When Meta switched on Muse in Singapore last month, ShopBack was one of eight launch connectors the agent could plug into. In the US, Amazon had taken a different view. It blocked Muse within 12 days of launch, complaining in part that an agent shopping for a customer bypasses the personalisation built into its store.

ShopBack, a shopping and rewards platform, chose to sign up rather than shut the door. Justin Lee, its Chief Product Officer, says the web was built for people to read, not for agents to act on. e27 sent him ten questions on what that means for a business that earns its keep between the shopper and the merchant. His answers show a confident bet. They also leave a few things unsaid.

Also Read: Agentic commerce’s dirty secret: the data powering AI purchases is often wrong

The stakes are easy to state. A shopping and rewards platform, lives in the gap between buyer and seller. An agent that can compare prices on its own could route around that gap entirely. Lee’s wager is that the agent will keep a shopping and reward platform in the loop because the reward is part of the best deal.

Two weeks to write for a reader that never skims

Without a connector, Lee says, an agent shops like a person with a search engine, only faster. It combs through pages designed for human eyes and pieces an answer together from whatever it finds. That works, but it is slower, and the agent cannot always tell whether a price or a reward is still current.

The connector replaces that guesswork with a direct line into ShopBack’s live data: merchants, prices and the savings attached to each. “Building one meant writing for a new kind of reader, one that takes everything at face value and acts on it straight away,” Lee says. His team built it in two weeks.

He frames Muse as the next stop on a familiar road. ShopBack moved from website to app to browser extension, and then into the ChatGPT App Store, where it was among the first shopping and rewards apps. Asked whether ShopBack saw something Amazon missed, Lee declines to pick a fight. “Different companies will make different choices for their own business,” he says.

It is a diplomatic answer to a blunt question. Amazon owns the shop, so it can afford to keep agents out. A shopping and rewards platform owns no shelves. If AI shopping agents reshape retail the way their backers expect, being the tool the agent shops with is partly insurance against being bypassed.

Same link, same commission, new storefront

Affiliate commerce runs on attribution: tracked clicks, cookies, a visible referral path. Lee insists nothing changes when Muse does the clicking. A sale counts as ShopBack’s only if it goes through a ShopBack link, which is the link Muse gives the shopper. The merchant’s own tracking confirms the sale, and merchants pay only for confirmed sales, on their existing terms.

What about commission on a sale the agent would have made anyway? Lee argues the agent weighs several merchants before answering. When a ShopBack reward tips the balance, “the reward is what won the sale”. It is the classic affiliate defence, the same logic behind Lazada’s US$100 million affiliate push. Whether it holds for an agent that might have picked that merchant regardless is harder to prove.

Also Read: Singapore is paying startups to secure the AI agents it is racing to deploy

On who owns the customer, Lee explains a traveller who books a flight through Muse buys from the airline, which issues the ticket and keeps the relationship. Muse is the channel and ShopBack the rewards layer.

To the questions on who (ShopBack or Meta) keeps the conversational data and whether money changes hands with the tech behemoth, Li says: “How Muse handles conversations is best answered by Meta. On our side, ShopBack never sees what the member types. When Muse decides a member’s request calls for ShopBack, it turns to the ShopBack connector, and the connector returns the relevant options and rewards.”

When it comes to ⁠payment, he claims that no fees changed hands between ShopBack and Meta. “We joined Muse’s Singapore launch at Meta’s invitation, because we are always looking for more places to reward our members, and personal AI agents are where more of them are starting to shop.”

Cheapest after cashback, or best for the merchant?

Meta’s own launch demo has ShopBack finding the cheapest return flight to Seoul after cashback. Can a user check that the answer really is the cheapest, and not the one from the merchant paying the highest commission? Lee’s reply is that the agent sees each deal’s price and savings and weighs them “on the facts”. Anyone who wants to check can open the ShopBack app and find the same deal there.

