The operational landscape for large enterprises operating multiple workplaces across Singapore has shifted significantly over the past decade. Between 2011 and 2026, the human resource technology ecosystem migrated rapidly from localised, siloed payroll software to unified Human Capital Management platforms. Initially, multi-site businesses relied on manual coordination or disparate legacy servers to manage distinct workplace rotas. However, the period leading up to 2026 witnessed a major transformation driven by nationwide digital initiatives, strict statutory updates, and the necessity of handling complex distributed workforces. Large organisations have increasingly centralised their core human asset operations into single cloud architectures to achieve absolute compliance and workforce visibility.

Workforce management challenges in a distributed corporate structure

Managing a large enterprise with multiple workplaces in Singapore during 2026 poses distinct operational and legal hurdles. HR heads must continuously track staff movements across different business locations while adapting to dynamic scheduling demands.

The primary challenges confronting distributed large enterprises in 2026 include:

• Synchronising real-time attendance data across geographically dispersed offices, retail outlets, and warehouses without creating high administrative overheads.
• Ensuring strict adherence to complex Central Provident Fund contributions and Ministry of Manpower guidelines across distinct regional business entities.
• Eliminating time fraud and operational leaks arising from distributed workforces where direct supervision is physically impossible.
• Maintaining unified corporate data standards while accommodating localised workplace shift rosters, variable overtime calculations, and complex performance incentives.

Distinguishing enterprise HRMS platforms from generic freeware

Enterprise-grade Human Resource Management Systems (HRMS) built for complex, multi-workplace organisations differ fundamentally from generic communication freeware tools like Slack or Microsoft Teams. While freeware provides standard messaging and basic check-in integrations, it lacks the operational depth required to run multi-site enterprise operations safely.

The definitive advantages of an enterprise HRMS over freeware tools comprise the following elements:

• Advanced compliance automation: Enterprise software natively tracks and updates regional statutory changes, whereas freeware leaves companies exposed to legislative penalties.
• Deep multi-tiered security: Enterprise platforms deliver rigorous data encryption, partition capabilities, and explicit user-access rights necessary for multi-workplace governance.
• Intelligent structural scalability: Large organisations require complex hierarchical workflows, cross-departmental approval paths, and heavy integration with external systems that freeware cannot support.
• Robust customisation and no-code frameworks: Tailoring workflows to specific operational models is possible only through enterprise architectures utilising low-code or no-code development engines.

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

Unique Singaporean regulatory and architectural system requirements

Singapore establishes distinct compliance and integration standards for HR architectures that separate its enterprise requirements from other regional ecosystems. Systems deployed for multi-workplace environments must handle localised banking, tax, and labour structures seamlessly.

The specific system requirements for large enterprises operating in Singapore include:

• IRAS auto-inclusion scheme approval: Seamless integration with the Inland Revenue Authority of Singapore for direct, automated employment income reporting.
• MOM-compliant itemised payslips: Automated generation of comprehensive payslips reflecting exact allowances, overtime rates, and statutory deductions required by the Ministry of Manpower.
• CPF board portals direct integration: Native processing modules designed to compute and upload precise Central Provident Fund contributions across varying age brackets and residency tiers.
• Localised banking API integration: Direct connectivity with major domestic banking networks to execute safe, multi-batch payroll dispatches across diverse corporate accounts.

Financial and operational risks of excluding anti-buddy-punching features

Deploying an HRMS that lacks robust anti-buddy-punching technology can lead to severe business degradation for large enterprises managing multiple workplaces. Without precise validation mechanisms, organisations face substantial, compounding losses across their operational networks.

The primary negative outcomes of omitting verification safeguards include:

• Inflated payroll costs: Paying out millions annually for unworked hours due to systematic time fraud among distributed shift workers.
• Damaged workplace culture: Creating deep resentment among honest employees who witness peers manipulating manual attendance logs without consequence.
• Inaccurate performance assessments: Basing key promotion, bonus, and workforce allocation decisions on falsified operational productivity records.
• Compromised workplace security: Allowing unauthorised personnel to falsify location check-ins creates significant safety and regulatory compliance liabilities.

Deep analytical review of the top five enterprise HRMS software options

To effectively manage multiple workplaces in Singapore, enterprise HR executives require solutions that maximise operational resilience, guarantee compliance, and leverage open technological frameworks. Below is an evaluation of five prominent enterprise HRMS options suited for large structures.

