Many Singapore companies offer a peculiar kind of workplace benefit: one that exists mostly in the HR handbook. Managers will tell you it is there. Employees, asked the same question, will tell you they have never come across it.

That gap sits at the centre of the Jobstreet by SEEK Singapore Workplace Culture Study 2026. The study was conducted by Milieu Insight among 600 employees and jobseekers and 200 hiring decision-makers. Half of employees (50 per cent) say they receive no organisational support at all to cope with always-on demands. Only 22 per cent of employers admit to offering none. That is a 28-percentage-point difference between the help bosses believe they provide and the help workers can actually find.

Also Read: Building burnout-resistant teams

Earlier instalments of e27’s reading of this study looked at why flexible work changed where Singaporeans work but not how much, and why 85 per cent of employers expect staff to stay reachable after hours. This one asks a simpler question: if the support exists, where is it?

The benefits nobody can find

The gap repeats itself in every type of support the study measured.

• Structured workload conversations: 40 per cent of employers say they hold them, but only 22 per cent of employees say they have had one.
• Boundary protections, such as rules that shield time off: 36 per cent of employers say they provide them, against 19 per cent of employees who notice them.
• Confidential feedback channels: just 13 per cent of employees know one exists.

There are two ways to read these numbers, and both are probably true. Some employers are being generous to themselves; the employer answers are self-reported, after all. Others may genuinely have the policies, but nobody has told staff about them, trained managers to use them, or made using them safe.

Either way, the effect on a worker staring at a 10pm message is the same. A boundary policy that nobody enforces is not a boundary. A workload conversation that never happens cannot redistribute any work.

Awareness is not the problem

What makes the gap hard to excuse is that employers are not in denial. Among those whose organisations expect always-on behaviour, 81 per cent recognise the long-term downside. Some 66 per cent say any short-term productivity gains come at the cost of eventual burnout.

Yet 48 per cent of those employers have no plans to introduce supportive policies. They can see the risk, and they have decided not to do anything about it.

Also Read: Burnout isn’t just personal, it’s becoming an operations problem

The budgets point the same way. AI and digital skills training tops employers’ investment priorities at 34 per cent. Workload management improvements attract 13 per cent, and extra hiring to ease the pressure just 12 per cent. In other words, Singapore companies are teaching staff to do more with better tools, not giving them less to do. As e27 noted earlier this week, employers are spending on the wrong fix.

Annual leave as a repair shop

When organisations do not build recovery into the working week, employees improvise. The study finds that 43 per cent of workers rely on taking leave to recover from always-on demands. Another 9 per cent say they lack the time or energy to recover at all.

That turns annual leave from a holiday into scheduled maintenance. It also means the cost of always-on culture is hidden from the people who could change it. Exhaustion does not show up on a dashboard as burnout; it shows up as a leave request, a quieter team member, or a resignation letter. Some 36 per cent of employees are already exploring new jobs because of wider workplace concerns.

The missing middle

If the policy exists at the top and the need exists at the bottom, the break is usually in between: the line manager. Research has repeatedly shown that the manager has an outsized effect on wellbeing at work, and this study puts a number on what happens when that link fails.

The report’s prescriptions are telling in how ordinary they are. It suggests managers hold explicit alignment conversations: rank the team’s priorities, agree on what counts as urgent, and set out who covers what outside working hours. It also recommends regular workload audits that force trade-offs whenever priorities change, so teams know what can be paused or dropped rather than simply added to the pile. Coverage handovers before leave would let staff actually switch off.

None of this costs much. Most of it costs nothing. That is precisely why its absence says so much. The obstacle is not money or knowledge; it is that nobody has been made responsible for doing it. Wellbeing strategies built around apps and webinars tend to fail for the same reason, which helps explain why corporate mental health efforts so often disappoint.

The problem is sharper for startups. Lean teams have no slack, and founders often double as the only managers, so the “missing middle” is the founder’s own calendar. Elsewhere in the region, workers are not waiting for HR. In the Philippines, where flexible work has become the price of talent, employees are already using AI as a burnout shield.

A caveat, and a test

The usual caution applies. This is a Singapore-only sample, employer responses are self-reported, and a jobs platform has an obvious interest in a restless workforce. The study’s categories are also loosely defined, so the exact size of each gap matters less than which way it points. And it points the same way every time.

Also Read: When AI takes your side in a workplace conflict

That suggests a simple test for any Singapore employer reading this. Ask your team, anonymously, which of your support policies they have used in the past six months. If the answer surprises you, you have just measured your own perception gap. Support that staff cannot see, or do not feel safe using, is not support.

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A Singaporean who will argue over a 50-cent difference in cashback at a hawker centre may have no idea what their savings account pays. New research suggests that person is the norm.

Some 89 per cent of Singapore residents hold spare cash, according to a survey of 1,000 people conducted by research firm Milieu. Among them, three in four do not believe that money is working as hard as it could. Only 11 per cent are very confident they know the interest rate their bank accounts pay.

Also Read: “Not a bank, not a gamble”: Chocolate Finance wants your business’s spare cash

The study was commissioned by Chocolate Finance, the cash management fintech founded by Singlife creator Walter de Oude. Chocolate Finance happens to launch a product in November that addresses the gap its research identifies. That does not make the numbers wrong. The fieldwork ran from 25 September to 5 October 2026 and carries a margin of error of plus or minus 3 per cent. But it is worth remembering who paid for the survey when reading what it concludes.

Points beat percentages

The most revealing finding concerns where people’s attention goes. Nearly half (48 per cent) of spare cash holders checked their cashback or reward points in the past six months. Only 37 per cent checked the interest rate on their spare cash. CPF balances, vouchers and promo codes all got more attention than savings rates.

The explanation is mostly about visibility. A discount shows up at checkout; points appear in an app with a satisfying ping. Interest builds up quietly in the background and rarely makes anyone feel clever. So a few dollars saved on a purchase gets more scrutiny than the return on a much larger pile of idle cash.

“People move their money around for an attractive welcome offer, but once that offer ends, the money often just sits there, earning very little,” de Oude said.

Spread too thin to see

Choice may be part of the problem. Singaporeans use an average of 3.7 banks and financial platforms, including incumbent banks, digital banks and wealth or cash management apps. Every new account promises a better rate. Together, they make it harder to know what any single pot is actually earning.

That is an awkward finding for an industry that has spent five years telling consumers they deserve more options. Singapore’s digital banks and wealth apps have fragmented the average saver’s money, but they have not made it any easier to understand.

Money without a job

The survey’s second theme is purpose. Some 72 per cent of spare cash holders describe their money as being for “one day, eventually”, or do not think about timing at all. Only 29 per cent sort all their money into clear categories.

When asked how they would behave if they could split spare cash into goal-based categories, 59 per cent said they would be more likely to leave the money untouched and let it grow. This is a statement of intent, not observed behaviour, and survey respondents are famously more disciplined in theory than in practice. Behavioural economists have long argued, though, that labelling money changes how people treat it, a habit known as mental accounting.