That is a consistency check, not an independent one. The app and the connector draw on the same data, so finding the same answer in both tells a shopper ShopBack is consistent, not that it is cheapest across the whole market.

The pay-to-rank question gets the most interesting answer. Merchants can already boost the rewards they offer through ShopBack, and Lee says that boost reaches the shopper as a bigger saving. “We give the agent the facts, and the agent decides,” he says. It echoes the promise that Muse doesn’t care about your ad budget.

The line is sensible, but it is thinner than it sounds. A boost is merchant money spent to win the agent’s pick, and it works best when the agent weighs savings heavily. For brands already worried that if an AI agent cannot find you, you do not exist, boosted cashback may become the cheapest way to be found.

When the agent books the wrong flight

Meta delayed Muse’s US launch over security concerns, and The Information reported that the agent sent emails without approval during testing. So who pays if Muse books the wrong non-refundable fare using ShopBack’s data? Lee’s answer puts the purchase with the merchant, under the merchant’s terms. ShopBack handles only the rewards side, through its help centre.

That is a neat division of labour, and probably the legally correct one. It is also the kind of handover that makes liability for autonomous agents so murky. Lee concedes the point in broader terms. “I believe trust will decide whether people shop with agents at all,” he says, adding that the industry must stay clear about who does what. In a market where Singapore firms lead APAC in deploying AI agents and in rolling them back, that clarity is not optional.

Plumbing or destination? Lee says both

Much of cashback’s pull is emotional: the user sees the reward, feels clever and comes back. If the agent does the shopping, Lee says, the satisfaction simply moves into the answer, with Muse showing the savings on each hotel option. Members still collect their rewards in ShopBack, and spend them online or in store with ShopBack Pay, a product backed by the MPI licence it secured from MAS.

The bigger worry is becoming back-end plumbing for someone else’s interface, especially as ShopBack builds its own AI tools. Co-founder Henry Chan has described searching 15 retailers for a single flight query. Lee rejects the choice. The connector runs on the same services as the app, so improving one improves the other. The app, with tools like its Travel Planner, remains where members cash out and stumble on deals they did not ask for.

Also Read: AI agents need someone standing behind them, says AmanTrue CEO Evin McMullen

Muse also has rivals: OpenAI’s Operator, Google’s Gemini Spark and Perplexity’s Comet. ShopBack built its connector to work with more than one agent. What stops it from becoming a swappable plug-in? Lee points to members’ own accounts and balances, merchant partnerships and more than a decade of understanding how people shop.

That moat is real but untested. Agents are built to find the best answer, as Lee keeps saying. The day a rival offers a fatter reward, the agent will report that fact without loyalty. ShopBack has bet that it can keep winning on the facts. In agentic commerce, that may be the only bet available.

The post ShopBack’s Justin Lee on why it let Meta’s Muse in while Amazon shut the door appeared first on e27.

You have an idea for a service or a small product. You have a free weekend and no developer. By Sunday night you also have a list: a domain, hosting, a site builder, a way to take payment, a mailing list, somewhere to keep customer data, and a plan for answering the same three questions every day.

None of it is hard on its own. Together, it is why many good ideas stay in a notes app.

Founders in Indonesia, Malaysia, the Philippines and Vietnam face this with fewer hours and smaller budgets than a funded team. The work between an idea and a paying customer is getting shorter, though, because more of it can now be handed to AI that does the task rather than only talking about it.

What “agentic” means in plain words

Most people have used AI that answers. You ask how to add a login page and it explains the steps. Agentic AI takes the steps. You ask for a login page, and it builds the page, connects the database and tells you what it did.

The difference is who does the work. An explanation still leaves you with a to-do list. An action makes the list shorter. For a founder who is not technical, or only partly so, that gap decides whether a project moves this week or next month.

Step 1: Test the offer before you build anything

Write your offer in three sentences: who it is for, what they get, and what they pay. Say it to ten people who fit that description. Then count how many ask a follow-up question, such as when they can start or how to pay.

