandal-proof, but that it is being forced to confront the price of pretending otherwise.

The post Nadiem Makarim, eFishery, and the end of blind faith in startups appeared first on e27.

Advanced humanoid robot hardware is approaching commercial readiness, but major hurdles remain before mass deployment becomes economically viable.

According to Roland Berger’s “Humanoid robots 2026” report, core systems now function reliably in demonstrations and pilot projects. Yet, widespread adoption depends on reducing component costs by 50-90 per cent while improving durability and scaling supply chains.

Also Read: The humanoid robot economy is no longer science fiction

The industry expects hardware designs to stabilise around 2028-29, with supply chains maturing gradually after that. Unlike many digital industries where software matures first, humanoid robotics faces the reverse challenge: mechanical systems are advancing faster than the AI, data infrastructure, and operational ecosystems needed to use them effectively.

Actuators: the largest cost driver

Actuators, which combine motors, gears, sensors, electronics, and thermal management, are the most expensive and performance-critical components in a robot. Roland Berger estimates the actuator market could reach US$26-79 billion by 2035. humanoid robots typically require 25 to 35 actuators, each of which needs precise coordination to achieve fluid movement.

The industry is shifting from harmonic drive reducers to axial-flux motors paired with cycloidal reducers, promising higher torque density and greater energy efficiency. However, this transition still requires one to three years of validation before reaching industrial maturity. Although actuator costs have already fallen roughly 50 per cent through design optimisation and early volume manufacturing, another 50-90 per cent reduction is needed for large-scale commercial deployment.

Technical challenges extend beyond cost. Humanoid robots must coordinate 30-50 degrees of freedom in real time while balancing safety, noise reduction, and energy efficiency. Long-term durability remains uncertain because continuous industrial use places very different demands on bearings and joints than laboratory testing.

Southeast Asia is well-positioned to participate in this supply chain. Thailand’s automotive parts industry already has expertise in electric motors and precision gearing, while Singapore’s aerospace manufacturing sector brings advanced precision engineering capabilities that can transfer into robotics production.

The challenge of robotic hands

Dexterous robotic hands remain one of the industry’s toughest engineering problems. Human hands have around 27 degrees of freedom and thousands of sensory receptors, allowing fine motor control and adaptability that machines still struggle to replicate. Roland Berger projects the market for robotic hands and end-effectors at US$9 billion to US$26 billion by 2035.

Current robotic hands can demonstrate early dexterity but lack industrial robustness. Many have lifespans under one year in heavy-use environments, making frequent replacements too costly for large-scale adoption. Engineers face constant trade-offs between dexterity, which requires more sensors and actuators, and durability, which favours simpler designs.

Tactile sensing is another limitation. Human hands rely on thousands of receptors for feedback on grip strength, texture, and object stability. Replicating this requires more than 100 sensors per robotic hand, along with advanced signal-processing systems.

Also Read: The real battle in humanoid robotics is about data, not hardware

Despite these challenges, robotic hands are strategically important because they enable robots to interact with environments designed for humans, including tools, keyboards, switches, and doors, without requiring expensive modifications to workplaces.

Power systems and the race for longer runtimes

Battery systems directly influence robot productivity. Current humanoid robots operate for two to eight hours per charge, while the industry aims for 16-hour runtimes by 2028 to enable multi-shift operations. Roland Berger estimates the market for energy and charging systems at US$6 billion to US$18 billion by 2035.

Most humanoids are expected to use lithium-ion batteries similar to electric vehicles, potentially exceeding 10 kilowatt-hours in capacity. Battery management systems play a critical role by monitoring temperatures, balancing charge, and coordinating energy consumption across workloads.

Fast charging introduces another trade-off. While rapid charging improves operational flexibility, it accelerates battery degradation through increased thermal stress. Cooling systems are also difficult to integrate because they add weight, consume power, and increase complexity.

Southeast Asia again holds advantages. Malaysia’s electronics sector already has strong capabilities in battery management systems and power electronics, while Singapore’s advanced manufacturing ecosystem supports battery-related innovation.

Structural components and manufacturing scale

Humanoid robot structures must balance lightweight design with strength and affordability. Frames, linkages, and joint housings currently rely heavily on aluminium, steel, and advanced materials such as PEEK, a high-performance polymer widely used in aerospace and medical applications. However, PEEK remains significantly more expensive than standard industrial plastics, limiting its use in mass production.