Also Read: Singaporean SMEs bleeding millions due to poor cash management

That is the thinking behind Jars, which Chocolate Finance will launch in November 2026. Customers will be able to divide their balance into pots for an emergency fund, a holiday or a home, each with its own purpose and timeframe.

The irony in the welcome offer

There is an irony in the pitch, and Chocolate Finance knows it better than anyone. The behaviour de Oude describes, money chasing visible perks, is exactly what nearly sank his company.

In March 2025, Chocolate Finance ended a popular feature that let users pay bills through payment services provider AXS, which many customers used to collect rewards. Within two weeks, about US$374 million was withdrawn, cutting its assets under management by some 40 per cent. Customers who had arrived for a perk left when the perk ended.

The company has rebuilt since then. It closed a US$15 million Series A+ round led by Nikko Asset Management and won a Hong Kong licence. By August 2026 it managed roughly US$1.3 billion for more than 150,000 customers, and it had expanded into business accounts with Chocolate Business. De Oude has also been open about that episode, telling the Echelon Singapore 2025 audience how the crisis reshaped the company.

Seen this way, Jars is as much a retention tool as a savings feature. Money that has been given a job is less likely to leave when a rival dangles a better welcome rate. That is good for savers who want discipline, and very good for a platform that once lost two-fifths of its assets in a fortnight.

A crowded jar shelf

Goal-based savings are not a new idea. Digital banks such as GXS have offered savings pockets since they launched. Wealth platforms, including Syfe, StashAway and Endowus, run cash management products that compete directly for the same idle money. StashAway is also widening its offer to keep customers for life, recently adding digital wills.

Chocolate Finance’s argument has never been about the headline rate alone. It points to its lack of lock-ins and fees, and to its top-up programme. There is also a structural difference consumers need to understand. Chocolate Finance is a licensed fund manager, not a bank. Customer money is invested in money market and short-duration bond funds held with third-party custodians, and it is not covered by Singapore’s deposit insurance scheme, which protects bank deposits. For the 89 per cent who are not fully sure what their accounts pay, that distinction is probably even less clear.

The question cuts both ways

The release ends by urging Singaporeans to ask whether their spare cash is “doing the job I need it to do”. That is a fair question, and the data suggests too few people ask it.

Also Read: How GXS relies on consumer insights and technology to drive digital banking innovation

It applies to platforms too. If savers are rarely checking their rates, then fintechs competing for that money owe them more transparency, not just more features. That means clear explanations of how returns are generated, what happens when markets wobble, and how quickly money comes back when it is needed. A jar is only useful if you can see what is inside it.

The post Points beat percentages: Why three in four Singaporeans think their spare cash is underperforming appeared first on e27.

Last week, Amazon was reported to be in talks to pay around US$7 billion for Decart, a three-year-old startup valued at just under US$4 billion in May. Cohere signed a letter of intent to buy AI security startup AISLE. Prime Intellect snapped up Moondream. Bumble agreed to a US$1.3 billion take-private. And that was a quiet week.

Rewind a few months and the numbers get silly. SpaceX bought Cursor for US$60 billion in stock, the priciest purchase of a private venture-backed startup ever. Nvidia paid US$12.9 billion for Hugging Face, roughly 26 times the offer Hugging Face had reportedly turned down earlier in the year. Crunchbase says the second quarter brought the most billion-dollar startup exits since 2021.

Also read: Southeast Asia’s biggest tech IPO of the year is a landlord

If you are a founder in Jakarta, Ho Chi Minh City or Kuala Lumpur, you are watching the greatest liquidity party in a generation through a window. You can see the champagne. You cannot hear the music.

The party, by the numbers

Tracxn counted 19 acquisitions of Southeast Asian tech companies in the first half of 2026, down from 34 a year earlier, plus just six IPOs. DealStreetAsia counted 41 tech M&A deals in the region over the same period, down 37 per cent, with only 14 VC- or PE-backed targets acquired.

Optimists point to exit value. Venture-backed SEA companies returned US$5.65 billion in exits in the first half, up from US$856 million a year earlier. But that money came from 12 exits. Fewer doors, bigger cheques, and most founders still standing in the corridor.

PitchBook put it bluntly earlier this year: the region’s problem is no longer deploying capital but getting it back out. And as e27 noted earlier this month, Southeast Asia’s most anticipated tech listing of the year turned out to be a landlord, not a consumer platform.

So the global market is minting AI exits at a record clip while SEA’s exit count falls. Those two facts are not unrelated.

What the buyers are actually buying

Look closely at the shopping list. Amazon wants Decart for software that lets AI models move between chips, which would help its own Trainium processors take on Nvidia. Nvidia bought Hugging Face because that is where developers show up before they ever touch Nvidia hardware. SpaceX bought Cursor’s distribution to expert software engineers.

The buyers are paying for chokepoints: compute efficiency, developer distribution and frontier talent. They are not paying for the application layer, the thin but useful products built on top of someone else’s model.

That application layer is where most of Southeast Asia’s AI startups live. Chatbots for SME customer service. Copilots for accountants. Vertical agents for logistics. These are real businesses solving real problems in Bahasa Indonesia, Thai and Tagalog. But to a hyperscaler in Seattle, they look like a feature the platform team can ship next quarter, or one the model lab will ship itself.

Even the region’s one AI mega-exit came with a return slip. Manus, the AI agent maker that moved from China to Singapore, sold to Meta for about US$2 billion in December 2025. Beijing ordered the deal undone in April. A Singapore address, it turns out, is not a clean title.

The consolation prize is a trap

When a full acquisition doesn’t come, Silicon Valley has a fallback: the licence-and-hire. The buyer takes the founders and key researchers, licenses the technology, and leaves the company standing. Nvidia’s reported talks with Reflection AI include exactly that option.

Also read: Manus came home, and Singapore couldn’t stop it

We now know how that story can end. In 2024, Google paid about US$2.7 billion in a deal that took Character.AI’s co-founders and dozens of staff back to Google. On 12 October, what was left of Character.AI filed for Chapter 11, with Disney’s US$20 million bid setting the floor for its assets.

Southeast Asia already runs a smaller version of this. DealStreetAsia found that tuck-ins and acqui-hires were what kept regional deals moving after valuations reset. That is fine for a founder who lands a job. It is less fine for the angel who wrote the first cheque, the employees holding options, and the LPs in Tokyo and Riyadh deciding whether SEA deserves a second fund.

An exit market that runs on acqui-hires is not an exit market. It is a recruitment agency with a cap table attached.

What the region should do instead

First, founders should stop assuming the American boom will trickle down. It won’t. Build for the buyers who actually exist. Circle’s planned US$400 million all-stock purchase of Singapore’s Tazapay last month is the template: a global player buying licensed cross-border payment rails it could not easily build itself. Regulated plumbing, local licences and messy multi-country compliance are moats a model lab cannot ship in a quarter. A clever prompt wrapper is not.

Second, take domestic listings seriously. The Philippine SEC has cleared GCash operator Mynt for an IPO of up to US$1.63 billion. India’s IPO boom shows how a deep home market can rewrite the exit playbook, with founders increasingly listing at home rather than in New York. SGX, IDX and Bursa will never be Nasdaq. They do need to become places where a US$300 million AI company can list without being ignored.