Those questions are your signal. Polite compliments are not. If fewer than two of the ten ask, change the offer before you touch a website.

Step 2: Build the smallest version that can take a customer

A first version needs three things: a page that explains the offer, a way to collect a booking, order or sign-up, and a way to follow up with the people who respond. A logo redesign, a blog and a second product can wait until after your first five customers.

This is the step where tools matter most, because it is where solo founders lose the most time to setup.

Also read: The US$1M per person revolution: how AI is reshaping Southeast Asia’s startup landscape

Where Hostinger fits: build, run and grow from one account

Hostinger began as a web hosting company and now describes itself as an agentic platform for building, running and growing a business online. It reported more than 5 million users in June 2026, described as small businesses and solopreneurs across more than 150 countries, with Indonesia among the five markets it names as the core of that base.

Build with Hostinger AI Builder

You can start Hostinger AI Builder from a prompt, a PDF, a screenshot or a link to an old site. In agentic mode the AI leads while you describe what you need. In manual mode you move sections and edit elements yourself.

Data, user accounts and sign-in run on Hostinger’s own backend, so asking for customer accounts means the AI sets up the database and the sign-in. It works in an environment separate from your live project, and changes go public only when you publish them.

Know the limits too. Hostinger’s documentation notes that agentic mode cannot currently create some types of projects, including native iOS or Android apps and trading or banking applications. If your idea falls into one of those categories, plan a different route.

AI Builder is designed for founders working solo or without a technical team, and for getting a working first version live quickly. As your product grows more complex, or starts handling large volumes of customer data or payments, bringing in a developer to review and extend what the AI built is a sensible next step.

Run with Hostinger Agent and Agentic Mail

Hostinger Agent works through chat to help you manage your site, from plugins and domains to fixes and edits. Hostinger says it is included with every plan for site management, and that a paid upgrade adds ready-to-use skills for SEO, content, marketing and sales.

Agentic Mail connects a mailbox to AI agents so they can sort enquiries or send routine replies. It takes some tool setup, so most non-technical founders will start with Hostinger Agent.

Sell and grow

To take orders, add Hostinger E-commerce, a separate subscription that lets you sell unlimited products. Hostinger Reach handles email marketing: describe the campaign or the customer segment and the AI drafts it.

Build your site with Hostinger

Step 3: Ask your first customers for something

After the first sale, ask that customer two questions: what nearly stopped them from buying, and who else should hear about this. Write the answers down. The first answer tells you what to fix on your page. The second gives you your next three conversations.

Do this for your first ten customers, not only the first. Patterns usually appear within a handful of answers, and they tend to be about trust, delivery time or unclear pricing rather than missing features.

Also Read: SEA’s venture capital shifts from mega-rounds to AI and SaaS

Step 4: Hand over the repeating work and keep the decisions

Make a list of what you did more than twice last week: answering the same enquiry, resizing images, drafting the same email. Those are the tasks to hand to an agent first. Pricing, which customers you take on and what you promise stay with you.

A simple weekly routine is enough to start. On Monday, read the week’s enquiries and decide which ones you answer yourself. Midweek, send one email to your list. On Friday, review what the AI changed and approve what goes live. While you are small, aim for about an hour of review a week.

Track three numbers for the first month: enquiries received, enquiries that became orders, and hours spent on admin. If the admin hours are not falling, the automation is not working yet, and that is worth knowing early.

The order matters more than the tool

Tools will change, and so will what each one can do. The order of work holds: test the offer, build the smallest version, get paid, then automate what repeats. If you want to try the build step this week, Hostinger AI Builder is a place to start.

Build your site with Hostinger

—

The e27 team produced this article sponsored by Hostinger

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

Featured image: Hostinger

The post How Hostinger is helping solo founders in Southeast Asia go from idea to paying customers appeared first on e27.