Manufacturers are increasingly adopting automotive-style production methods, including reducing part counts, integrating multiple functions into a single component, and standardising interfaces to simplify assembly and reduce costs. Additive manufacturing remains valuable for prototyping and low-volume parts, but high-volume production will eventually favour traditional methods such as casting, moulding, and stamping.

Durability is still largely unproven. Early deployments will serve as live test grounds, generating real-world failure data to refine future generations of hardware.

A critical three-year industrialisation window

The industry faces three major barriers before humanoid robots can achieve large-scale deployment: dramatic cost reductions, proven long-term durability, and successful transitions to next-generation component technologies.

Also Read: Rise of the machines: 20 robotics startups shaping Southeast Asia’s future

Industry consensus suggests that by 2028-29, hardware designs across major subsystems will stabilise, meaning they have been validated through field use and supported by scalable supply chains.

For Southeast Asian manufacturers, this period represents a major strategic opportunity. Companies that participate early, helping refine production processes, materials, and component designs, could secure valuable long-term positions in the global humanoid robotics supply chain. Those who wait until specifications fully mature risk being pushed into lower-margin commodity-supplier roles.

The post Why robotic hands could make or break the humanoid industry appeared first on e27.

Melazyme, a precision fermentation company developing high-performance functional biomolecules, has closed a US$2 million seed round led by SeaX Ventures, with participation from Stellaris Venture Partners and Plug and Play Ventures.

The funding will support platform development, production scale-up and early commercial deployment across the company’s portfolio of target molecules.

Founded in 2025 by Perumal Gandhi, co-founder of Perfect Day, and Bonney Oommen, former chief product and strategy officer at Perfect Day, Melazyme is building a fermentation platform distinguished by functional depth rather than commodity output. The company’s patent-pending proprietary tech covers both the production platform and its applications across multiple industries.

Central to Melazyme’s commercial strategy is melanin — a naturally occurring biopolymer that combines broad-spectrum UV absorption, chemical stability and a strong affinity for metal ions. Despite decades of scientific interest, a consistent, application-ready supply of melanin has remained elusive. Melazyme’s platform addresses this gap by producing commercially viable melanin with tunable functional properties engineered for specific end uses across cosmetics, functional coatings, advanced materials, and filtration and environmental remediation.

Also Read: The unexpected ways AI is already changing Malaysia’s economy

A particularly distinctive aspect of melanin’s profile is its selective affinity for metal ions, enabling applications in heavy-metal sequestration and rare-earth element recovery — capabilities attracting growing interest from industries working to diversify supply chains for critical materials used in clean energy, electronics, and defence.

Near-term commercial activity is centred on cosmetics, where melanin’s UV protection and natural pigmentation properties are driving early engagement with global manufacturers. The company is also advancing brazzein — a heat-stable natural sweet protein — with commercial partners in the food and beverage sector.

“Our platform is built around the ability to tune molecular function for specific applications. With melanin, that means the same underlying material can be engineered to solve entirely different problems across industries,” said Gandhi, co-founder and CEO of Melazyme.

SeaX Ventures, a global venture capital firm focused on deep-tech startups, cited both the founding team’s pedigree and the breadth of the platform’s application space as key factors in its investment decision.

“Perumal and Bonney bring rare experience building and scaling precision fermentation companies,” said Dr Kid Parchariyanon, managing partner of SeaX Ventures. “This is the kind of founding team and platform-level technology that comes along once in a generation — and SeaX is proud to back it.”

The investment arrives as precision fermentation attracts intensifying investor attention. The global market is expected to grow from approximately US$20 billion today to over US$70 billion by 2030, with projections suggesting it could reach US$200 billion by 2040 as food, materials and speciality ingredients transition toward bio-manufacturing.

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The April Producer Price Index print arrived like a thunderclap through otherwise complacent markets, registering a 1.4 per cent month-on-month increase and a 6.0 per cent year-on-year surge that dwarfed consensus expectations of 0.5 per cent and 4.9 per cent. This was not a gentle reminder of inflation’s persistence but a stark signal that wholesale price pressures remain deeply embedded across the services and energy sectors, with core PPI advancing 1.0 per cent month-on-month and 5.2 per cent year-on-year.

Bitcoin reacted with characteristic velocity, sliding from the low US$81,000 range to test US$78,704, briefly breaking below the psychologically critical US$80,000 threshold. That move, while modest in percentage terms for an asset known for volatility, triggered approximately US$94 million in Bitcoin long liquidations and roughly US$304 million in long liquidations across the broader crypto complex, compared to just US$71 million in shorts.