Third, policymakers have spent a decade paying for startups to be born: grants, sandboxes, matching funds. They have spent almost nothing on how startups end. Deeper secondary markets, friendlier tax treatment for early share sales and smoother cross-border mergers within ASEAN would do more for the next fund cycle than another innovation centre with a foosball table.

Also read: Character.ai was worth US$2.7B to Google. Disney just offered US$20M

Finally, investors should be honest with their LPs. If your SEA AI portfolio is mostly application-layer companies running on rented models, your exit thesis is a prayer. Price it that way.

The window won’t stay open

Booms end. Amazon, Nvidia and SpaceX will not keep paying 26 times their first offer forever. When the window shuts, it will shut on everyone, including the region that never got near it.

The question for Southeast Asia is not whether it can join this party. Mostly, it can’t. The question is whether it builds the companies, exchanges and rules to host its own next time.

Right now, we are still waiting outside, checking our phones, telling each other the music sounds great.

The post The AI exit window is wide open. Southeast Asia isn’t standing anywhere near it appeared first on e27.

Ibrahim Arief did not set out to found a legal tech startup. He set out to stay out of prison.

The former VP (Engineering) at Bukalapak, widely known as Ibam in the startup circle, is a defendant in Indonesia’s Chromebook procurement case, the graft prosecution that also ensnared former education minister and Gojek co-founder Nadiem Makarim. Facing a case file of roughly 5,000 documents and testimony from about 400 witnesses, Arief did what engineers do–he built a tool.

That tool is now Vindica.ai, a US-incorporated startup selling AI-powered fact-finding to defence teams during live trials. It has a paying client and raised a round of angel investment from a US-based investor. Its founder, meanwhile, is under city detention, has seen his sentence raised to five years by the Jakarta High Court, and is waiting on the Supreme Court.

Also Read: Why legal’s biggest AI problem isn’t technology

It is, to put it mildly, an unusual pitch deck.

The witness timeline that started it

The product moment, Arief told e27, came when a lawyer asked whether AI could produce a complete chronological list of every meeting a particular witness had attended, so the defence could question them methodically. Rebuilding that real timeline exposed how fluid Indonesian courtrooms are: witnesses appear at short notice, and others retract earlier statements mid-trial.

Most legal-tech, he argues, is built for pre-trial research, such as finding precedents, drafting and reviewing documents. Very little of it helps a defendant in real time, while testimony is still being given. Cross-examination of testimonies is one of the sharpest tools for testing the truth. It goes blunt when the questioner has no time to prepare. Untested testimony becomes “fact,” and untested facts produce questionable verdicts.

However, court notices often come less than 24 hours before the witness takes the stand. In that time, the defense must find the testimony buried in thousands of pages and cross-check it against every other witness. It must also trace its link to thousands of items of evidence.

So why not just use a general-purpose chatbot? Arief’s answer is personal. A co-defendant’s legal team, he says, once issued a press statement placing him at meetings in 2019 when he was not even in Indonesia. By his account, associates had fed court documents into a standard large language model, which cross-wired the facts. The error was corrected before trial, but the lesson stuck: in court, one invented fact can sink a defence’s credibility.

The wider profession has learnt this the hard way. In 2023, a US court sanctioned lawyers in Mata v. Avianca for filing a brief that cited cases ChatGPT had made up, and similar episodes have since surfaced in other jurisdictions.

A council of models that argue with each other

Vindica is engineered around that fear. Rather than relying on one model, it runs what Arief describes as a swarm of heterogeneous agentic models acting as an adversarial council: they investigate a query and confer over their findings. A separate auditor agent then checks every response against the primary source pages, using provenance embedded in the data.

Underneath sits a legal knowledge graph across the case documents, mapping how facts, parties and money flows connect. That, he says, is what lets Vindica trace risk across more than a million data points in a way a chat-style tool cannot.

The trade-off is speed. A deep query takes four to five minutes, and a 30-page witness analysis goes through about an hour of layered checking. Arief claims benchmarks such as the GDM-MRCRv2 shows that even leading models miss details 10 to 12 per cent of the time in very large contexts. Other benchmarks such as the AA Omniscience hallucination rate also show leading models tend to invent answers when they fail to find answers.

Language is the other hurdle. Global models, he says, handle Bahasa Indonesia poorly, especially messy courtroom speech and scanned files. Vindica uses ensembles that cross-correct transcription and OCR (optical character recognition) errors at every stage, and benchmarks itself against his own actual case files, alongside a custom mock case of around 2,000 pages. Legal-domain verification is led by his wife, who holds a Master’s in Law from the Netherlands.

Two dissents, then a longer sentence

Arief credits Vindica with helping his defence take apart hostile witnesses in real time. Some, he says, admitted in court to receiving bribes from vendors while trying to shift blame onto him as an external consultant, yet were treated only as witnesses, not suspects.

Also Read: Nadiem Makarim, eFishery, and the end of blind faith in startups

The May verdict was a rare 3-2 split, with two judges writing dissenting opinions arguing that Arief must be exonerated of all charges. Prosecutors had sought 15 years; the court handed down four. Arief says such dissents have been almost unheard of in major Indonesian cases over the past 15 to 20 years.

The High Court later added a year. Arief says Vindica has flagged irregularities in the verdict, which are now before the Supreme Court. Better fact-finding, it seems, can split a bench. It cannot promise an outcome. Makarim himself was sentenced to 10 years in June.

Arief also pointed to Tempo Magazine’s 2025 investigative coverage of extortion in major cases, which, according to the magazine, included the Chromebook procurement case, as an indication that his case is being used as leverage against a higher-profile figure, and he believes this is happening because that figure refused to pay the extortion demands. The person named in the Tempo coverage later appeared in the indictment of the former Deputy Attorney General for Special Crimes, from whom authorities seized 74 kilograms of gold and large sums of cash in July 2026, and whose trial for extortion and money laundering is ongoing.

Who it is built for

Vindica’s first client arrived by word of mouth before any formal launch: a high-profile case involving a former minister. Within days, the product was redeployed from Arief’s own prosecutor-led cases to the Corruption Eradication Commission’s (KPK) case against the former minister, without any major changes to the core engine. Arief said this adaptability is why he also sees potential uses in commercial arbitration and contract negotiation. He is adamant it assists lawyers rather than replacing them, since persuading judges remains a human job.

Asked whether he would license it to prosecutors, he went further: he would give it to them for free. Used early in investigations, he argues, it could expose gaps in the evidence and stop innocent people like himself from being indicted. He also said Vindica is planning to allocate part of its revenue to providing pro bono support for defendants who cannot afford large law firms, a promise worth watching, given that the revenue currently comes from well-funded defence teams.

On privacy, Vindica says all data at rest is hosted in Indonesia, in line with the country’s Personal Data Protection Law. Vindica runs regular security testing, only works with zero-training model providers where all data in transit for inference will not be used by third-parties to train their AI models, and the system runs strong multi tenant access controls. Vindica even supports on-premise deployments with local models and local inference clusters for clients desiring additional layers of privacy.

