Thailand-headquartered online beauty marketplace Konvy has closed a US$22 million Series B round led by Cool Japan Fund (CJF), signalling a sharper push to export its omnichannel playbook across Southeast Asia.

Existing backers, including Insignia Ventures Partners, also participated in the financing.

The capital injection comes at a pivotal moment: Konvy has already entrenched itself as a major force in the kingdom’s beauty and personal care market, and now it wants to turn that domestic strength into regional scale, with the Philippines and Malaysia first in line.

A proven domestic engine

Konvy’s core advantage is its reach across multiple channels. The company combines its own e-commerce site with a presence on leading marketplaces, social commerce activity and offline retail. That omnichannel footprint has allowed it to assemble a catalogue of more than 20,000 SKUs from over 1,000 brands and to secure a position as one of Thailand’s most influential beauty platforms.

Also Read: How technology can influence the beauty and cosmetics industry

That market leadership is not merely about assortment. Konvy has invested in the data and logistics plumbing that knit together transactional channels and customer touchpoints, which the company argues helps it turn product curation into repeat sales and stronger brand relationships.

“We have built a strong leadership position in Thailand, and we are now focused on scaling that success across Southeast Asia,” said Qinggui Huang, Group CEO of Konvy. “With CJF as our lead partner, we are uniquely positioned to bring high-quality Japanese brands to the region while continuing to grow our own portfolio of private label products.”

The quote is revealing for two reasons.

• First, Konvy still pursues a hybrid strategy: it wants to be both a channel for third-party brands and a manufacturer of private-label goods.
• Second, the deal with CJF is explicitly strategic aimed at positioning Japanese beauty and health brands for faster growth in Southeast Asian markets.

Why Cool Japan Fund matters

CJF is not a run-of-the-mill investor. Established to promote Japanese culture and products abroad, it brings sectoral and diplomatic heft in addition to capital. For Konvy, CJF’s participation is less about the check and more about the pathway it opens to Japanese manufacturers and brand owners who want an on-ramp into Southeast Asia.

The partnership is bilateral. Konvy gains privileged access to suppliers and products; CJF gains a distribution partner that understands the nuances of Southeast Asian consumer tastes and the region’s varied commerce landscape. For Japanese brands, this is valuable: Southeast Asia’s demand for curated, higher-quality personal care products is rising, but navigating marketplaces, social commerce and offline retail across multiple countries is operationally complex.

Expanding into the Philippines and Malaysia

Konvy’s roadmap is to use the Thai playbook to scale in the Philippines and Malaysia. Both countries present attractive demand-side dynamics, rising middle-class consumption and a growing appetite for curated beauty offerings. Still, they also pose structural challenges such as fragmented distribution, payment preferences and language differences.

Also Read: Beauty’s next big bang: Why beauty tech collaboration holds the key to a US$590B future

Konvy plans to transplant its omnichannel model, but it cannot simply replicate operations wholesale. The company must adapt marketing, product selection and fulfilment to local tastes and logistics networks. That will require both local hires and partnerships with regional players, alongside investments in customer insights to avoid treating the region as homogeneous.

Market observers note that social commerce is particularly potent in the Philippines, where influencer-led buying and chat-based transactions remain central. Malaysia, meanwhile, presents a multicultural market with diverse regulatory environments for cosmetics and supplement categories. Konvy’s stated intention to combine marketplace listings, social commerce and offline retail suggests it understands these nuances; execution, however, will determine success.

Private labels and exclusive distribution

Part of Konvy’s pitch is its ambition to scale private-label brands through exclusive distribution agreements with established partners. Private labels offer higher margins and tighter control over assortment, but they also carry inventory and brand risk. Scaling private labels across countries means mastering local regulatory frameworks for product formulation, labelling and claims.