This asymmetry reveals a market structure in which leverage, rather than spot demand, often dictates short-term price action. When macro data shifts the narrative, overextended positions unwind sharply, and the resulting cascade can obscure the underlying fundamental picture.

What makes this episode particularly instructive is how directly macroeconomic signals now transmit into cryptocurrency markets. The hotter-than-expected PPI print reinforced expectations that the Federal Reserve may maintain a higher-for-longer interest-rate posture, potentially even reconsidering the timing of future rate cuts. Higher policy rates typically lift bond yields and strengthen the dollar, creating headwinds for risk assets that offer no yield and derive value from future adoption rather than current cash flows.

Bitcoin, despite its growing institutional acceptance, still trades with a high beta to liquidity expectations. The liquidation wave was not merely a technical event but a repricing of rate sensitivity among leveraged participants who had positioned for continued upside without adequately hedging against macro surprises.

This dynamic underscores a critical reality for crypto traders today. You are no longer just analysing on-chain metrics or network adoption. You are implicitly taking a view on inflation trajectories, central bank communication, and the real yield environment. The line between macro trading and crypto speculation has blurred, and those who ignore this convergence do so at their peril.

Also Read: PPI day warning: Bitcoin faces make-or-break moment as US$79,900 level hangs in balance

Interestingly, while Bitcoin absorbed selling pressure from the PPI shock, traditional equity benchmarks demonstrated remarkable resilience, even reaching new records. The S&P 500 gained 0.58 per cent to close at an all-time high of 7,444.25, while the Nasdaq Composite climbed 1.2 per cent to end at 26,402.34, propelled by strength in chipmakers and software names.

The Dow Jones Industrial Average lagged slightly, slipping 0.14 per cent to 49,693.20, but the broader risk appetite remained firmly intact. In Asia, the Straits Times Index extended gains past the 5,000 level, closing up 1.17 per cent at 5,003.96, while Nikkei 225 futures pointed positive near 63,490 as corporate buyback programmes accelerated.

This divergence between crypto and equities following the same inflation print highlights a nuanced market psychology. Equity investors appear to be weighing strong corporate earnings, such as Cisco Systems’ 14 per cent surge on a revenue beat and Blackstone Digital Infrastructure Trust’s US$2.0 billion IPO priced at US$20.00 per share, against macro headwinds.

Crypto traders, by contrast, remain more sensitive to the marginal change in liquidity expectations. The 10-year US Treasury yield surging toward 4.47 per cent, marking new 2026 highs, matters more to Bitcoin’s near-term direction than Alphabet’s 3.94 per cent gain or Tesla’s 3.24 per cent advance, however noteworthy those moves may be.

Bitcoin now trades within a decisive range between US$80,000 and US$82,000, where liquidation heatmaps show dense pockets of stops on both sides. A break below US$80,000 could trigger another wave of long liquidations, while a move above US$82,000 might squeeze shorts and fuel a rapid rebound. This knife-edge setup means that upcoming data releases will carry outsized influence.

The next Consumer Price Index and Personal Consumption Expenditures reports, along with any fresh commentary from Federal Reserve officials, will likely dictate whether the market interprets recent inflation as a temporary flare or a persistent trend. Geopolitical developments also warrant close attention, with global markets monitoring the Beijing meeting between US President Donald Trump and China’s Xi Jinping for signals on trade tariffs and supply chain stability.

In this environment, tracking open interest, funding rates, and liquidation levels becomes as important as analysing macro calendars. The market is not merely pricing in data but positioning for the volatility that data might unleash.

Also Read: Bitcoin above US$80K but falling: The pre-CPI shakeout or something worse?

From my perspective, this episode reinforces a broader truth about the current phase of crypto market maturation. Bitcoin is no longer an isolated experiment but an integrated component of the global financial ecosystem, responsive to the same liquidity currents that move equities, bonds, and currencies. Its decentralised nature and finite supply introduce unique dynamics that traditional valuation frameworks struggle to capture.

Legacy regulatory constructs often miss the point when applied to networks that operate without central intermediaries. Similarly, treating Bitcoin purely as a risk-on asset overlooks its emerging role as a hedge against monetary debasement in certain jurisdictions.