The competition is formidable. Harvey and Thomson Reuters’ CoCounsel have raised the bar for AI legal assistants, while LexisNexis has folded generative AI into Lexis+. 

Locally, Hukumonline dominates legal information. Most of these tools, however, are built for English-language research and drafting, not live criminal trials in Bahasa Indonesia. Vindica’s bet is that niche, and he claimed his AI can easily be extended to support other languages, though adoption across Asia still faces stubborn barriers of cost, trust and data security.

Key-person risk, engineered around

The obvious question for any investor is what happens if the founder goes to prison. Arief’s answer is structural. He holds no equity in Vindica; the US parent company is founded independently, which also gives the company a path into Singapore and Malaysia. He serves as founding engineer, owns the original intellectual property, and has granted Vindica an exclusive long-term license to his original IP. Everything Vindica develops after the date the license was granted belongs to Vindica as its own IP, while Arief receives royalties on Vindica’s gross revenue, which gives him skin in the game in lieu of the equity a founder would usually hold.

It is a clever arrangement, but not an airtight one. If the original IP sits with the founder, backers will want to know exactly how the company’s licence to it survives his absence. Arief argues that his absence will not revoke Vindica’s license, and that the company can continue to operate and grow even if the upcoming Supreme Court decision does not acquit him. Even so, he still believes an acquittal is a realistic possibility.

Also Read: Asia’s legal AI challenge isn’t tech; it’s talent and mindset

The personal cost is already steep. After more than a year with no income, Arief says he sold all the shares and savings he had built over 15 years to cover legal, medical, and living costs. Even if acquitted, he does not expect to recover them.

What the defendant’s chair taught him, he says, is something a decade of scaling engineering teams never did: when liberty is on the line, trust and credibility is not a feature. It is the product.

The post Ibrahim Arief is building a legal AI startup from city detention appeared first on e27.

In Thailand, many of the most visible startup investors carry the names of the country’s largest banks and business groups.

SCBX operates SCB 10X. Kasikornbank established Beacon Venture Capital. Bank of Ayudhya created Krungsri Finnovate, while Bangkok Bank has Bualuang Ventures. Investment vehicles linked to telecommunications, energy, retail and industrial groups extend the network further.

Corporate venture capital has shaped Thailand’s technology ecosystem for much of the past decade. A 2026 study commissioned by the Japan International Cooperation Agency found that nearly all companies in Thailand’s SET50 index had established either corporate venture arms or dedicated investment divisions.

As traditional venture funding becomes more selective, this structure gives corporate investors greater influence over which startups receive capital, gain access to major customers and find a possible path to acquisition.

For founders, the benefits are substantial. Corporate investors can provide customers, infrastructure, regulatory knowledge and distribution networks that financial investors cannot easily reproduce.

But this creates a tension. A traditional venture fund is primarily concerned with the value of the startup. A corporate investor must also consider the interests of its parent company. These objectives may remain aligned for years. They may also diverge when the startup wants to work with a competitor, expand into a different market or reject commercial terms that favour its shareholder.

Why corporate capital matters so much in Thailand

The model is particularly powerful in Thailand because large companies occupy influential positions across banking, telecommunications, retail, energy, manufacturing and logistics. A partnership with one corporate group can open access to customers, procurement budgets and infrastructure that would otherwise take years to reach.

For a fintech startup, a bank-backed investor may provide payment infrastructure, compliance expertise and access to institutional customers. An industrial group may offer factories, engineers and supply chains. A retail or telecom company may provide distribution to millions of users.

In a market where commercial adoption can be more difficult than product development, these assets may be worth more than the cheque itself.

The problem is that the same corporation may become investor, customer, distributor and potential buyer. That concentration can accelerate growth. It can also reduce the startup’s freedom to negotiate with the wider market.

Also Read: Your ESOP is a fundraising document. Most founders treat it as a HR perk

A shortage of independent alternatives

Thailand is not without venture capital. It has domestic funds, family offices, accelerators and access to regional investors. The difficulty is the limited depth of the market.

The JICA study identified a persistent funding gap between seed and Series A, as well as limited support for companies trying to move into later stages. This is particularly difficult for startups that have outgrown small early rounds but have not yet demonstrated the regional scale expected by international funds.

Corporate investors are well positioned to fill that gap. They have large balance sheets and strategic reasons to support technologies connected to their businesses.

However, corporate money is not always interchangeable with capital from an independent fund. Once a strategic shareholder enters the company, competing corporations may worry about conflicts of interest or information sharing. A startup backed by one bank may find other banks reluctant to become customers. A company closely associated with one conglomerate may face similar concerns elsewhere in its industry.

The investment may solve the immediate financing problem while making part of the remaining market harder to reach.

What CVC can deliver

Several of Thailand’s largest venture-backed companies have attracted significant corporate capital.

Flash Express has received investment from groups linked to SCBX, Krungsri and PTT. Ascend Money’s shareholders include CP Group, Ant Group, MUFG and Krungsri-related capital. LINE MAN Wongnai has also attracted backing from investors connected to telecommunications, banking and energy businesses.

The presence of these investors does not prove that corporate capital caused the companies’ success. It does show how closely the financing of major Thai technology companies is connected to established business groups.

The best corporate investors can shorten sales cycles, help startups meet the security requirements of large customers and provide access to senior decision-makers.

They also offer credibility. Large organisations are often cautious about buying from young companies because they worry about business continuity, data security and long-term support. Investment from a recognised institution can signal that the startup has passed serious financial and technical scrutiny.

But corporate patience has limits. A change in leadership, a restructuring or a reduction in innovation spending can weaken support quickly. The durability of the partnership depends on whether the startup remains important to the parent company’s strategy.

Also Read: Read the sectors, not the headline: What Singapore’s growth upgrade tells SEA founders

When alignment becomes dependence

The risks become clearer when the priorities of the investor begin shaping the startup.

A corporation may encourage a portfolio company to customise its technology for the parent group. This can generate revenue and provide a major reference customer. It can also consume resources that could have been used to build a product for a wider market.

Exclusivity presents an even greater risk. A corporate investor may request priority access to new products, favourable pricing or exclusive rights within a sector. Founders seeking both capital and a large customer may accept these conditions because the immediate benefits appear attractive.

The eventual cost may be substantial. The startup may gain an anchor customer while reducing its ability to work with competitors. Even without formal exclusivity, the market may begin to see the company as belonging to one corporate ecosystem.

Acquisition rights can create similar problems. Preferential negotiating rights or early access to information may give one shareholder an advantage over other buyers and reduce competitive tension in a future sale.

This matters in Thailand because exit options remain limited. When public listings and acquisitions are scarce, a corporate shareholder may become investor, customer and most likely buyer at the same time. That can provide a route to survival. It can also weaken the founder’s bargaining position.

Supporting or stalling the ecosystem?

There are two ways to view Thailand’s dependence on corporate venture capital.