Exclusive distribution plays to Konvy’s strengths in logistics and marketing. By offering select international brands a single point of entry into multiple Southeast Asian markets, Konvy can simplify expansion for brand owners. The firm claims it leverages proprietary consumer insights to help partners grow efficiently. If true, those insights, not just stock and channels, will be the sustainable moat.

Competitive landscape: crowded and fast-moving

Konvy is not the only player racing to aggregate beauty demand in Southeast Asia. Regional marketplaces, global platforms and a wave of vertical-first startups are all vying for consumers’ attention. Social commerce specialists and live-streaming vendors add another layer of competition, particularly for trend-driven and lower-priced items.

To carve out a defensible position, Konvy will need to convert Thai dominance into durable network effects: exclusive brand relationships, loyal customer cohorts and logistics economies across borders. The CJF tie-up could help lock in supply-side advantages, but it will not shield Konvy from competition on pricing, speed and marketing innovation.

Capital allocation and execution risks

US$22 million provides runway, but expansion across multiple countries, scaling private labels and beefing up fulfilment are capital-intensive tasks. Konvy’s playbook will likely require spending on warehousing, local teams, regulatory compliance and marketing, especially in markets where brand recognition is low.

Also Read: Thai beauty e-commerce firm Konvy bags US$10M from Insignia Ventures

Execution risks include misreading local product-market fit, underinvesting in payments and returns infrastructure, and failing to recruit credible on-the-ground partners. Rapid geographic expansion has sunk many once-promising e-commerce plays; Konvy must balance ambition with disciplined market testing.

What success looks like

If Konvy hits its targets, the company could become the default gateway for Japanese beauty brands entering Southeast Asia, a position that would create recurring revenue streams from exclusive deals and private labels, plus valuable consumer data. That would also make Konvy an acquisition target for larger regional platforms or strategic investors seeking category-specific distribution assets.

But success is not guaranteed. The company must demonstrate that its Thai model translates to countries with different cultural tastes, spending power and commerce behaviours. The winning formula will likely combine bespoke local product mixes, aggressive social commerce strategies, and frictionless logistics for both B2C and B2B clients.

Strategic bet, not a fait accompli

Konvy’s Series B is a strategic bet: leverage Thai success, partner with a Japan-focused fund to secure supply, and expand where rising middle-class demand meets digital commerce opportunity. The US$22 million will buy time and capacity, but the real test comes in execution.

For Southeast Asia’s beauty ecosystem, the deal matters because it signals continuing consolidation and the increasing importance of curated, omnichannel distribution models. For Japanese brands, Konvy’s rise offers a plausible route into regional markets without the headaches of building local distribution from scratch. For competitors, it raises the stakes: the marketplace is getting more selective about which partners can translate local leadership into regional influence.

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There was no funding announcement. No government mandate. No corporate strategy deck. Just borrowed rooms, called in favours, and a recurring observation that Singapore’s AI builders had nowhere to collide.

That was the origin of 65labs, now Singapore’s largest grassroots AI builder community with more than 5,000 members. Since its founding, the community has outgrown every venue it has ever been given. This reveals that the demand for such a platform had always been there; what was missing was the occasion.

“The gap was infrastructure,” says Sherry Jiang, co-founder of 65labs and CEO of AI finance startup Peek, in an email interview with e27. “The invisible machinery that Silicon Valley has built over decades — the third spaces, the casual collisions, the culture of showing up for each other without an agenda. Singapore didn’t have enough of it. So we started building some.”

What makes 65labs genuinely unusual is who is running it. Every co-founder holds a full-time role elsewhere. The community is built in the margins: between jobs, on weekends, after hours.

Interestingly, this is not seen as a limitation. Instead, Jiang argues that it is the point.

“Grassroots means you don’t wait for permission,” Jiang says. “No one handed us a mandate or a curriculum. We saw a gap and started filling it.”