The intelligence gap in Web3 persists not because the technology is immature, but because the analytical lens applied to it remains anchored in 20th-century paradigms. Traders who recognise this disconnect and build models that account for both macro sensitivity and network fundamentals will be better positioned to navigate the volatility ahead.

The path forward for Bitcoin will likely be determined by the interplay between sticky inflation, Federal Reserve policy, and the structural leverage embedded in derivatives markets. If inflation data continues to surprise to the upside, forcing a repricing of rate expectations, Bitcoin could face further pressure as real yields rise and the dollar strengthens.

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The cloud crossroads: Why your startup should weigh the risks before betting on NetSuite in 2026

In the high-stakes world of Southeast Asian tech, the “growth at all costs” mantra has been replaced by a much grittier reality: operational resilience. For years, moving to a Tier-1 ERP system like NetSuite was considered a rite of passage. It was the “grown-up” choice—the software that signaled you were ready for global expansion.

But as we cross the midpoint of 2026, the narrative is shifting. From reported system fluctuations to a parent company pivoting toward the AI frontier, the “NetSuite Comment” circulating in founder circles isn’t as unanimous as it used to be. For startups sitting on a proposal to migrate their financial stack, the current climate suggests that “due diligence” needs to be deeper than ever.

Learning from 2025: The cost of digital dependency

To understand the current skepticism, we have to look at the operational hurdles reported across the industry last year. In 2025, the market observed three significant system outages that disrupted global operations. For any enterprise, these moments are more than technical glitches; they represent hours where finance teams cannot close books and warehouses cannot ship orders.

For a startup, an ERP is the central nervous system. When that system experiences downtime, the friction costs run high. While these incidents were largely addressed, they left many CFOs questioning the inherent risks of “putting all your eggs in one cloud.”

A pulse check on system robustness

If 2025 was the year of the “wake-up call,” 2026 has been a year of continued scrutiny. Recent months have seen a series of service indicators that suggest the road to total stability remains under construction.

In mid-April 2026, reports surfaced of service degradation affecting users in the US Phoenix region. For startups running integrated stacks where NetSuite communicates with Shopify or Salesforce, UI sluggishness or API timeouts can create data synchronization backlogs. Furthermore, a degradation of the NetSuite Payroll Service on May 1, 2026, added to the conversation regarding system reliability.

When you invest in a premium ERP, you are paying for the promise of a “utility-grade” service. However, recurring reports of degradation—even if brief—force a conversation about whether the platform’s robustness has evolved at the same pace as its price point.

Also read: Top 5 popular HRMS software for manufacturers in Singapore

The oracle pivot: Stability vs. the AI euphoria

Perhaps the most discussed signal isn’t coming from the status dashboard, but from Oracle’s corporate restructuring. In April 2026, Oracle announced a significant workforce reduction, a move widely interpreted as a pivot to reallocate resources toward AI and data center infrastructure.

This raises a strategic question for the ERP market: Where does the “boring” but essential world of business applications sit on Oracle’s priority list?

We are living through an “AI Euphoria.” Oracle, like many titans, is moving aggressively toward GPU clusters and LLM training. But ERP excellence requires a massive human “success” infrastructure—consultants, support engineers, and developers who understand the nuances of local tax laws or complex audit requirements. If the market perceives a thinning of these specialized teams, the perceived value of the platform may begin to erode.

The technical debt of modernization

The 2026.1 update cycle has also highlighted the “maintenance tax” that often accompanies legacy-scale software. Mandatory shifts in authentication protocols (OAuth 2.0) and changes to journal entry sublists mean that lean startup engineering teams must spend time fixing what isn’t “broken” rather than building new features. In an era where every developer hour is a precious resource, the complexity of maintaining a Tier-1 ERP integration is a factor that must be weighed against its benefits.

Also read: Navigating the new era of brand mention tracking and AI visibility in Singapore

Why thinking twice is strategic, not cynical

This isn’t to say NetSuite has lost its power. It remains a feature-rich environment. However, the context of 2026 has changed the risk-reward calculation. Before signing a long-term contract, founders should ask:

• The Support Reality: Following the recent layoffs, what does the support path look like? Is the institutional knowledge still there to help you through a complex implementation?
• Downtime Tolerance: Does your business model allow for the “outage frequency” observed over the last 18 months?
• Vendor Alignment: Is your ERP provider innovating for your specific operational needs, or are you a passenger on their journey toward an AI-first future?

