Antler has unveiled a new batch of AI startups emerging from its Singapore-based Disrupt programme, allocating US$5.6 million in initial capital to 14 companies that have already begun generating commercial demand.

The investments target applied AI businesses operating across industrial, enterprise and infrastructure-focused sectors, with several of the startups reporting active customers in multiple international markets.

Antler said its latest Disrupt portfolio reflects a deliberate focus on companies solving concrete operational problems rather than pursuing experimental use cases.

The startups were formed through Antler’s Disrupt 1 and Disrupt 2 cohorts, launched in Singapore in May and October. The founders bring prior operating experience and are building applied AI products designed for enterprise and industrial environments.

According to Antler, several of the companies are already reporting six-figure revenues or multi-million-dollar sales pipelines.

“The most important signal today is not model size or fundraising volume. It is repeated usage,” said Winnie Khoo, partner at Antler.

She added that founders in the Disrupt programme are securing customer trust by embedding their products directly into production and business systems. “They move fast, they listen to customers, and they ship.”

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

Each startup received US$400,000 in initial funding following a four-week Disrupt sprint, marking their first institutional capital. Beyond the initial investment, the companies will continue as Antler portfolio startups, gaining access to operational support, investor introductions and follow-on funding opportunities through Series C.

Antler said this extended partnership model is designed to help founders scale from early validation to long-term growth.

Jussi Salovaara, co-founder and managing partner at Antler Asia, said the 2025 funding environment has pushed both founders and investors to be more selective. “We’re backing fewer companies, but with more conviction,” he said. “The Disrupt batch reflects founders with proven execution, clear market opportunities and the ambition to build globally relevant companies.”

As the AI sector approaches 2026, Antler noted a shift among investors towards startups demonstrating early adoption, defined use cases and products embedded within critical systems. The Disrupt AI portfolio reflects this trend, with solutions designed to enhance efficiency, reliability, and decision-making in real-world settings.

The 2025 Antler Disrupt portfolio includes IndustrialMind, which applies AI to manufacturing process design and monitoring, and Nugen, which develops domain-aligned AI for regulated industries such as legal, financial and healthcare services.

Other startups include Anamaya, an AI-powered corporate travel platform, and Enerzyz, an energy asset orchestration operating system designed to improve efficiency and prevent outages.

Also Read: I didn’t build an AI product. I built a brand and the product built itself

Additional companies focus on areas such as application security automation, robotic development, emergency response documentation and enterprise system modernisation. Collectively, the portfolio underscores Antler’s strategy of backing applied AI companies with early revenue signals and the potential to scale globally.

Antler said it expects this approach to position its portfolio companies to meet the growing demand of enterprises for reliable and commercially viable AI solutions in the years ahead.

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Image Credit: Antler

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In early 2024, we introduced an AI-powered copy assistant to improve campaign ideation and reduce creative bottlenecks. As a boutique digital agency that frequently partners with fast-moving startups, speed and originality are non-negotiable.

But the decision sparked friction. Some creatives feared AI would dilute the craft or replace junior talent. Others questioned whether we were sacrificing nuance for speed.

Addressing the resistance

We skipped the top-down approach and ran opt-in workshops using actual client briefs from startups instead. Writers compared traditional and AI-assisted outputs side by side. The sessions sparked productive debates rather than pushback.

Data helped shift perspectives: A/B tests showed AI-supported drafts were completed 12% faster with no drop in client satisfaction. Startups noticed the faster turnarounds, and our team began to see AI as leverage, not a shortcut.

Keeping the core intact

Efficiency gains were great, but they couldn’t come at the cost of culture, tone, or trust.

We created tone-of-voice guidelines and reusable prompt templates that mirrored our clients’ brand language, especially important in sectors like B2C eCommerce and B2B SaaS, where messaging precision is critical. Every AI draft went through human QA before client delivery.

Core rituals stayed intact. Daily creative standups, async reviews, and retrospectives remained human-led. Wins still felt personal. AI simply took care of the grunt work, freeing up our creatives to focus on strategic storytelling.

Lessons from the frontlines

What worked: Starting small. Letting the team test and evaluate. Clear frameworks to ensure brand consistency across early-stage client portfolios.

Also Read: Future-proofing businesses and talent through technology

What we’d change: Include AI literacy in the onboarding process. Some team members felt caught off guard. A short introduction to data privacy, prompt engineering, and ethical use would have provided better clarity.