Also Read: Konvy bags US$22M to bring more Japanese beauty brands into SEA

In practice, that philosophy shapes everything about how 65labs operates. There are no certifications, no headcounts reported upward, and no KPIs tied to a government grant. The community programmes from the bottom up, watching what questions its members are actually asking, which problems they are stuck on, and building events around that signal.

The people who turn up reflect that approach. Agrim Singh, a co-founder of the 65Labs community who is also the CTO and co-founder of Niyam AI, describes the range as genuinely surprising: NUS and NTU students at their first technical event sitting next to engineers with three decades of experience; a father who arrived at a 24-hour hackathon with his two teenage children and competed alongside seasoned founders; mid-career professionals from finance, law, and healthcare using 65labs as an on-ramp for reorienting their careers around AI.

“What they have in common is that they’re not here to talk about AI,” Singh says. “They’re here to build with it.”

No panels, no speculation

65labs made a deliberate early decision about which events it would and would not run. No panels where people speculate about AI’s future or keynotes from people who are not close to the work. If you take the stage at a 65labs event, you are showing something you actually built: what worked, what broke, what you would do differently.

“That standard filters the room naturally,” Singh says. “People who come to be seen at an AI event stop coming after the first one. People who come to learn and build keep coming back.”

The results of that filter have been visible enough to attract serious outside attention. OpenAI chose 65labs to run its first official Codex hackathon in Singapore. Cursor held its first Singapore event through the community. And now, 65labs is hosting AI Engineer World’s Fair — the world’s leading conference for AI engineers, backed by OpenAI, Google DeepMind, Cursor, Vercel and Z.ai — when it makes its first-ever Asia stop in Singapore from May 15 to 17.

Also Read: Hiring creatives in the AI age: Skills over titles

Singapore’s unique position

Jiang draws a sharp distinction between what 65labs is building and what top-down initiatives can offer. She invokes an unlikely historical parallel: the Homebrew Computer Club, the garage gathering founded in 1975, where a then-unknown engineer named Steve Wozniak first showed up and went home to begin designing what became the Apple I. The club never had more than a few hundred members, but its cultural legacy is incalculable.

“That’s what grassroots actually means,” she says. “The room exists because we built it. Everyone in it chose to be there.”

Singapore’s geographic and political position, she argues, makes 65labs something more than a local success story. Unlike San Francisco, which she describes as a cultural silo that exports ideas more readily than it imports them, Singapore is structurally wired to look both ways: East and West, emerging markets and developed markets, consumer and enterprise.

“The builders here are naturally exposed to product principles and engineering approaches that have worked across wildly different contexts,” she says. “Western companies are starting to recognise this. They’re not just coming to broadcast. They genuinely want to understand how different markets are solving problems they haven’t cracked yet. That curiosity is new.”

As 65labs scales, its co-founders are clear-eyed about the risks. Singh names integrity as the hardest thing to preserve, the slow erosion that comes from individually defensible decisions that accumulate into something unrecognisable.

“Every community that has lost its culture has lost it the same way,” he says. “We think about that a lot.”

The marker of success they keep returning to is deceptively simple: are the people who showed up before anyone was watching still in the room?

For now, they are. And the room, as ever, is full.

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Image Credit: Nicholas Cheng (VideoPulse.io)

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Many of us are already buying life in pieces. We ride-share instead of owning a car, rent co-working desks rather than committing to a long-term lease, and use cloud storage instead of a server. You don’t buy an entire cow to enjoy a glass of milk, and the same goes for markets.

Fractional investing, which allows an investor to buy a portion of a unit in a share or ETF as opposed to a whole share, can help investors turn spare change into market exposure. It helps level the playing field, as it turns markets from something reserved for those with six-figure salaries into something anyone can participate in. 

More than just lowering barriers, fractions change the way people think about money. Every small order becomes a building block and a step forward, and accessibility, affordability and diversification stop being abstract concepts and start becoming part of everyday investing. They’re very useful for building the right mix, but still, fractional investing can be risky if it leads to lots of small buys without a plan.