The optimistic view is that CVC fills a genuine institutional gap. Corporate investors back companies that independent funds may consider too small, too local or too closely tied to regulated industries. Without them, fewer startups would receive capital or gain access to major customers.

The more critical view is that corporate dominance may slow the development of a deeper independent venture market. Strategic investors can justify an investment partly through the commercial value a startup may create for the parent company. A financial investor, focused mainly on returns, may reach a different valuation. This can create difficulties in later rounds, particularly if the startup remains dependent on contracts with its existing shareholder or has failed to expand beyond Thailand.

Both interpretations may be true. Corporate capital may be essential because independent financing is scarce. Its dominance may also make it harder for independent financing to develop.

Beyond the cheque

Corporate venture capital will remain central to Thailand’s startup ecosystem because it reflects the structure of the wider economy.

Banks and conglomerates control assets that young companies need. They can provide customers, distribution, expertise and infrastructure on a scale few independent investors can match.

But CVC should be judged by what happens after the investment. A successful partnership should help a startup win customers beyond the parent group, attract independent follow-on capital and expand across Southeast Asia.

Thailand needs corporate investors. It also needs companies capable of becoming independent from them.

The best corporate backer provides capital, customers and credibility while leaving the startup free to build a market beyond its sponsor.

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

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

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Image credit: Kristina Paukshtiteion

The post As venture funding retreats, Thailand’s corporate investors gain more power appeared first on e27.

For many companies expanding into Southeast Asia, hiring is no longer the hardest part. The bigger challenge is often what comes after: setting up a local entity, complying with employment regulations, running payroll and moving money across borders without unnecessary delays or excessive costs.

Singapore-headquartered TalentHero, co-founded by Oliver Lewis (CEO) and James Miles (COO), is looking to address these challenges through a new strategic joint venture in Thailand, alongside a proposed business partnership with Thai cross-border payments provider DeeMoney.

Also Read: 1982 Ventures joins Limited’s US$18.5M seed round to simplify cross-border business banking

The joint venture, established between TalentHero and Aswin Phlaphongphanich in his capacity as a private strategic investor, will focus on developing Employer of Record (EOR), recruitment, payroll administration and related workforce solutions for businesses operating in Thailand.

Separately, the new venture intends to explore payment partnerships, such as with DeeMoney, to support cross-border payments, international remittances and corporate payouts for its recruitment and EOR clients.

The agreement was signed in Bangkok on 2 October 2026, with Lewis and Miles representing TalentHero. Phlaphongphanich, who is also Co-Founder and CEO of DeeMoney, participated in his private investment capacity.

DeeMoney CFO Dylan Keota also attended, reflecting the parties’ intention to explore a commercial payments collaboration. The transaction was facilitated by Michael Gui, Partner at Copper Advisory.

At its core, the new venture targets a practical pain point. Companies want to hire in Thailand without necessarily establishing a Thai subsidiary from day one. At the same time, employers operating across multiple jurisdictions need reliable employment administration, payroll support and efficient payment processes.

“Building a team in a new market involves more than finding the right people. Employers also need reliable employment support and a practical way to manage payroll and payments,” said Lewis. “Through our new venture in Thailand, and by exploring commercial payment solutions with DeeMoney, we aim to make that journey simpler for businesses entering and growing in the market.”

Why EOR is becoming part of the expansion toolkit

Employer of Record, or EOR, has become a familiar model for startups and growth companies entering new markets. Under this arrangement, a business hires local employees through a third-party local employer, which handles employment administration, payroll and HR compliance. The client manages the employees’ day-to-day work, while the EOR handles the legal and administrative employment layer.

Also Read: TrueMoney and Fireblocks want Thai users on blockchain rails without them noticing

The model gained momentum during the remote-work boom, but its use in Southeast Asia is also tied to a more durable trend. Companies want to build distributed teams across multiple markets without carrying the cost and complexity of setting up local entities everywhere.

For Thailand, the proposition is timely. The country has long been a regional base for tourism, manufacturing, trade and services, but it is also positioning itself more strongly in digital industries. International companies entering the market need local hiring support, while Thai talent is increasingly part of regional and global teams.

TalentHero’s role in the joint venture will be to provide employment infrastructure and operational expertise. The company offers EOR, recruitment, global payroll and outsourcing services, combining talent acquisition with employment administration and operational support.

That matters because hiring is rarely a single transaction. A foreign company may first need to recruit a local country manager, then build a sales, operations or technical team, and later decide whether to incorporate locally. EOR can act as a bridge during that process, particularly for startups testing product-market fit or enterprises launching a regional function.

Where cross-border payments enter the picture

An additional opportunity being explored is the connection between employment services and international payment infrastructure.

DeeMoney, founded in 2017, specialises in international money transfers and cross-border payment services for individuals and businesses in Thailand.

Rather than participating as an equity shareholder in the new joint venture, DeeMoney is being considered as a separate commercial payments partner, with discussions focused on potential applications of its existing payment capabilities to the recruitment and EOR sectors.

These could include international remittances, cross-border business payments and payroll-related payout infrastructure, subject to applicable regulations, commercial arrangements and operational feasibility.

Thailand is both a destination and a source market for migrant workers, expatriates and regional business activity. For employees supporting families overseas, or companies managing payments to international contractors, suppliers or distributed teams, reliable payment infrastructure is an important operational consideration.

“Employment services and cross-border payments are closely connected, particularly for businesses operating internationally,” said Phlaphongphanich. “We see an opportunity to explore how DeeMoney’s established payment capabilities could complement TalentHero’s workforce solutions, helping businesses manage international payments more efficiently.”

The opportunity is not simply to offer more services under one roof. If commercially viable, closer coordination between employment administration, payroll processes and established international payment providers could reduce operational friction for companies building teams across Southeast Asia.

Any payment services arising from the proposed collaboration would remain subject to the relevant regulatory requirements and be delivered through appropriately licensed providers.

A crowded but growing market

The new venture will not be operating in an empty field. Globally, EOR and payroll platforms such as Deel, Remote and Oyster have built large businesses helping companies employ people across borders. In Asia, players including Multiplier and other HR-tech providers are competing to serve companies hiring across the region.

Also Read: Circle to acquire Tazapay for US$400M as USDC push moves into cross-border payments

On the payments side, DeeMoney operates in a similarly competitive landscape. Wise, Airwallex, Nium, Tranglo and traditional banks all serve parts of the cross-border payments market, while local fintechs and remittance providers compete on price, speed and coverage.

What could differentiate TalentHero’s new Thailand venture is the combination of international employment expertise, local market knowledge and potential access to established commercial payment infrastructure.

Global platforms often sell broad geographic coverage, but companies entering Thailand may still need local nuance. That includes employment administration, payroll timing, worker expectations, compliance processes and payment corridors that match actual business requirements.

Integration will nevertheless be important. EOR and recruitment are operationally demanding businesses, while international payments require appropriate licensing, risk controls and reliability. Any partnership must therefore balance customer convenience with regulatory compliance and operational effectiveness.

Thailand as a strategic growth market

For Southeast Asia’s startup ecosystem, TalentHero’s expansion reflects a broader shift in business infrastructure.