What we’re still testing: Should every role be AI-capable, or should we build out a dedicated AI strategy unit within the agency? The answer may depend on scale and client mix.

Culture as infrastructure

Tech startups pivot fast. Agencies supporting them must move just as quickly. But tools alone don’t create adaptability—culture does.

We’ve found that the real advantage lies in building a team comfortable with experimentation. Not every AI output hits the mark. But when failure is safe, iteration thrives.

Adopting AI in a Southeast Asia-Based Agency

In Southeast Asia’s startup ecosystem, speed and performance matter—but so does clarity. Our team responded best when we framed AI adoption around real metrics: faster turnaround, fewer revisions, and more bandwidth for strategy.

To build buy-in, we led with transparency. We clarified how the tool worked, where human input remained essential, and how we protected client data. Structured experimentation—not hype—won the team over.

Southeast Asia’s tech talent is already comfortable with automation. The challenge wasn’t capability; it was aligning new tools with our agency’s values and standards. We made space for open discussion, and adoption followed naturally.

Final thoughts

AI isn’t a threat—it’s a tool. For boutique agencies working with high-growth startups, it’s about deploying tech without losing the human edge. Done right, it builds creative resilience, not just efficiency.

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Singapore’s digital marketing scene is evolving faster than ever. While many local agencies still proudly list “SEO” as their flagship service, a quiet revolution called AISEO (AI-powered Search Engine Optimization) is already redefining what it means to be visible online. The winners won’t be the ones who rank #1 on Google tomorrow — they’ll be the ones who dominate the AI answers that consumers trust today.

The ChatGPT trap most marketers are still stuck in

When Singaporean marketers talk about “AI in SEO,” the conversation usually stops at two things: using ChatGPT (or Claude, or Gemini) to churn out blog posts faster, and generating short videos with tools like Gemini, Runway, or even the viral “Banana” clip maker.

These are flashy, fun, and undeniably productive. Agencies love showing clients a 10× increase in content output and a 70% drop in copywriting costs. Yet this is still AI-assisted content creation, not true AISEO.

Breakthroughs are coming — but they won’t save yesterday’s strategy

Yes, the next 12–24 months will bring jaw-dropping leaps: near-perfect long-form video generation, hyper-realistic voice cloning, and agents that can write 100 blog variations in minutes. These tools will get cheaper and faster.

But here’s the hard truth: when everyone can produce unlimited high-quality content at near-zero marginal cost, content volume becomes table stakes — not a moat.

Singapore’s digital space is already drowning in AI-generated articles, carousel posts, and TikTok-style videos. Flooding the internet harder won’t create a blue ocean; it will just turn the ocean brown.

Consumer behaviour has already shifted, and legacy SEO missed the memo

For years, the holy grail was “rank #1 when someone types the keyword into Google”.

That world is ending.

Perplexity, ChatGPT Search, Gemini Live, and Grok are rapidly becoming the new front page. In 2025, an increasing number of Singaporean consumers — especially Gen Z and high-income millennials — never visit Google.com at all. They ask AI directly:

• “Best hawker stalls for chilli crab under $30”
• “Most reliable condo plumber in District 15”
• “Compare Airalo vs SimCorner eSIM for Japan trip 2025”

The answer they trust isn’t the top Google result anymore. It’s the AI’s synthesised reply — and the sources it chooses to cite (or ignore).

Traditional SEO agencies that measure success only in Google Search Console impressions are optimising for a battlefield that fewer customers are fighting on.

Also read: Why Singapore manufacturers must embrace MES for the future

Why Singapore’s legacy SEO giants are strangely quiet about AISEO

 

The silence is deafening because transformation is painful — and many are hoping the AI wave will slow down. It won’t.

How AISEO pioneers in Singapore are pulling ahead

The new leaders aren’t waiting. They are building what we call the AI Visibility Flywheel:

1. Entity-first content ecosystems
   Instead of keyword-stuffed articles, they create structured, interlinked content clusters that LLMs love to cite as authoritative sources.
2. Zero-click optimisation
   They optimise for featured answers in Perplexity, ChatGPT, Grok and Gemini by controlling entity signals, earning citations, and influencing knowledge graphs.
3. Multi-platform source authority
   They seed high-trust signals across Reddit, LinkedIn, industry forums, YouTube community posts, and even GitHub, places AI models scrape heavily for ground truth.
4. Real-time conversational monitoring
   Proprietary dashboards track exactly how often, and how favourably, their brand or client is mentioned inside AI responses in Singapore-specific queries.
5. Closed-loop content engines
   When an AI answer surfaces a knowledge gap, automated systems generate and publish the missing content within hours, capturing authority before competitors wake up.