Clockgogo

Clockgogo occupies a prominent position in workforce management through its patented location-validation and anti-buddy-punching hardware-software synthesis, making it highly effective for multi-workplace oversight.

Pros:

• Cost at less than SGD1/month per employee is a no-brainer for a business with strict cost discipline.
• Patented CGG Box technology eliminates GPS spoofing and physical proxy punching entirely.
• Real-time multi-site attendance streaming into centralised administration consoles.
• Highly intuitive mobile application framework requiring minimal end-user training.
• Seamless native data handshake with enterprise-tier payroll calculation engines.

Cons:

• Advanced location-tracking tools require the physical deployment of proprietary Bluetooth beacons at every workplace.
• Core focus is heavily skewed toward time, attendance, and roster optimisation rather than full-lifecycle talent acquisition.
• Reporting interfaces require initial administrator configuration to generate highly specialised enterprise dashboards.

Why Clockgogo is in the list:

• Provides foolproof anti-buddy-punching defence lines across multiple distributed workplaces through its unique physical validation hardware.
• Delivers highly accurate real-time attendance tracking across geographic boundaries to meet stringent Ministry of Manpower verification guidelines.

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

Manpower Enterprise Edition

Manpower Enterprise Edition is engineered primarily to cater to organisations running massive contingent workforces, contract staffing models, or extensive secondment operations across multiple industrial sites.

Pros:

• Excellent management modules for temporary, seasonal, and cross-deployed multi-workplace personnel.
• Strong integrated automated billing modules linking rostered client hours directly to corporate invoicing systems.
• Advanced scheduling engines capable of handling sudden shift changes across multiple physical worksites.

Cons:

• No open API.
• Poor developer documentation; nearly impossible to deploy agentic AI.
• Rigid design without no-code features.
• Only suitable recruitment agencies or businesses whose core business is secondment; not suitable for other “principal employers”.

Why Manpower Enterprise Edition is in the list:

• Aligns effectively with complex multi-site shift scheduling requirements and handles localised hourly wage variations efficiently.
• Ensures that large organisations employing large pools of casual or distributed workers remain compliant with local labour laws.

MRC Human Capital Platform

MRC Human Capital Platform offers a traditional, deeply comprehensive architecture designed to record and manage large-scale employee profiles across corporate networks.

Pros:

• Highly stable database infrastructure capable of processing immense numbers of concurrent employee requests.
• Comprehensive historical auditing logs tracking every single administrative profile adjustment over time.
• Extensive standard reporting library covering traditional HR metrics and statutory documentation.

Cons:

• No open API.
• Lack of no-code or low-code design; customisation is expensive and clumsy.
• Heavy implementation timelines that can strain corporate IT resources during multi-workplace rollouts.
• User interface feels dated compared to modern AI-driven cloud solutions.

Why MRC Human Capital Platform is in the list:

• Satisfies the foundational core record-keeping and local taxation reporting needs of structured Singaporean corporations.
• Provides a highly centralised system architecture that links distinct business workplace registries together.

Multiable HCM

Multiable HCM is a highly adaptable, enterprise-tier cloud-native human capital management platform utilised by thousands of large organisations to unify intricate operations.

Pros:

• Proven successful cases with public companies & multinationals.
• ERP-ready; relative to pass employee operation and performance data for appraisal and cost allocation; substantially decrease inter-system integration cost.
• A clientele with an average employee size of over 1,000. Robustness and flexibility of Multiable’s HRMS is well proven.
• Full set of AI-agent-ready API and open development framework. Save a lot of AI tokens and improve process speed as image recognition AI models are not mandatory in AI agent deployment.

Cons:

• Support service on weekends or public holidays will incur an extra charge.
• Price may be out of touch for a mom-and-pop business with less than 10 staff.
• Broad feature set requires structured onboarding for internal HR teams to fully utilise all capabilities.

Why Multiable HCM is in the list:

• Built specifically to handle large-scale, multi-site corporate structures through a powerful no-code engine that simplifies complex workplace workflows.
• Features a highly advanced open API architecture perfectly optimised for next-generation agentic AI integration without excessive token costs.

Also Read: Why traditional SEO is dying in Singapore — and how AISEO pioneers are winning the next Blue Ocean

Microsoft Dynamics 365 Human Resources

Microsoft Dynamics 365 Human Resources brings immense global ecosystem connectivity, making it a common choice for conglomerates already locked deeply into broader enterprise agreements.