An affordable entry point into capital markets

For young investors and fresh graduates, fractional investing can be their first real entry point into capital markets. Instead of waiting years to build a large lump sum, they can start with a small amount and still own a slice of global companies or funds. Fractions remove arbitrary minimums and let people size positions to conviction, not to whatever one full share costs. 

Also Read: Digital wealth platforms hit scale in SEA as foreign investing apps outgrow local rivals

This accessibility matters as it helps turn investing from an intimidating task into a habit that grows with an investor’s income. Fractional investing is also an affordable way for investors to build exposure with just a few spare dollars each month, as exposure can be built step by step and scaled up over time. Instead of chasing cheap stocks to build a portfolio as quickly as possible, new and less experienced investors can use fractions to steadily shape a portfolio that matches their priorities and long-term plans without committing to whole shares. 

An opportunity to dip into inaccessible assets

Fractional investing is a great way to ease into big-ticket names that would otherwise be out of reach. An example would be Berkshire Hathaway’s Class A shares, which have never been split and still trade at hundreds of thousands of US dollars each (not to be confused with its more affordable Class B shares). As another example, many of us might be familiar with Booking.com, a go-to travel platform, whose parent company Booking Holdings trades above US$5,000 per share. With fractions, investors can start small in such stocks without breaking the bank.

Fractions can also serve as a way to “test the waters” with new ideas. By trying a small position first to see how it behaves and then scaling up only if it fits the plan, this can help investors to grow their confidence gradually, instead of rushing into trades they may not be ready for.

Diversification remains key

The catch is that while fractions make investing easier to start, they don’t remove the need for discipline. The risk is less about the tool itself and more about how people use it. Think of it like cai png (economy rice): you could take five scoops, but if they’re all meat dishes, you haven’t built a balanced meal, just different forms of the same thing. Diversification means mixing in some vegetables, tofu, or maybe even a fish dish. 

Also Read: From clicks to conversations: Why your next customer in Southeast Asia is an AI agent

In markets, US$30 across five tickers can look like a variety, but if they’re all the same theme (such as US mega-cap tech), you’ve built a single-factor bet with extra steps. The rules don’t change just because the tickets are smaller. After all, a risky company is still risky, and a well-diversified fund is still exactly that. 

For Singaporeans, the hard part isn’t access to investing, but how we assemble and maintain our portfolios. We like to say we’re kiasu and overly cautious, but the numbers tell a different story. Many Singaporeans are running barbell portfolios — very safe on one end and very bold on the other. What’s really missing is the middle: a steady, diversified core that compounds quietly. 

Fractional investing can help fill this middle without turning investing into a second job. Put simply, the edge isn’t finding the next big thing; it’s building a middle that survives the quiet, ordinary months. Decide the mix, set a monthly routine, review on schedule, fine-tune as you go, and ignore the noise in between. Let the fractions do the quiet work while you get on with the things that matter the most. 

The views and opinions expressed are solely those of the author and do not constitute financial, investment, or professional advice.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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In the business cycles of the past, obsolescence was a slow process. A factory or a retail chain had decades to depreciate its assets before a competitor rendered them irrelevant. But in April 2026, the timeline of decay has collapsed. We are living in the era of the velocity of obsolescence.

For the modern enterprise, the most dangerous line item on the balance sheet isn’t debt to a bank—it is technical debt disguised as innovation. As a founder who spends my days dissecting Enterprise Risk Management (ERM) systems, I see a recurring pattern: companies rushing to integrate agentic AI and hyper-automation on top of brittle, legacy foundations. They are building skyscrapers on top of 19th-century plumbing. In 2026, this isn’t just an IT headache; it is a macroeconomic risk that can wipe out market caps overnight.

The fragility of the AI wrapper

The last two years saw a gold rush of startups and enterprise features that were essentially wrappers around global AI models. At the time, it looked like rapid innovation. Today, it looks like a liability.