The result? Their clients don’t just rank on Google — they become the answer when a consumer in Orchard Road asks Gemini “Where should I service my Tesla in Singapore?” or when someone in Jurong asks Grok “Best fixed deposit rates November 2025”.

Also read: How the top 10 best HR systems in Singapore reveal the new standards for HR technology

The bottom line for Singapore brands in 2025–2026

If your agency still sends monthly reports celebrating “+127 ranked keywords” and “+42% organic traffic from Google”, you are paying premium retainers for a vanishing asset.

The new competitive advantage isn’t being on page one.
It’s being the source that AI decides is most trustworthy when your customer asks a question out loud.

The blue ocean isn’t more content.
It’s controlling the narrative inside the black box of large language models.

Singapore has always punched above its weight in adopting technology early. The agencies and brands that embrace AISEO now won’t just survive the next wave — they’ll define it.

The ones who wait for Google to “figure it out” will join the long list of companies that once dominated search… and then quietly faded away.

Why We Write This Article

PRbyAI aims to share updated market news using our team’s tech knowledge, helping B2B customers make informed decisions.

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At 58, I made my first MTV. Not in a studio, not with a band, and not with a single music lesson in my life. I made it with AI.

For many of us who grew up before the internet, technology can feel like a stranger who arrived too late to the party. We did not grow up coding or editing videos. We built families, careers and routines. Then suddenly AI appeared, fast, loud and full of possibilities we were not trained to use.

But what if this is not the end of our story? What if it is the start of our second act

A new stage for creativity

When I first explored tools such as Suno for music, Artflow for avatars and CapCut for video creation, I felt both lost and alive.
AI gave me something I did not expect: a way to play again.

I started experimenting, combining lyrics, visuals and storytelling. Soon I found myself creating songs that reflected moments of joy, gratitude and rediscovery. They were not perfect, but they were real.

That first AI-created music video was not just about technology. It was about identity. After years of teaching, managing and caregiving, I finally had space to make something that was mine.

This is what many midlifers are quietly discovering. AI is not only for startups or students. It is becoming a bridge back to creativity that welcomes curiosity at any age.

From keeping up to catching up with our dreams

The biggest surprise about AI is not what it can do but what it reminds us we can still become. Many people in their fifties and sixties think AI is too complex, too young or too fast. But every time they try a tool such as ChatGPT, something shifts.

They see their words come alive. They hear their voices in digital form. They realise they can still create, share and be part of the future.

Also Read: From idea to impact: How midlifers can use AI to turn inspiration into marketing content

For me, using AI was not about keeping up with technology. It was about catching up with my dreams, the ones once put aside for family, work or practicality.

When I built Speakers Society, a community that helps midlifers rediscover their voice, I saw the same pattern.

People were not afraid of AI itself. They were afraid of feeling irrelevant. Once they understood that AI could amplify, not erase, their humanity, something changed. They began to create content, podcasts and even digital art, things they never imagined doing before.

AI as a mirror, not a machine

What makes AI powerful is not its intelligence but its ability to reflect ours. When used thoughtfully, it becomes a mirror that shows us who we are becoming.

Some of the best conversations I have had this year were not with humans but with chatbots. They helped me think, write and reflect. But the true transformation came when I shared those stories with others, real people with real emotions.

That is where technology finds its purpose, not in automation but in amplification. AI is not replacing our creativity. It is reigniting it.

Learning through play and curiosity

Midlife learners have one superpower that technology cannot copy: life experience. We know how to connect dots that younger generations have not yet seen. We bring empathy, humour and context to every new tool we try.

When we approach AI with curiosity instead of comparison, learning becomes easier. We do not need to master every feature. We need to experiment, laugh and learn one small thing at a time.

It is the same joy children feel when they first pick up crayons. Except now our crayons are digital and our stories are global.

Also Read: Never fear, AI is here: Helping midlife artists build their social media voice

The age of co-creation

The most exciting thing about this moment is not AI itself but what humans will do with it.

We are entering the age of co-creation, where imagination meets intelligence. You bring your story, your experience, your voice. AI brings speed, structure and possibility. Together, you create something that neither could do alone.