The first wave of digital tools helped companies sell online, communicate remotely and accept payments. The next wave is increasingly focused on essential operational functions: hiring, employment compliance, payroll administration and cross-border business payments.

Thailand offers an attractive environment for this approach. Its position within regional trade and investment flows, established industrial base and growing digital economy make it a relevant market for companies building international teams.

The joint venture also represents another step in TalentHero’s broader Southeast Asian expansion strategy, building on its existing regional operations and ambition to simplify international hiring and workforce management.

Also Read: Why investors often back Vietnamese startups more aggressively than Thai peers

For founders and operators, the appeal is straightforward. If they can enter a new market, hire efficiently, remain compliant and manage employment-related payments reliably, they can focus more resources on customers and growth.

The new Thailand venture is currently progressing through its establishment and operational preparations. The parties have not publicly disclosed its ownership structure or financial terms, and any commercial payment collaboration with DeeMoney remains subject to further discussions and applicable regulatory requirements.

As Southeast Asian businesses become increasingly regional, and international companies look deeper into the region for talent, employment infrastructure and cross-border payment services are becoming more interconnected.

Through its new Thailand venture, TalentHero aims to play a growing role in supporting that transition.

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Every few weeks, another report tells the same story about Southeast Asian tech: capital has fled, deals have dried up, and the region’s startup engine has stalled. The most recent numbers make the case forcefully. Zero dedicated regional private equity funds reached final close in the first half of 2026.

Three pan-Asian mega-funds — EQT, Blackstone, and Bain Capital — absorbed US$39.2 billion, or roughly 85 per cent of all Asia Pacific PE capital raised in that period. Regional tech funding had already fallen 79 per cent between 2022 and 2024, from US$10.1 billion to US$2.2 billion, and exit values dropped a further 32 per cent in 2025.

Read those figures and the conclusion writes itself: the building has stopped. But that conclusion only holds if institutional capital is still the right instrument for measuring who is building.

The concentration problem sits inside the AI number too

Even the one bright spot in the data is thinner than it looks. Southeast Asia’s AI startups raised US$4.1 billion in 2026 through July, more than double the US$2 billion raised in all of 2025. That sounds like recovery, until you notice that Kling AI’s single US$2.8 billion Series D accounts for about 68 per cent of it. Strip that one round out, and native AI companies across the entire region raised roughly US$1.3 billion this year — a real number, but not the turnaround the headline implies.

So the capital that does exist is concentrating twice over: regionally, into a handful of pan-Asian vehicles, and within Southeast Asia’s own AI sector, into a handful of outsized rounds. Both trends are true. Neither tells you much about whether people are actually building.

Also Read: Light liquidations and flat funding: Is Bitcoin about to explode?

A second economy isn’t showing up on any cap table

While institutional funding was contracting, a different kind of activity was compounding. The market for AI-assisted, natural-language software building — often called vibe coding — is now estimated at US$4.7 billion and growing at roughly 38 per cent a year, with 63 per cent of active users being non-developers rather than trained engineers. The same reporting puts the typical span from a first idea to a paying customer at about four weeks — a cycle that requires no seed round, no pitch deck, and no line item in any PE report.

This is not a story about tools making bad builders look competent. It is a story about who gets to start. A product manager, a designer, or, increasingly, someone with no formal technical training at all can now ship and monetise a working product inside a month, entirely outside the instruments used to track “the startup ecosystem.” None of that activity registers as a data point in the reports currently used to declare the region’s tech sector shrinking.

I can speak to this from experience. I came up through the Normal Technical stream at school rather than a computer science degree, and spent years working as a paramedic before I started building software by prompting. What began as one product, a consumer signal-intelligence platform under construction at OnTheRice, eventually led to a board and product-architecture role at SCAVerse, a Singapore culture-tech venture.It does not counter the funding data. It is one example of a pattern those figures can’t capture: builders who exist before, and sometimes without, a term sheet.

The asymmetry now being closed isn’t only between founders

The same shift is playing out one level down, between institutions and the consumers those institutions serve. The AI consumer insights market is projected to grow from US$5.3 billion in 2026 to US$12.15 billion by 2034, with retail and e-commerce applications already accounting for about 45 per cent of that spend. What that money is buying, in practice, is the ability to point institutional-grade pattern recognition — the kind previously reserved for analyst desks and trading terminals — at ordinary consumer decisions: what a price move actually means, which claim in a press release holds up, which trend is a signal and which is noise.

Also Read: A funding round can improve your metrics without improving your company

Historically, that gap belonged to whoever could afford a terminal, an analyst, or a research subscription. It is the same gap that separated a funded founder from an unfunded one. Both are narrowing for the same reason: the cost of building serious analytical tooling has fallen faster than the institutions measuring “innovation” have updated their instruments.

Why this matters more than the funding headlines

If the only lens applied to Southeast Asia’s tech health is PE fund closes and disclosed equity rounds, the region will keep reading itself as being in retreat, even as real building activity — by non-traditional founders, using AI-native tools, serving consumers directly — may be at a multi-year high. That mismatch has consequences. Policymakers calibrate support programmes off these numbers. Investors calibrate conviction off them. A region that under-counts its own builders risks under-investing in exactly the layer where its next founders are already working.

The instruments didn’t just miss the recovery. They may be measuring an economy that is quietly becoming smaller than the one actually running underneath it — and the builders who never needed a term sheet to start are not going to wait for the definition to catch up.

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

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

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Here is an uncomfortable finding for anyone building a 2027 marketing plan this month: audiences are warming to advertising, and marketers are growing less sure that theirs works.

That tension sits at the centre of Kantar’s Media Reactions study, published on 2 October and based on interviews with more than 800 senior marketers and 23,000 consumers. Only half of advertisers now feel they have the right balance between brand building and performance, down from 60 per cent a year ago. Confidence in the media mix slipped from 64 per cent to 57 per cent. And just 51 per cent say they are pulling actionable intelligence out of their data. Kantar’s own conclusion is blunt: the fix is sharper intelligence, not a bigger pile of data.

The hidden cost: The confidence gap

Call it the confidence gap: the distance between how much a team can measure and how sure it is about what to do next. It is easy to miss because every individual number looks healthy. Each platform reports its own engagement, its own attributed return and its own reach, and each one, read alone, says the money is working.

The trouble is that these numbers grade their own homework, and they often point the wrong way. Kantar’s creator research earlier this year found that platform engagement and real brand-building potential line up only about a third of the time. The number most teams use to pick creators misleads them two times out of three. Repeat that across search, social, retail media and video, and you get a dashboard that is busy, green and quietly uninformative.

Part of the gap is perception rather than performance. Kantar’s effectiveness data shows that channels working together drove 43 per cent of campaign performance between 2020 and 2025, up from 18 per cent before 2014. Marketers are getting better at making a fragmented mix pay. They just can’t see it clearly enough to defend it.

The moment it bites

Picture a regional head of marketing in Singapore in mid-October, three weeks from locking next year’s budget. Her quarterly review looks excellent. Paid social return on ad spend is up. Engagement on the creator programme has doubled. Cost per click fell in every market. Then the CFO asks the only question that matters: which of these moved revenue, and which can we cut?