Every new AI chip arrives with a bigger compute number. Fewer arrive with an honest admission that those chips increasingly sit idle, waiting for data to trickle in over copper wires that were never designed for this kind of workload.

Singapore’s Staera Semiconductor is betting its future on that gap. The deeptech startup, formerly known as New Silicon Corporation (NSC), emerged from stealth today with US$4.6 million in pre-seed funding to commercialise Lightwire.

Lightwire is an optical interconnect that generates light inside the silicon chip itself rather than bolting a light source on next to it.

Also Read: Nexstrom lands US$12M to bring 2D semiconductors to 12-inch wafers

Openspace Capital led the round, with participation from SGInnovate, Black Kite Capital, 28 Holdings, In Group and Decimus Technologies. Staera is a spin-off from the Low Energy Electronic Systems (LEES) research group at the Singapore-MIT Alliance for Research and Technology (SMART), MIT’s first research centre outside the US.

Copper is running out of road

The problem Staera wants to solve is not new, but AI has made it acute. Inside an AI system, data has to travel between processors, memory stacks, boards and racks, over distances ranging from a millimetre to a metre. According to the company, copper’s electrical performance degrades roughly a thousandfold across that range. Push more data further over copper and you pay for it in power and heat.

That is a painful trade at a time when electricity is becoming the binding constraint on AI. The International Energy Agency expects global data centre electricity use to more than double, from about 415 terawatt-hours in 2024 to around 945 terawatt-hours by 2030. In Southeast Asia, where operators are already running short of power for AI servers, every watt saved on moving data is a watt that can go to compute, or not be drawn from the grid at all.

Even Nvidia, which said in 2025 it would stay with copper for as long as it could, now plans to use both copper and optics in its AI systems. Analysts tracking AI’s emerging bottleneck economy increasingly point to interconnects, packaging and memory bandwidth, rather than raw compute, as the place where the next squeeze, and the next wave of spending, will land.

Building the lamp into the wafer

Most optical links today are assembled from separate parts: a laser or LED made elsewhere, attached next to the chip and coupled to waveguides. Every join adds cost, power draw and another thing that can fail.

Staera’s pitch is that it fabricates the whole optical link on a single commercial silicon wafer using standard fab steps. That means gallium nitride (GaN) LEDs as the light source, silicon nitride waveguides to route the light, and the CMOS circuits that drive it, all on one piece of silicon. Lightwire sits inside the bridge or interposer chip that already connects processors and memory in today’s AI hardware, so, in theory, it slots into existing packaging flows.

“Copper performance plummets over the millimeter-to-meter distances that matter most in AI accelerators, and bolt-on optics add power and complexity,” said Dr Andrew Kim, CEO of Staera. “We build the light into the chip, the entire optical link inside a chip, so the connection gets smaller, cooler and faster with each generation.”

Also Read: NASA-linked, MIT-trained founders’ nSWX raises US$2M for AI chip packaging

The headline numbers are striking. Staera says Lightwire is designed to move data at under 0.2 picojoules per bit, against about 5 pJ/bit for co-packaged optics, the current state of the art. At memory scale, it says moving 24 terabytes a second would take under 50 watts with Lightwire, versus nearly a kilowatt with co-packaged optics. It also claims a reach beyond 50 mm, compared with 2 mm for the UCIe-A die-to-die links used in today’s chiplet designs.

The fine print hides in “designed to”

Note the verb. Almost every efficiency figure Staera has released is a design target, not a measured result from a shipping product. Commercial release is pencilled in for 2030, four years and, almost certainly, several funding rounds away.

There is also an engineering trade-off worth understanding. Each Lightwire link runs at a modest 4 to 8 Gbps, far slower per lane than the high-speed electrical and laser-based links found in data centres today. The bet is on density rather than speed: more than 600 links per millimetre of chip edge, all running in parallel. That approach plays to the strengths of LEDs, which are cheap and frugal with power, but cannot match lasers on per-channel bandwidth.