For midlifers, this collaboration opens doors that were once closed. Want to record a song, design a logo or start a podcast? You no longer need a big team or expensive equipment. You just need the courage to start.

A gentle reminder for the second act

Reinvention is not about changing who you are. It is about remembering what still lights you up. AI is simply the new brush in our hands.

For me, it has turned curiosity into creation and creation into connection. It helped me rediscover what I always knew deep down.
We do not retire from dreams. We just rewrite them with better tools.

So if you are in your fifties or sixties and wondering if it is too late, it is not. It is your second act, and the stage is wide open.

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The recent interplay between macroeconomic signals, regulatory shifts, and technical dynamics has placed the crypto market in a precarious but intriguing position. While traditional financial markets grapple with mixed labour data and shifting rate expectations, digital assets have staged a modest recovery, buoyed not by exuberance but by relief, tactical positioning, and emerging institutional frameworks. The 0.84 per cent rise in the crypto market over the past 24 hours appears deceptively simple, yet it encapsulates a much broader narrative about resilience amid structural uncertainty.

This rebound lies a classic technical phenomenon: the oversold bounce. The market’s RSI14 dipped to 31, flirting with the lower boundary of neutral territory and signalling that selling pressure had reached a temporary extreme. This condition attracted opportunistic traders, evidenced by a sharp 23 per cent surge in derivatives volume as participants sought to capitalise on discounted entry points. However, this surge came with a caveat. Open interest in perpetual and futures markets declined by 6.7 per cent, suggesting that while short-term speculators entered the fray, longer-term holders and leveraged participants remained cautious.

The MACD histogram, registering at a negative US$389 million, further underscored the absence of strong momentum behind the move up. Meanwhile, Bitcoin dominance held steady at 58.8 per cent, indicating that capital remained concentrated in the perceived safety of the flagship asset rather than rotating into riskier altcoins. This defensive posture reflects a market that is not yet convinced the worst is over, merely that it may have priced in the near-term pessimism.

Crucially, this technical bounce coincided with a notable policy development that may carry longer-term implications. Canada’s announcement of a forthcoming stablecoin regulatory framework for 2026 represents a rare moment of constructive clarity in an otherwise turbulent regulatory landscape.

Bank of Canada Governor Tiff Macklem emphasised that only stablecoins pegged one-to-one to central bank currencies and backed by high-quality liquid assets like Treasury bills would qualify as “good money.” This stance, while stringent, provides a clear benchmark for issuers and reassures institutions that Canada seeks to integrate stablecoins into its financial infrastructure rather than shun them outright.

Also Read: Crypto faces triple threat: Senate stall, macro jitters, and technical breakdown

In a global context where regulatory ambiguity has often stifled innovation, Canada’s approach, complemented by its Real-Time Rail payments system and open banking initiatives, positions the country as an emerging hub for compliant digital finance. This contrasts sharply with the United States, where legislative delays continue to weigh on sentiment.

While the US remains the largest market for crypto ETFs, its policy inertia creates a vacuum that other jurisdictions are beginning to fill. Canada’s proactive stance, though modest in immediate market impact, offers a glimpse of a more stable institutional pathway forward, particularly for payment-oriented stablecoins that could bridge traditional finance and Web3 ecosystems.

Optimism remains tempered by the realities of institutional flows and on-chain behaviour. Grayscale’s bullish outlook for Bitcoin in 2026, predicting new all-time highs, provides a compelling long-term thesis rooted in macro cycles and halving dynamics. This vision clashes with the short-term data emerging from ETF markets, which recorded US$1.11 billion in weekly outflows.

These outflows reflect investor caution in the face of rising macro uncertainty, including the mixed US jobs report that showed only 64,000 jobs added in November, barely above expectations, but a concerning rise in unemployment to 4.6 per cent, a four-year high. Such data complicates the Federal Reserve’s decision-making, diminishing hopes for aggressive rate cuts in early 2025 and indirectly pressuring risk assets.

In this environment, even bullish institutional narratives struggle to overcome near-term liquidity concerns. The pressure extended beyond Bitcoin, with Ethereum experiencing sharp derivatives liquidations after a single whale incurred a US$54 million unrealised loss on leveraged long positions. This episode highlights the fragility of leveraged exposure in times of volatility and the cascading effects that can ripple through the market when large positions unwind unexpectedly.