If your enterprise’s core intelligence is dependent on a third-party API that you don’t control, you have no moat. More importantly, you have no architectural resilience. When those underlying models update, pivot, or change their security protocols, your innovative feature breaks.

The risk here is systemic dependency. True enterprise SaaS in 2026 must be modular. It must allow you to swap your intelligence layer without tearing down your operational layer. At Prospero, we call this model-agnostic risk management. It’s the only way to ensure that your software doesn’t become obsolete the moment the next version of an LLM is released.

Identity as the new perimeter

In 2026, the network perimeter is dead. With the rise of remote work and decentralised AI agents, you can no longer protect your enterprise with a simple firewall. The new perimeter is identity.

Many enterprises are still struggling with fragmented identity systems. They have separate logins for their CRM, their HRIS, and their Risk Management tools. This fragmentation is a massive operational risk. A robust enterprise architecture requires a single source of truth for identity.

Also Read: Technology debt is the risk company boards keep deferring – until it becomes a crisis

This is why we obsess over seamless integration with protocols like LDAP and Keycloak. If your identity management isn’t integrated into your risk engine, you cannot automate safely. An autonomous AI agent is only as safe as the permissions it inherits. Without a unified identity layer, you are giving a “digital employee” the keys to the castle without knowing which doors they are opening.

The legacy AI crisis

We are now seeing the first wave of legacy AI—systems built in the 2023-2024 hype cycle that are now unmaintainable. They were built for demos, not for durability.

The risk of Legacy AI is twofold:

• Data toxicity: AI models trained on unvetted or biased data that now produce hallucinations in critical risk reports.
• Code bloat: Custom-built AI features that are so deeply hard-coded into the system that they cannot be updated without breaking the entire Enterprise Resource Planning (ERP) stack.

This is why security-by-design is the only sustainable path. Risk management shouldn’t be a module you “add” to your software; it should be the framework upon which the software is built. If risk isn’t in the code, it isn’t in the company.

Macro-implications: The cost of inflexibility

From a regional perspective, the companies that will lead ASEAN in the next five years are the ones that can pivot their business models in weeks, not years.

Also Read: Atome lines up US$345M debt as Southeast Asia fintechs shun equity

If your technical architecture is a monolith of technical debt, you are macro-inflexible. You cannot respond to new OJK regulations in Indonesia, you cannot integrate with the latest regional payment systems in Singapore, and you cannot scale your risk protocols to a new market.

In 2026, inflexibility = insolvency. The market is moving too fast for companies that are held back by their own legacy software.

Closing thoughts: Building foundations, not just features

The message to the community is a call for architectural rigour. As founders and leaders, we must resist the temptation to ship flashy features that add to our technical debt. Instead, we must invest in the boring, difficult, but essential work of building integrated enterprise foundations.

We need systems that are modular, sovereign, and identity-centric. We need risk management that is baked into the architecture, not slapped on as a post-script.

The winners of 2026 won’t be the ones with the most AI bells and whistles. They will be the ones who built antifragile systems—platforms that can evolve as fast as the market, secure as an army, and transparent as a glasshouse.

Stop building for the demo. Start building for the decade.

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

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I did not have a big “AI moment.” No dramatic reveal. No boardroom decision where we said, “Alright, let’s replace this role with AI.”

It was quieter than that. Started with something small like scheduling.

At one point, we were juggling multiple client calls across different markets, time zones, and team members. It sounds simple, but it wasn’t. Back-and-forth emails, missed slots, reschedules, overlaps. It took time. And more importantly, it took attention.

So we tried using an AI-powered scheduling assistant. Nothing fancy. Just something to handle availability, propose slots, send confirmations, and follow up if needed.

And within a week, that task was gone from our daily thinking.

No one needed to “own” scheduling anymore. It just… happened.