Staera does have manufacturing pedigree on its side. It says it has been building GaN LEDs into silicon chips in commercial foundries since 2016, with yields now at 98 to 99 per cent. That longevity cuts both ways, though. A decade of R&D culminating in a US$4.6 million pre-seed cheque is a modest sum for a company that wants to rewire AI hardware, and a reminder of how capital-hungry chip startups are.

Investors seem comfortable with the long horizon. “We backed Staera because of the strength of its technology, the depth of its team and its potential to define a new category in semiconductor connectivity,” said Hian Goh, co-founder of Openspace Capital.

The startup also won the ECTC Start-up Competition at the IEEE Electronic Components and Technology Conference in May, and placed runner-up at Lam Research’s 2026 Lam Capital Venture Competition the same month.

A crowded race to dethrone copper

Staera’s claim to be the first and only optical interconnect built fully into the chip will be tested by a well-funded field. In the US, Ayar Labs and Lightmatter have raised hundreds of millions of dollars for silicon photonics, while Marvell agreed to acquire photonic interconnect startup Celestial AI in late 2025.

California’s Avicena is the closest conceptual cousin, using microLED arrays for short-reach chip links. Broadcom and Nvidia, meanwhile, are pushing co-packaged optics into networking switches.

Closer to home, Staera joins a small but growing cohort of Southeast Asian semiconductor startups moving beyond assembly, including photonics player LightSpeed Photonics. Its real differentiator is monolithic integration: if the light source is grown on the same wafer as the circuits, it sidesteps the assembly and alignment headaches that dog bolt-on optics. Whether that holds at volume is the question customers will ask first.

Singapore wants a bigger slice of the AI hardware stack

Staera’s emergence fits neatly into Singapore’s push to climb the chip value chain. A*STAR and the Economic Development Board recently unveiled SG Semiconductor as a national identity for the sector, A*STAR has teamed up with Synopsys on AI chip packaging, and Applied Materials has expanded its Singapore footprint with a US$500 million campus. Interconnects and advanced packaging, the unglamorous plumbing between chips, are exactly where the city-state hopes to matter.

Also Read: Amplicity raises US$1M to put Singapore’s sleeping data centre batteries to work

The fresh capital will go towards advancing the technology, expanding the team into the US, and deepening work with customers and supply chain partners. The US push is telling: the buyers who will decide Lightwire’s fate, hyperscalers and AI chip designers, mostly sit in California.

For now, Staera has a compelling physics argument, a manufacturing track record and a four-year runway to prove its numbers survive contact with real hardware. If they do, the most important part of tomorrow’s AI chips may be the light nobody sees.

The post Copper is choking AI. Staera secures US$4.6M to swap it for light appeared first on e27.

The show is over. The founder sits on the hotel bed and counts the cards.

Four hundred, give or take. A dozen promises to call next quarter. Several requests for samples. Everyone said the product was good. Not one conversation with someone who would actually use it.

Who comes to the booth

Importers. Distributors. Consultants. Accountants. Some buy. Others advise on regulation, tax and market entry. None of them uses the product.

The distributor knows what moves off the shelf, what gets returned, where the margins are. The consultant knows the rules. The accountant knows the tax treatment. None of them knows what happens after the product leaves the store: who opens it, at what hour, for what purpose. That was never their job.

So you hear the same sentence at 10 shows in a row. Great. Send samples.

Los Angeles, 1959

Honda opened its first overseas subsidiary in Los Angeles in June 1959, in a storefront on Pico Boulevard with eight employees. By the end of the year it had sold just 170 motorcycles. Americans wanted big motorcycles. Harleys. Triumphs.

Then the 50cc Super Cub started to move. Americans didn’t ride it the way the Japanese did. Some hauled it to campsites and fishing holes. Honda went where they were: direct mail to sporting-goods, boating and fishing shops, ads in general-interest magazines like Life, shelf space where no motorcycle had been sold before.