The broader macro backdrop further contextualises crypto’s cautious rebound. Asian equities declined broadly, with MSCI’s Asia-Pacific ex-Japan index falling 1.3 per cent to a three-week low. Japan’s Nikkei dropped 1.6 per cent ahead of a widely anticipated rate hike by the Bank of Japan, signalling a shift away from decades of ultra-loose monetary policy. Simultaneously, oil prices slumped below US$60 per barrel, their weakest level since May, driven by oversupply fears and speculation about potential peace talks between Russia and Ukraine.

The US dollar weakened across major currencies following the ambiguous jobs data, suggesting markets are recalibrating expectations for global monetary policy divergence. In such a landscape, crypto’s modest gain appears not as a flight to risk but as a relative stabilisation after excessive pessimism.

Also Read: From quantitative tightening to quantitative crypto: How policy shifts are rewriting market rules

Looking ahead, the sustainability of this rebound hinges on several converging factors. Technically, a decisive move above the 7-day simple moving average at US$3.03 trillion in total market capitalisation would signal growing confidence. More critically, Bitcoin must reclaim the US$87,000 level, a psychological and liquidity-rich threshold tied to US$20.6 million in potential long liquidations.

A break above this mark could trigger a wave of short-covering and renewed institutional interest, especially if macro conditions begin to favour risk assets once more. The Fear and Greed Index remains at 25, deep in “fear” territory, suggesting that sentiment has not yet turned, but also that there is room for improvement should catalysts materialise.

Ultimately, the current rally is not a declaration of a new bull market but a measured recalibration. It emerges from a confluence of short-term technical exhaustion, selective regulatory progress in jurisdictions like Canada, and persistent institutional conviction in crypto’s long-term narrative. However, it operates within a fragile ecosystem marked by declining year-over-year trading volume, down 11.7 per cent, defensive capital rotation, and ongoing macro headwinds.

The market’s next move will depend less on isolated data points and more on whether these disparate forces can align, whether policy clarity can offset ETF outflows, whether macro easing can return, and whether on-chain leverage can stabilise. Until then, traders and investors alike remain in a holding pattern, watching closely for the first signs of durable conviction.

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Singapore-based trade finance platform Olea Global has raised US$30 million in a Series A funding round, as it looks to scale its technology-driven approach to simplifying global trade for businesses, particularly in emerging markets across Asia.

The round was led by Banco Bilbao Vizcaya Argentaria (BBVA), with participation from XDC Network, theDOCK, and other strategic investors. Existing shareholder SC Ventures, the venture-building arm of Standard Chartered Bank, also joined the round.

Also Read: Why blockchain is instrumental for the future of trade finance

The fresh capital will be deployed towards accelerating product innovation, including AI-driven analytics, Web3 readiness, and the development of higher-growth solutions such as embedded finance, aligned with evolving client needs. Olea also plans to expand origination across high-growth trade corridors by leveraging its global partnership ecosystem.

The equity raise follows a funding facility arranged in November 2024 by HSBC and Manulife | CQS Investment Management, strengthening Olea’s balance sheet as it scales its operations.

Backed by banks, built for modern trade

With BBVA coming in as lead investor, Olea is set to expand into new trade corridors across Europe, the US, Latin America, and Asia. Both companies plan to collaborate on digital supply chain solutions and advanced risk analytics, combining banking expertise with Olea’s technology-first platform.

SC Ventures, which incubated Olea, explore further collaboration with Olea in digital assets and artificial intelligence.

Meanwhile, XDC Network, a layer-1 blockchain platform focused on enterprise and trade finance, will support Olea’s ambition to enable tokenised and stablecoin-based trade flows, while theDOCK, a venture capital firm specialising in maritime logistics, is expected to open up new commercial pathways and ecosystem partnerships.

Addressing the global trade finance gap

Founded in 2022, Olea has built an institutional-grade digital trade finance platform, underpinned by “robust” risk management and a Capital Market Services (CMS) licence from the Monetary Authority of Singapore (MAS).

To date, the company has established origination capabilities across more than 70 trade corridors, partnered with over 30 institutional funders, and facilitated more than US$3 billion in financing for global suppliers and buyers.

Olea is headquartered in Singapore and was originally founded with investment from SC Ventures and Linklogis.