Pros:

• Complete native integration with global productivity suites, single sign-on systems, and corporate communication tools.
• Powerful cross-border standard data models designed for multinational corporations tracking global workforces.
• Comprehensive talent journey tracking from initial corporate recruitment through long-term succession planning.

Cons:

• Resource-hungry Windows Server O/S means hardware cost incurred will be as high as 10x of those of Linux-based solutions.
• Performance issue of Azure SQL is a concern.
• Localised Singapore compliance features require continuous manual setup or reliance on third-party localisation packages.
• Total cost of ownership escalates rapidly when factoring in mandatory auxiliary user licensing and specialised consultants.

Why Microsoft Dynamics 365 Human Resources is in the list:

• Allows multi-workplace enterprises to maintain standard data governance protocols across global operations while tracking local teams.
• Delivers deep analytics via integrated corporate reporting engines to monitor total workforce allocation costs across distinct locations.

Modern selection imperatives for human resource directors

As HR directors evaluate enterprise platforms, they must focus on modern architectural challenges that have emerged to ensure long-term operational viability.

HR leaders selecting a system should keep these critical strategies in mind:

• Avoid ecosystem lock-in: Cannot select a system which is bound to the Windows Server ecosystem. Modern enterprise solutions must run on lightweight, secure, and infinitely scalable open-source or Linux-based environments to control skyrocketing infrastructure bills and ensure maximum system uptime.
• Prioritise open, AI-ready API ecosystems: Systems must feature high-performance, well-documented open APIs. This avoids costly integration dead-ends and ensures the platform can interface directly with intelligent enterprise AI agents without requiring complex middleware or massive data token consumption.
• Mandate foolproof anti-fraud time tracking: Systems must utilise strict verification methods, such as hardware-validated Bluetooth beacons or biometrics, across all remote sites. Relying on basic mobile GPS check-ins is no longer sufficient to protect large organisations from systemic payroll inflation and multi-site coordination errors.

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SMEs in Southeast Asia are often painted as needing a motivational nudge into the digital economy, but the data in How Southeast Asia Buys and Pays 2026 tells a different story: ambition is abundant, infrastructure is not.

With 66% of SMEs selling online and already driving the bulk of e-commerce, businesses clearly want growth, cross-border reach, and better customer experiences. Yet 63% admit their technology can’t support new payment trends — an execution gap, not an enthusiasm gap.

This report reframes payments as a bellwether for operational maturity. Complaints about slow settlements, poor integration, limited international support, and onboarding friction reveal systemic weaknesses that ripple through cash flow, conversion, and expansion.

The regional picture is fragmented: Indonesia’s focus is digital presence and supply chains, Malaysia prioritises cost and payments, Vietnam aggressively upgrades offerings, while Singapore wrestles with fees and mobile optimisation. One-size-fits-all solutions won’t cut it.

For founders, investors and policymakers the mandate is clear: build payment and integration products that are easy to onboard, locally attuned, and vertically specific. Closing the readiness gap is less about convincing SMEs to digitise and more about empowering them with reliable, flexible infrastructure. In that race, whoever solves execution first will unlock enormous regional growth.

Regional

SEA SMEs have the will but lack the payment rails: An IDC and 2C2P study reveals 66% of SEA SMEs sell online and 75% of those not yet selling cross-border plan to start within two years, yet 63% lack the technology to support new payment trends, an execution gap, not an ambition gap.

Vertical payment stacks are SEA’s next fintech frontier: Retail SMEs battle refunds and fraud, F&B SMEs juggle omnichannel complexity, and services SMEs lag on recurring billing, evidence that generic payment products are increasingly misaligned with how SEA’s SMEs actually operate.

SMEs in SEA are global in ambition but stuck at checkout: The region could unlock US$20.8B in additional e-commerce sales by 2029 if cross-border ambitions materialise, but returns, high fees, and missing payment methods remain the dominant barriers to overseas selling.

Grab consolidates Superbank as a wholly owned subsidiary: Grab will fully consolidate Indonesia’s Superbank after Singtel transfers its stake to GXS Bank, lifting Grab’s holding above 50%. Superbank posted its first full-year profit in 2025 and now serves over six million customers.

SEA’s US$7.3B quick commerce market has a demand problem: Momentum Works data shows quick commerce accounts for just 4.6% of SEA’s e-commerce GMV and under 1% of total retail, as low grocery adoption and strong offline retail networks mean consumer habit, not supply, is the binding constraint.