Also Read: Why SEA’s retailers need to protect AI-powered customer experience with observability 

Nobody in the room can answer with confidence. Every channel can show a number that went up; none can show that the sales would not have happened anyway. So the budget rolls forward with a few percent shaved off everywhere, the same plan as last year, defended with the same slides.

That is the confidence gap turning into money. It is not one bad decision. It is a year of decisions nobody can explain.

The shift: A new channel nobody can measure yet

The gap is about to widen. Kantar finds that a net 75 per cent of marketers plan to increase investment in AI assistants in 2027, and 62 per cent expect generative AI to play a pivotal role in brand recommendations. Yet only 32 per cent of consumers use these assistants to research brands, and just 23 per cent trust what they recommend. Money is moving ahead of evidence.

The buy side already feels it. In the IAB’s outlook last month, 86 per cent of US buyers said they are changing how they measure media because of conversational AI and agents, and 45 per cent named comparing AI-driven and traditional customer journeys as their hardest measurement problem. Being found, cited and recommended in AI answers is turning into a goal in its own right, with no agreed way yet to count it.

What wins in 2027 is less measurement theatre and more signal discipline:

• Fewer, causal metrics. Pick the handful of numbers that track revenue or margin, and test them with holdouts instead of trusting each platform’s attribution.
• Prediction before spend. Score creative and audiences before the budget goes out, so the post-campaign report confirms a bet rather than explains it away.
• Category context. Read what competitors and audiences are doing across the market, not just your own funnel. A number only means something next to the market it sits in.

Why Southeast Asia feels it first

The confidence gap is wider here, for structural reasons. A regional team plans across half a dozen markets, several languages and a platform mix that changes at every border, from marketplaces to super-apps to messaging-led commerce. Global brands often hand local teams a direction from headquarters and a dashboard built for a single market, then ask them to defend spend line by line.

Also Read: AI chats are becoming the new starting point for online shopping

Agencies carry the same load with fewer people. An independent shop pitching against a network rarely loses on ideas; it loses on the depth of the read it brings into the room. That is why the insight stacks agencies build now matter as much as their creative. Whoever can explain the category, the audience and the competitive moves fastest earns the right to say what the numbers mean.

How the gap gets closed

The teams closing the gap are not adding dashboards. They are changing what they look at before they spend. As the founder of SOMIN, I see the same pattern across brands and agencies: read the category first, find the few signals that predict outcomes, and let those signals set the plan.

Two cases from our own work show how this plays out, and both are shared here as examples of the approach, not as proof the product works.

At Mothercare Singapore, the local team was tracking more than 4,000 category ads a year by hand and still guessing which content would land with Singaporean parents. Benchmarking the category by engagement per post rather than by volume showed that content about the real challenges of parenthood earned roughly 39 engagements per post, against about seven for festive gifting. With that read in hand, the team reported that time spent on research and ideation fell by 80 per cent, and that audience segmentation became three times more refined.

SAMY, an independent creative agency, used a similar approach to pitch a UK hospitality group against larger networks. Instead of leading with concepts, it walked in with a read of the client’s competitive set and an audience the category had left unserved, and won a multi-million-pound retainer. The agency now gets a click-through prediction on its creative before media money moves, which it reports at 78 per cent accuracy.

The three-number test

None of this requires a bigger martech stack. It requires the discipline to retire the metrics that flatter and keep the few that predict, and the confidence to explain that choice out loud: to the CFO, to clients and to the market. The leaders who do that in public, with a steady voice and the data behind it, will set the terms everyone else gets measured by.

So before the 2027 plan is locked: if you had to cut your dashboard to three numbers tomorrow, which three would you keep, and would your CFO pick the same ones?

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

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

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The cryptocurrency sector experienced a severe and sudden decline over the last 24 hours. Bitcoin fell 2.28 per cent to US$81,370.58. The broader digital asset ecosystem mirrored this downward trajectory, dropping 2.22 per cent to a total valuation of US$2.74 trillion.

An unexpectedly hot United States inflation report drove this widespread selloff across all major digital exchanges. The Bureau of Labor Statistics released the September Consumer Price Index data on October 14. This official government report showed the headline index rose 3.7 per cent year-over-year, beating the consensus forecast of 3.6 per cent.

Core inflation also surprised veteran investors by rising 0.3 per cent month-over-month, above the strict expectation of 0.2 per cent. These stubborn inflation numbers immediately altered investor sentiment and sparked a broad retreat from speculative risk assets. Retail traders and large institutional funds reduced their exposure to protect their capital.

Investors now anticipate a much more hawkish stance from the central bank due to persistent, sticky inflation readings. Higher interest rates directly reduce the appeal of non-yielding assets and force capital into safer government bonds. Policymakers will likely maintain elevated borrowing costs for a significantly longer period to combat the stubborn price increases across the real economy.

Traders eagerly await the upcoming Federal Reserve meeting scheduled for October 27 and October 28. The central bank committee will evaluate these fresh inflation metrics before making its final policy decision. Traditional equity exchanges and digital assets now move in near-perfect lockstep during major macroeconomic events. Bitcoin currently has a high correlation of 96.6 per cent with the S&P 500 index.

The total cryptocurrency space exhibits an even stronger 97 per cent correlation with the broader stock market. Professional traders increasingly view digital assets as high-beta extensions of traditional technology equities. This tight mathematical relationship means any negative macroeconomic news instantly pressures token prices and forces algorithmic selling.

Also Read: Could a hot inflation print send Bitcoin and Ethereum into freefall?

Technical indicators confirm the overwhelming bearish momentum across the entire digital asset landscape. Bitcoin recently broke below a very tight trading range and violated crucial historical support levels. Analysts previously identified the US$81,900-US$82,000 price range as a vital floor for the leading digital asset. The absolute failure to hold this specific area accelerated the downward price movement and triggered automated sell orders.

The 50-day moving average currently sits at US$82,636 and now acts as formidable overhead resistance for any attempted relief rallies. Aggressive short sellers completely control the immediate trend and actively push the price toward lower liquidity pools.

If the asset fails to reclaim the broken support zone in the coming days, aggressive sellers will likely drive the price down to test the US$78,000 mark. A deeper, more painful correction could easily push the valuation into the US$78,000 to US$79,250 support range, where long-term buyers might finally step in to accumulate more coins.

Excessive leverage in the complex derivatives market significantly amplified the recent drop in spot prices. The sudden macroeconomic shift forced the rapid liquidation of heavily leveraged trading positions across multiple global exchanges. Crypto derivatives platforms processed over US$71.16 million in Bitcoin liquidations within a single 24-hour period.

This massive forced selling represents a staggering 52.33 per cent increase from the previous trading session. Bullish traders absorbed the vast majority of this financial pain, as long liquidations specifically totaled US$59.15 million. These forced margin closures created a violent cascading effect that pushed the spot price even lower in a very short timeframe.