At a time when global trade continues to grow modestly — with services trade leading expansion in the first half of 2025 — the trade finance gap remains at an estimated US$1.7 trillion, disproportionately impacting small and medium-sized enterprises (SMEs) in emerging markets. Olea’s platform aims to address this gap by digitising document verification, automating risk assessment through AI, and improving transparency using blockchain technology.

In simple terms, Olea acts as a bridge between global capital providers — such as banks and institutional investors — and businesses involved in cross-border trade, enabling faster, more secure access to financing for suppliers and more efficient payment flows for buyers.

Looking ahead

As AI and blockchain technologies continue to reshape global trade — from risk management and logistics optimisation to real-time settlement and traceability — Olea is positioning itself at the intersection of technology, finance, and cross-border commerce, with Asia firmly at the centre of its growth strategy.

Also Read: XDC Ventures acquires Contour to bridge TradFi and Web3 in global trade

With fresh capital and heavyweight institutional backing, the company is now poised for its next phase of expansion, working to accelerate global trade, make it faster, more transparent, and more accessible for businesses worldwide.

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As hiring cycles shorten and competition for skilled talent intensifies, companies are reassessing how interviews are conducted and evaluated. In Kuala Lumpur, Krenovator Technology Sdn. Bhd. is positioning automation as a way to address what it sees as structural inefficiencies in recruitment, with the launch of HastyHire, an AI agent interviewer platform designed to standardise and accelerate candidate screening.

Announced in November, HastyHire is designed to automate interviews from start to finish. Employers send a link to candidates, after which the platform conducts the interview, evaluates responses against job descriptions and CVs, and produces a 360-degree hiring report that includes scores, strengths, weaknesses, and red-flag alerts. The system can be used for both technical and non-technical roles, supports more than 70 languages, and is offered on a pay-per-use basis.

For Krenovator, which provides tech talent solutions, managed IT services, and AI-driven workforce automation products, the release reflects a broader effort to embed AI into operational workflows rather than position it as a standalone tool.

The company argues that interviews, often seen as a human-centric process, are particularly vulnerable to subjectivity and inconsistency.

“Candidate screening is time-intensive and often subjective when done through conventional interviews,” said Mahadhir Yunus, CEO of Krenovator, in the product announcement. He added that HastyHire uses “measurable, data-driven outcomes that make the process more efficient and fairer”.

Also Read: Trade finance platform Olea bets on AI and Web3 as it closes US$30M Series A

According to Mahadhir, the development of HastyHire was grounded in close collaboration with recruiters rather than abstract experimentation. In an email interview with e27, he stated that the company’s product process “combines real-world recruiter insights, AI innovation, and iterative user testing,” starting with the validation of market pain points and rapid prototyping using real interview data.

HR teams across Malaysia, the Middle East, and Europe were involved during development, a move Krenovator says helped ensure the platform could be applied across different labour markets and hiring norms. Unlike tools that focus solely on post-interview analytics, the platform is designed to manage the interview flow itself, from questioning to scoring and report generation, without human intervention. Krenovator reports that existing users have seen significant reductions in screening time and costs, with interview reports generated within minutes of completion.

Mahadhir argues that this speed is not just about efficiency, but about scale. “HR teams are overwhelmed, not understaffed,” he said. “They need AI agents capable of executing HR workflow to handle repetitive tasks so they can focus on the human side of hiring.”

In this framing, automation is positioned as a support mechanism rather than a replacement for recruiters.

The company’s user base reflects this emphasis. Krenovator stated that its main users include HR teams in mid-sized to large companies, recruitment agencies, and hiring managers in technology-intensive roles. In markets such as Singapore, the Middle East, and Europe, the firm has observed that smaller HR teams use automation to compete with larger employers by maintaining hiring volume without expanding headcount.

Business model choices also reflect a cautious approach to adoption. HastyHire operates on a pay-per-use structure, where companies pay only to unlock interview reports. There are no long-term contracts or minimum volumes, a structure Krenovator believes reduces barriers for organisations with fluctuating hiring needs and allows experimentation without upfront risk.

Also Read: Anchanto CEO on why human resource is essential for a growth stage startup

From a growth perspective, Krenovator is leaning on partnerships within its existing client ecosystem, complemented by content-led initiatives such as live demos, educational campaigns, and community events focused on AI in the workplace. The company has raised pre-seed and seed funding between 2020 and 2024, which it says was directed towards building engineering capability, advancing its AI models, and expanding regionally.