Monthly sales passed 1,000 in May 1961. By 1962, Honda was selling 40,000 a year in the US.

Honda’s answer wasn’t a bigger motorcycle. It was a different customer.

Nobody at a trade show tells you their customers load this into a pickup. You see it only by being there.

Also Read: Start with the problem, not the token: What Wall Street’s tokenisation push means for Southeast Asian founders

Samsung’s year abroad

In 1990, Lee Kun-hee launched Samsung’s regional-specialist programme. Not an expat posting. One employee, one country, a year or more. Learn the language. Walk the streets. Learn how ordinary people live.

Insiders resisted: the cost, the good people pulled off the line. Lee pushed it through. “We cannot do anything without globalised manpower,” he reportedly said.

Today each specialist costs more than 100 million won (US$68,000) a year on top of salary. Harvard Business Review later called the programme a vital part of Samsung’s globalisation.

Honda learned by selling there. Samsung paid to learn how people lived there. Neither mistook a visit for knowing the market.

The three-day expansion

For many startups, “global” means three days a year. A booth bought with a government subsidy. A conference someone else organised. Then the report home: productive trip. A few dozen meetings. Hundreds of cards.

Trade shows are easy to count. Meetings held. Cards collected. Samples requested. Subsidy spent. But what did the founder learn about the customer? There is no column for that.

The trip fills the CRM. The customer stays a stranger.

The customer never came to the booth. The founder met the people whose job is to explain a country’s market, and they relay a life they don’t live. If your overseas strategy came out of their mouths, it isn’t a strategy. It’s hearsay. The company’s next three years may depend on a second-hand account of the market.

Also Read: The frontier AI money is getting picky. Southeast Asia’s AI founders should price that in now

Why nobody goes

A week on a foreign street is harder to count. It is also uncomfortable. No shared language. Strangers who can’t imagine why they’d need your product. The hotel and the booth are the safest ground a founder has abroad.

But the discomfort is where the questions start. Questions that never come up in a convention hall. You might learn why no one needs your product. Or why they need it for something you never imagined. Either answer is worth more than 400 cards.

Skip it, and everything downstream rests on second-hand knowledge. A country manager hired by someone who has never met a customer. Local pricing set from a distributor’s spreadsheet. Local marketing built on a consultant’s slide. We call it going global.

Four hundred cards, and not one customer’s day understood. That founder didn’t enter a market. He took a business trip, and burned through more of a shrinking runway.

One question

In the country you want to enter, can you walk through one customer’s day, morning to night? What’s their name?

—

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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Airwallex wants Singapore to know it is staying put. The cross-border payments firm said on Wednesday it will invest more than SGD2 billion (about US$1.5 billion) in the city-state over the next five years and grow its local headcount from over 750 to more than 1,000.

The move cements Singapore as one of its two global co-headquarters, alongside San Francisco.

The pledge coincided with the official opening of its expanded office at Guoco Tower in Tanjong Pagar, which the company describes as Singapore’s tallest building. A new floor on level 35 is now occupied and another is due in early 2027, taking Airwallex’s local footprint to more than 80,000 sq ft across four floors.

Also Read: Growth-minded Singapore SMEs turn to fintech amid cost pressures: Airwallex survey

On paper, it is a hefty vote of confidence at an awkward moment. The US1.5 billion figure is roughly three times what every Singapore fintech raised combined in H1 2026. That half-year haul, US$499 million across 53 deals, was the city-state’s weakest first-half fintech showing in close to a decade. Nearly two-thirds of it came from a single cheque: Airwallex’s own Series H.

What US$1.5 billion actually buys

Airwallex did not break the figure down. The release says the money will support workforce expansion, product and technology capabilities, and the strengthening of “global and regional operations”. That is a broad bucket. Over five years, it could easily absorb salaries, office leases and compliance costs that a fast-growing company would incur anyway.