The derivatives sector currently shows a positive funding rate of +0.0048 per cent. This metric indicates that optimistic buyers still pay a premium to hold long positions despite the recent, severe price decline. Smart money traders need to see a complete stabilisation in open interest to confirm the market has successfully flushed out the excess leverage and established a firm base.

Also Read: Below US$82,620 Bitcoin could test US$81,154 next

The timing of this macroeconomic data release significantly worsened digital asset price action. The inflation report hit the trading desks during a period of notoriously thin weekend liquidity. Market makers and large institutional trading desks typically reduce their activity during Saturdays and Sundays. This lack of deep order book liquidity allows relatively small sell orders to cause massive price slippage. The combination of forced derivative liquidations and thin weekend order books created a perfect storm for volatility.

Retail traders watched their portfolios shrink rapidly as the market lacked the necessary depth to absorb aggressive selling pressure. This structural market vulnerability highlights the immense risks of holding highly leveraged positions during major macroeconomic announcements.

The total cryptocurrency capitalisation faces its own critical technical test on the daily charts. The aggregate valuation recently defended the crucial US$2.67 trillion support level against aggressive selling pressure from nervous participants looking to exit their risky bets.

Technical analysts recognise this specific price point as the exact 78.6 per cent Fibonacci retracement level from the recent major swing high. A sustained break below this crucial floor would expose the entire digital asset ecosystem to severe downside risks and panic selling. Aggressive bears would then target the yearly swing low situated precisely at US$2.6 trillion.

Conversely, a successful and decisive defense of this support zone could spark a powerful relief rally across the board. Confident buyers might then push the total market capitalisation back toward the 50 per cent Fibonacci level at US$2.77 trillion. The overall structural health of the digital asset ecosystem depends heavily on maintaining these aggregate valuation thresholds and demonstrating underlying buyer demand.

The immediate future of the cryptocurrency sector hinges entirely on the upcoming economic data releases. The Bureau of Labor Statistics will publish the highly anticipated Producer Price Index report later today, October 15, to provide further clarity on wholesale inflation trends.

Also Read: Bitcoin’s US$83,000 test: Can institutional demand hold the line?

This specific data point serves as the final major inflation metric before the central bank convenes for its crucial policy meeting. A softer reading could provide immediate relief to battered risk assets and spark a short-term technical rebound. Another hot inflation print will undoubtedly extend the current aggressive selloff and drive prices to new local lows.

I view the current market environment as a classic macro downdraft, in which stubborn inflation fears trigger a distinct flight from risk. Institutional buyers must step in to defend the US$81,000 support level and stabilise the bleeding across major trading pairs.

The trading action will soon reveal whether smart money views this dip as a prime buying opportunity or if more deleveraging awaits impatient retail traders. Traders must closely monitor daily closing prices to confirm the prevailing directional trend. A daily close below US$81,000 will confirm further downside toward lower support zones and validate the bearish thesis.

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At M360 ASEAN in Kuala Lumpur last week, the GSMA released its ASEAN Consumer Scam Report 2026. Nearly half of reported scam cases across six markets remain unresolved. Nearly nine in ten consumers said they had recognised AI being used in scams, from deepfakes to voice cloning. Julian Gorman, the GSMA’s head of Asia Pacific, summed it up: “Access alone is no longer enough.”

A month earlier, the GSMA’s Mobile Economy Asia Pacific 2026 named the rise of AI and declining digital trust as two of four forces shaping the region’s next phase. The share of ASEAN consumers who say they have been scammed rose from 31 per cent in 2024 to 45 per cent in 2025.

Across the region, operators are now moving AI into the customer app. The technology operators are racing to deploy is the same technology eroding the trust they need to deploy it. That dependency is missing from most business cases.

Trust is now a churn number

For years, trust sat in the compliance column. That is changing. The 2026 scam report found that people who have been scammed are more than twice as likely to switch accounts or providers as those who have not. The 2025 edition found that 36 per cent of consumers would switch financial services provider for stronger security built on telecom data.

Operators hold both sides of that equation. Their networks carry the calls and messages scammers rely on, and their data can help stop them. Some are already treating protection as a product: CelcomDigi sells a dedicated safety range alongside its mobile and fibre plans, and Globe has convened a Philippine anti-scam coalition with the Global Anti-Scam Alliance. Trust is already on the price list.

The risk sits with the operator

AI inside a telco app runs on the operator’s license and on a billing relationship that may be decades old. When a vendor’s model gets something wrong, the regulator calls the operator, and so does the customer.

Southeast Asia has mature rules for networks and, increasingly, for personal data. Consumer-facing AI inside an operator’s app is newer ground, and in practice much of its governance still lives in vendor contracts. That is a thin layer on which to rest a national operator’s reputation.

Also Read: Inside Singapore’s biggest telecom cyber defence operation

Subscribers have already written part of the spec

The most useful finding in the GSMA’s 2025 scam research was not a victim count. Consumer comfort with sharing data with conversational apps fell from 53 per cent to 40 per cent. In the same survey, 72 per cent said they were comfortable with limited, purpose-bound checks that use network signals to protect them.

Read together, those numbers describe the AI subscribers will accept. Not a chatbot that asks them questions. A system that works in the background, for a defined purpose, on as little personal data as possible.

Four tests operators can apply

In this context, trust is architecture, not assurance. Four design choices can be tested before anything goes live.

• First, the AI reads patterns, not people. There is no conversational surface between the subscriber and the model, so there is nothing to impersonate and nothing to phish.
• Second, the operator holds the identity key, and the intelligence layer sees only irreversible identifiers.
• Third, data is processed in-country.
• Fourth, the capability is exposed as an operator-controlled API: every call is logged, priced and revocable, and the operator can switch it off.

We had to build to these tests ourselves, because operator security teams kept asking the right question: if this sits inside our app, how do we know you will not walk off with our data? The answer that worked was not a promise. It was something their own teams could test before launch. That should be the standard for every AI vendor in this market. Do not ask for trust. Hand over something to test.

Also Read: How Agentic AI will create telecom’s first truly autonomous workforce by 2030

Breadth substitutes for intimacy

Personalisation is usually assumed to need more personal data. It does not have to. A system that sees wide behavioral signal across telecom, payments, content and gaming can personalise on patterns rather than identity. The more it sees of what people like you do, the less it needs to know about who you are.

Where trust is actually earned

Most subscribers do not decide whether to trust an operator by reading its privacy policy. They decide in small, frequent exchanges: whether points are credited when promised, whether a voucher works at the till, whether an offer feels useful or intrusive.

A user who watches food content and sees grocery vouchers surface first experiences AI as a service. The same signal used to push products they never asked for reads as surveillance. Every honored reward is a deposit. Every offer that feels like tracking is a withdrawal.

That exchange matters beyond churn. The GSMA estimates that 3.1 billion people live within mobile broadband coverage but do not use it. For many of them, the question is not whether the network reaches them. It is whether being online is safe enough to be worth it.

Operators planning AI launches for 2027 should be able to answer two questions before signing a vendor. Can our own security team test this before it goes live? Can we switch it off tomorrow? If the answer to either is no, the AI is not ready, however good the demo looks.

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

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

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