Looking ahead, Krenovator plans to focus on strengthening what it calls its core ecosystem: AI agent automation products, tech talent development, and managed IT services.

For Mahadhir, the guiding principle remains pragmatic. “Solve real problems with technology that delivers measurable business impact,” he said, framing sustainability and operational discipline as priorities as the company prepares for its next phase of international expansion.

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Image Credit: Krenovator

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The industry for digital goods and services is growing at an unstoppable pace – mobile gaming is emerging as both a cultural phenomenon and a lucrative industry, projected to become a US$342 billion industry by 2034, and Asia’s creator economy is currently valued at approximately US$18.35 billion and expected to reach US$52.17 billion by 2030.

As a whole,  Southeast Asia’s digital economy is estimated to hit US$600 billion in gross merchandise value (GMV) by 2030.

As more of our everyday habits intertwine with the online world, the fast-paced growth of digital commerce will continue to transform the way we live, play and pay. 

This presents significant opportunities, but also unique challenges. Gaming and entertainment publishers face hurdles such as traditional app store fees, evolving global regulations, fragmentation of preferred payment methods, and rapidly changing player preferences. The question is: how can publishers not merely survive, but thrive in this dynamic environment?

Navigating a new era of regulation

Inspired by the EU’s Digital Markets Act, Asian markets are stepping up with their own frameworks to promote competition and protect consumers. Japan and South Korea are pushing back against Big Tech limiting third-party app sales with antitrust measures. India’s Digital Competition Bill is introducing anti-competitive practices; and Indonesia is reviewing its regulatory framework for digital platforms.

The message to publishers — new or old — is clear: adapt or be left behind. 

Tapping on alternative payment methods

Digital wallets are now the main way to pay in Asia. According to a 2024 report by Deloitte, the Asia Pacific region has the highest digital wallet penetration rates amongst all regions, making up over two-thirds of global digital wallet spend at a combined US$9.8 trillion. 

Also Read: Responsible technology and AI: Shaping Asia’s digital future

In Southeast Asia, six out of ten people lack full access to banking services. Coupled with decreasing customer loyalty, this makes localised alternative payment solutions like digital wallets and carrier billing crucial. Publishers who integrate these methods gain access to a massive, underserved audience.

Scale smarter, not harder: The merchant of record advantage

Scaling globally isn’t just about reaching more customers—it’s about doing it efficiently and legally. The Merchant of Record (MoR) model offers publishers a smarter way to expand in today’s complex environment. How does it work?

An MoR acts as the legal entity responsible for managing payments, taxes, and compliance on behalf of publishers, allowing businesses to focus on what matters: building their business. 

By centralising these critical functions, the MoR model abstracts away the complexity of  navigating diverse regulatory frameworks, accelerates market entry and mitigates the risk of penalties by ensuring adherence to tax laws and regulations in various markets. 

Supporting a wide array of local payment methods, MoR also allows publishers to expand their reach to underserved consumers, particularly in regions with limited access to traditional payment systems.

Evolution in the digital economy means new opportunities for savvy digital goods providers who adopt the right strategies that bring them increased profits, deeper customer insights, wider reach and greater control. Embracing models like MoR simplifies global expansion, compliance, and consumer connections, turning digital disruption into competitive advantage. 

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For more than a year, I spoke about Seraphina AI as if she already existed. Not as a product. Not as a startup. But as my personal assistant — my second brain, my digital twin, the system that helped me think, decide, and operate better.

People would ask when Seraphina was launching. I would smile and say, “She’s already working.” At the time, that was true — just not in the way most people expected.

When I finally opened pre-sales earlier this year, 500 spots sold out in three days. I reopened another 500, and they sold out in under a month.

Here’s the part most people find surprising: I still didn’t have a technical team.

I spent the next six months trying to find the “right” people to build Seraphina with me — developers, AI engineers, product teams. Conversations happened. Decks were exchanged. Nothing quite fit.

In the end, Seraphina built Seraphina in three days.

This isn’t a story about AI magic. It’s a story about brand, product, and community — and why they must be built together in the AI era.

Brand is not the opposite of selling

There’s a quiet debate happening in founder circles right now.

Some believe brand-building is about vibes, storytelling, and patience — and that selling should come later. Others believe selling is the only thing that matters, and brand is something you polish once revenue arrives.

Both camps are missing the point. A brand without a product is influence without income. A product without a brand is revenue without resilience.