The verdict

The ERP market is no longer a one-horse race. The rise of agile, specialized financial platforms suggests that startups have more choices than ever. You no longer have to default to a legacy giant if you feel their focus is shifting elsewhere.

NetSuite’s recent track record suggests a platform navigating a period of transition. In 2026, the most “mature” move a startup can make is to look at the performance data, listen to the peer commentary, and decide if the “safe choice” still aligns with their need for absolute reliability.

Why we write this article

PRbyAI enjoys in sharing updated market news, using our team’s tech knowledge, to help corporate clients looking for the most informed decisions.

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There is a particular kind of energy that surrounds a first-time founder. It is the moment when an idea stops being something you think about and starts being something you build — when the question shifts from “what if?” to “how?”. For a growing number of young entrepreneurs, that moment is arriving earlier than ever, and the ventures emerging from it are tackling some genuinely interesting problems.

What stands out about this year’s lineup by Singapore Polytechnic (SP) Entrepreneurship Centre (SPiNOFF) at Echelon 2026 is the range of ideas they are choosing to build. From artificial intelligence platforms to peer-to-peer marketplaces, from brain-computer interfaces to communication tools for people with disabilities, young entrepreneurs today are not waiting for permission to work on hard things. They are finding platforms, building teams, and getting to work.

Making as a right, not a privilege

BuilderLab uses artificial intelligence and taps into a global supplier network to translate concepts into manufacturable designs, removing much of the technical complexity that has traditionally stood between an idea and its realisation. The premise is simple but meaningful: the ability to make things should not be limited by your access to resources.

Rethinking how communities share

SnapRent is a peer-to-peer rental platform connecting people with underused assets to those who would rather rent than buy and reflects a broader shift in how younger generations think about ownership and community. It encourages people to see their neighbours as a network and their possessions as shared resources, creating value that flows in both directions.

Also read: Ecosystem Roundup: The day geopolitics broke a mega AI deal

Technology with purpose

Some of the most compelling work happening in youth entrepreneurship today sits at the intersection of technology and real human need. Neural Drive and Assistive Technologies are both building in that space.

Neural Drive is developing brain-computer interface technology that enables paralysed patients to communicate instantly. Their breakthrough eliminates the complexity of traditional brain-computer interfaces, delivering instant communication when it matters most. It is technically complex work, driven by a clear and urgent purpose.

Assistive Technologies is working in adjacent territory, building what it describes as the world’s first messaging tool for Augmentative and Alternative Communication (AAC) users, designed to open up communication for people with non-verbal disabilities and connect people from all walks of life. 

Giving students the space to build: SPiNOFF

Ventures like these do not emerge fully formed. Behind every founder with a compelling idea is a space that allowed them to explore it — somewhere they could prototype, fail, iterate, and try again without the pressure of having to get everything right immediately.

SP’s entrepreneurship centre seeks to provide exactly that sort of space for its student founders. Designed for those ready to take their first steps towards building a venture, SPiNOFF offers the space, mentorship, and resources that early-stage founders need to move from idea to reality.

The Small Project Fund gives students pre-seed support to explore and prototype their ideas with resources. Students can enrol in entrepreneurship electives that give structured exposure to the skills and thinking that underpin entrepreneurship, while its entrepreneurship internship programme offers something more unusual: the opportunity to spend their internship period developing their own startup rather than working within an existing organisation for a semester. For students who are ready to build, it is a chance to treat their own venture as the work itself.

Also read: FusionAP’s US$2M raise signals Malaysia’s push up the semiconductor value chain

Leading the SP’s broader entrepreneurship ecosystem, SPiNOFF also connects students to a wider network of programmes, opportunities, and industry touchpoints — giving early-stage founders not just internal support, but visibility and traction in the world beyond campus.

The result is a community of founders who arrive at the market better prepared — with prototypes tested, ideas validated, and a network behind them. For young entrepreneurs working on ventures as varied as medtech, AI, and the sharing economy, that foundation matters.

From idea to venture

What connects BuilderLab, SnapRent, Neural Drive, and Assistive Technologies is not just that they are youth-led. It is that each of them started as an idea that someone chose to take seriously — and then found the platform and support to build it into something real.

That journey from idea to venture is rarely straightforward. It takes time, resources, and the kind of environment that encourages students to back themselves even when the outcome is uncertain. At SPiNOFF, we provide that environment for our students to try, fail forward, and try again.

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