That was the first moment it hit me. Not in a scary way, but in a very practical one. Something we had assumed required a human, such as coordination, communication, and judgment, was now being handled well enough by a system.

Not perfectly. But well enough that we didn’t feel the need to step in.

That’s when the question shifted.

It wasn’t “can AI do this?”

It became “how many things like this exist in our business?”

We started experimenting more intentionally after that. Research was next. Instead of manually pulling together insights for proposals or campaigns, we used AI agents to gather initial data, summarise trends, and even suggest angles. Again, not perfect. But it reduced the starting friction.

Outreach followed. Drafting first-touch emails, structuring follow-ups, even suggesting subject lines. The team would still refine and personalise, but the heavy lifting was already done.

Reporting was another one. We tested workflows where AI could pull campaign data, summarise performance, and draft a readable report before a human ever touched it.

Individually, none of these felt groundbreaking.

But together, they added up to something bigger.

A layer of work, the kind that used to take a team’s time every single day, was quietly being absorbed.

What surprised me wasn’t just what AI could do. It was how quickly we adapted once we saw it working.

The initial hesitation wasn’t about capability. It was about trust.

The team didn’t push back because they were afraid of losing jobs. They hesitated because they weren’t sure where they fit in this new setup. If the system could draft, summarise, and coordinate, what was its role now?

Also Read: The hire you almost made: Why workflow outlasts hype

That’s something I had to address early.

We had to reframe how we saw work. The goal wasn’t to replace people. It was to remove the parts of the work that didn’t need their full attention.

Once that clicked, things changed.

People stopped seeing AI as something that takes away and started seeing it as something that gives back time, headspace, and energy.

But it wasn’t all smooth.

There were moments where AI fell short, and those moments mattered.

Context was the biggest gap.

AI could draft a decent outreach email, but it didn’t always understand nuance especially in B2B conversations where tone, timing, and relationship history matter. It could summarise data, but sometimes missed what was actually important.

And when things went wrong, they went wrong quietly.

That was the risk.

A human mistake is usually obvious. An AI mistake can look correct at a glance until it isn’t.

So we kept human checkpoints in place. Not because we didn’t trust the tools, but because we understood their limits.

Another thing we didn’t anticipate was the operational layer that came with it.

Someone had to think about prompts. Someone had to decide what “good output” looked like. Someone had to maintain consistency across tools.

AI didn’t remove management. It changed what needed managing.

If I’m being honest, the biggest shift wasn’t operational. It was mental.

It changed how I think about hiring.

A year ago, if we needed more output, the instinct was to hire. More clients meant more people. More work meant more hands.

Now, that assumption doesn’t hold the same weight.

If I were building a team from scratch today, I wouldn’t start by asking, “Who do I need?”

I’d start by asking, “What actually needs a human?”

Because not everything does.

The roles that feel most secure aren’t the ones tied to execution anymore. They’re the ones tied to thinking, judgment, relationships, and ownership.

Things that require context. Taste. Responsibility.

Everything else is… negotiable.

Also Read: Breaking barriers: Reimagining SME growth with practical AI strategies

And I don’t say that lightly.

I’ve built teams. I care about people. I understand what jobs mean beyond just output.

But ignoring this shift doesn’t protect anyone. It just delays the adjustment.

The reality is, AI agents are already here. Not as a concept, but as quiet operators inside workflows.

They’re not replacing entire teams overnight. But they are reshaping what teams need to look like.

Smaller. Sharper. More focused.

Less about doing everything manually, more about knowing what should be done manually.

If there’s one thing I’d say to another founder thinking about this, it’s this:

Don’t start with replacement. Start with relief.

Find the tasks your team quietly dreads. The repetitive ones. The ones that drain energy without adding much value.

That’s where AI fits best.

Not as a headline. Not as a strategy.

Just as a way to make work feel a little lighter.

And once you feel that shift, even in a small way, you start seeing your business differently.

Not everything needs a human.

But the things that do matter more than ever.

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