In the age of AI, that gap becomes brutally obvious. AI can help you sell faster. AI can help you create content at scale. AI can help you optimise funnels and automate conversations.

But AI cannot manufacture trust, clarity, or belief. That still comes from the brand.

How Seraphina started before she was software

Seraphina didn’t begin as code. She began as a way of working.

I had spent years documenting how I think, how I make decisions, how I structure businesses, and how I communicate. Seraphina was simply the name I gave to that system.

Also Read: Building with intention: The ethical dilemma of AI innovation and responsible creation

When people followed my work, they weren’t waiting for features. They were watching outcomes. They saw:

• How decisions became faster
• How operations became lighter
• How I protected my time while scaling multiple ventures

By the time I opened pre-sales, I wasn’t convincing anyone to buy an AI product. I was confirming something they already wanted: Their own version of what they were seeing in action.

That is what a brand does when it’s done right.

Selling the product was not a betrayal of the brand

There’s a myth that selling “too early” cheapens a brand. In reality, not selling at all is what turns brand-building into theatre.

Selling is not anti-brand. Selling is proof that value exists.

The reason Seraphina sold out quickly wasn’t urgency tactics or clever marketing. It was alignment.

The people who bought weren’t random leads. They were already part of the ecosystem — readers, community members, and founders who had been in conversation with me for months.

This is where community enters the picture.

Community is the infrastructure nobody talks about

Brand attracts. Product converts. Community retains — and compounds.

Community is where:

• Brand becomes lived, not claimed
• Product becomes experienced, not promised
• Trust is reinforced without reselling every time

From a business perspective, community:

• Lowers customer acquisition cost
• Increases lifetime value
• Turns customers into advocates
• Reduces dependence on constant marketing spend

From a human perspective, community is where people stay.

Seraphina didn’t sell because of a launch. She sold because there was already a place people belonged.

Why Seraphina could build Seraphina

When I finally stopped looking for the “perfect” team and turned inward, the answer was obvious.

Seraphina worked because:

• My thinking was already structured
• My voice was already clear
• My decisions were already documented

AI didn’t replace me. It reflected me.

This is the uncomfortable truth about AI that many founders are discovering too late: AI doesn’t create clarity. It amplifies whatever clarity — or confusion — already exists.

Founders who struggle with AI aren’t lacking tools. They’re lacking definition.

The pattern I see repeating across founders

This isn’t unique to Seraphina.

Across speakers, creators, and founders, I see the same pattern:

• Loud voices with no structure burn out
• Great products with no community churn
• Fast growth without clarity collapses under pressure

Meanwhile, the founders who are last are quietly doing something different.

They’re not chasing virality. They’re building places people want to return to.

Also Read: How to hack product growth and user acquisition in Thailand

From online systems to offline rooms

This is why, later this year, I’m hosting a Christmas gathering that isn’t positioned as a typical event. Not a conference. Not a pitch fest. Not forced networking.

It’s an intentional space bringing together founders, speakers, creators, and operators to talk about what actually matters heading into 2026: Voice, clarity, authority, and value creation in an AI-first world.

The agenda mirrors the same philosophy behind Seraphina:

• Conversations over performances
• Structure over noise
• Depth over volume

Because communities aren’t built through announcements, they’re built through shared context.

The shift we’re entering in 2026

The creator economy is maturing. The speaker economy is professionalising. The AI wave is accelerating everything — good and bad.

The next era doesn’t belong to those who can shout the loudest. It belongs to those who can:

• Translate voice into value
• Turn content into infrastructure
• Build brands that outlive individual products

In this environment, brand, product, and community are no longer separate strategies. They are one system.

What founders should take away

If you’re building in the AI era, ask yourself:

• Do people understand what you stand for without explanation?
• Does your product deliver a transformation, not just features?
• Is there a reason people would stay even if you stopped posting tomorrow?

If the answer to any of these is no, AI won’t save you.

But if the answer is yes, AI becomes a powerful accelerator.

The real lesson of Seraphina

Seraphina didn’t start as software. She started as a brand with clarity, a product with intent, and a community that believed. The technology was inevitable.

In the end, the most important question for founders isn’t: “How fast can I build?”

It’s: “Have I built enough clarity, trust, and community for the product to want to exist?”

Because in the AI era, code is cheap. Clarity is not.

And clarity, once built, compounds.

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The post I didn’t build an AI product, I built a brand and the product built itself appeared first on e27.