The hiring target deserves the same scrutiny. Adding roughly 250 roles over five years works out to about 50 a year. By comparison, Airwallex’s global headcount went from more than 2,300 when it announced its US$320 million Series H in June to more than 2,700 today. That is some 400 people in about five months. Singapore is growing, but it is not where most of the new desks are going.

What the company stresses instead is the kind of jobs. Airwallex says it will build “specialised, high-value capabilities” in product development, engineering and AI.

The Singapore Economic Development Board (EDB), which worked with the company on the expansion, struck the same note. “We welcome Airwallex’s continued investment in Singapore, which will significantly increase its footprint and anchor more product and AI capabilities here,” said Herman Loh, Senior Vice President and Co-Head, Digital Industry Singapore at EDB.

That is the more meaningful signal. Singapore’s pitch to global firms has long rested on being where regional decisions get made. Anchoring engineering and AI work, rather than just sales and compliance teams, is what keeps that pitch credible as other financial centres court the same companies.

Ninety per cent, of what?

The growth numbers are eye-catching. Airwallex Singapore reported 90 per cent year-on-year growth in both revenue and total transaction volume in H1 2026. It did not disclose absolute figures, so it is hard to tell how much of that is a modest base compounding quickly.

Group-level numbers offer some perspective. In June, Airwallex said it had reached US$1.3 billion in annualised revenue in March, up 74 per cent, and US$287 billion in annualised transaction volume, up more than 120 per cent. The periods are not like-for-like, but Singapore appears to be outpacing the group on revenue while trailing it on volume.

Also Read: The hidden margin killer: Why CFOs are rethinking cross-border payment infrastructure

The company credits demand from local businesses that want their finances in one place. “Singapore SMEs increasingly value integrated financial solutions that bring their financial operations together on one platform,” said Lionel Tan, Head of SME and Growth at Airwallex. He added that interest in AI tools for managing finances is also rising.

The customers it names are telling. Far East Flora, Stryv, Circles, Moom Health, ZENXIN Organic and Chronos Agency span floristry, food, telecoms, health and marketing. That mix suggests Airwallex is reaching well beyond venture-backed startups into traditional SMEs taking their first steps overseas.

A crowded corridor out of Singapore

Airwallex is hardly alone in treating Singapore as a launchpad. Homegrown unicorn Nium has been pushing into stablecoin rails, most recently by acquiring Cypher. Circle’s US$400 million deal for Tazapay showed that stablecoin giants want a slice of regional flows too. Aspire courts the same SMEs with business accounts and spend tools, while Stripe, Wise and Adyen fight for merchants.

Airwallex’s answer is regulatory depth. It holds more than 85 licences worldwide and runs its own settlement integrations. It has also shown it will buy its way into markets rather than wait, as with its acquisition of Paynuri in South Korea.

From Singapore, the firm is expanding into Malaysia, Indonesia and Vietnam. In these markets, payment habits, foreign exchange rules and licensing regimes differ sharply, and cross-border payments remain fragmented enough that licences matter more than marketing.

A co-headquarters is a promise, not a guarantee

“We’re not just expanding our presence in Singapore, we’re investing in the talent, technology and capabilities that will power our next phase of global growth,” said Arnold Chan, General Manager, Asia-Pacific.

Also Read: Before the licence: What Singapore’s regulated institutions ask a fintech partner first

The open question is how much decision-making weight “co-headquarters” really carries. Dual-HQ structures tend to tilt over time. Airwallex earmarked its Series G to power US expansion, so San Francisco will exert a strong pull.

Still, in a year when fintech capital in Singapore has thinned, a company committing multi-year spending, four floors in a landmark tower and AI engineering roles is a signal EDB will gladly amplify. The real test comes in 2031: whether the 1,000 jobs materialise, and how many of them build products rather than sell them.

The post Airwallex’s US$1.5B Singapore pledge dwarfs the island’s entire fintech funding haul appeared first on e27.