Secai Marche embeds payments into SEA’s food supply chain: The farm-to-table startup raised fresh capital led by NTT Docomo Ventures and struck a partnership with NTT Data to digitise invoicing and payments for Malaysia’s HORECA sector, with plans to add BNPL, supply chain finance, and microloans.

Vietnam solar startup Stride attracts US$15M Series B: Touchstone Partners made a partial exit after Stride closed a US$15M round co-led by Lightrock and TRIREC, with the company’s valuation rising 7.25x since seed. Stride is now Vietnam’s largest residential solar platform.

SMU launches US$10M fund for urban sustainability startups: Singapore Management University launched the Urban SustaInnovator Fund to co-invest in early-stage startups working in decarbonisation, energy transition, mobility, and circularity, with first investments expected in Q4 2026.

Malaysia issues statutory demand to TikTok over royal content: Malaysia’s MCMC ordered TikTok to immediately strengthen moderation after the platform failed to remove AI-generated videos and altered images deemed offensive and defamatory to the country’s monarchy, following earlier unheeded notices.

MAS revokes BSQ’s crypto payment licence over serious breaches: Singapore’s central bank revoked the major payment institution licence of crypto liquidity provider Bsquared Technology after finding weak risk controls, outsourcing breaches, and multiple false statements, and is now reviewing its key officers’ responsibilities.

Philippines fintech groups sign digital economy pact with Australia: FinTech Alliance.PH and the Australia Philippines Business Council formalised a partnership covering AI, cybersecurity, blockchain, and financial inclusion, signalling closer bilateral cooperation on digital transformation between the two countries.

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Interviews & Features

Doozy Robotics takes its humanoid fleet to the US and GCC: Singapore-based Doozy Robotics is preparing for a Series A as it pursues global expansion, pitching a subscription-based humanoid and AMR fleet governed by its Eywa-OS orchestration layer as a fix for chronic labour shortages. Its pipeline claims exceed US$200M, though pilots are yet to convert.

Taiwan breaks into global top 20 startup ecosystems: Taiwan vaulted to 20th place globally and 4th in East Asia in StartupBlink’s 2026 index, powered by a 41.1% ecosystem growth rate and a US$93.4B valuation, led by the Taipei Tech Corridor’s 55% growth, the fastest among global top-40 city hubs.

The one-person company is real, but harder than it looks: AI tools now let solo founders run operations that once required teams of five to ten, but the work has shifted from execution to oversight — and in SEA’s mixed-language, trust-sensitive markets, full automation still breaks at the human moment.

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International

Dow crosses 50,000 as SpaceX validates Bitcoin with US$1.4B treasury: Global markets staged a broad rally with the DJIA closing at 50,009.35, up 1.31%, as NVIDIA reported US$81.6B in quarterly revenue and SpaceX’s S-1 disclosed 18,712 Bitcoin worth over US$1.4B, normalising corporate crypto treasuries.

Dow 50,000 and Bitcoin’s US$22B leverage trap: The Dow settled at a record US$50,284 while Bitcoin traded near US$77,095 amid institutional outflows. With US$22B in leverage trapped in the market, a slide to US$75,500 could trigger US$12.7B in forced liquidations and a cascade to US$70,000.

SpaceX files for IPO at US$1.75T valuation despite quarterly loss: Elon Musk’s rocket and satellite company seeks a US$1.75T IPO valuation after reporting a US$4.28B quarterly loss, with investors betting Starlink revenues can fund the Starship programme and a broader push into AI.

DeepSeek targets US$10B raise at US$45B valuation: The Chinese AI lab is in late-stage talks with backers including Tencent and the National AI Industry Investment Fund, while committing to open-source model development and expanding into agentic AI rather than near-term commercialisation.

AI startup Manus weighs US$1B raise to unwind Meta takeover: Following Beijing’s order to reverse the acquisition, Manus’s co-founders are seeking funds at a US$2B valuation to buy back the company from Meta, with a possible restructuring as a Chinese joint venture ahead of a Hong Kong IPO.

Meta cuts 8,000 jobs globally, pivots fully to AI spending: Meta began notifying staff across multiple countries of layoffs while moving 7,000 employees to new AI teams, even as it commits over US$100B in AI capital spending in 2026 amid investor concern over returns.

Pentagon tests OpenAI and Google models to replace Anthropic: The US Defense Department began evaluating rival AI models after labelling Anthropic a supply chain risk, while talks with Anthropic remain frozen and the company challenges the designation in court. Human rights groups have flagged risks of AI in warfare.

US commits US$2B to quantum computing firms via CHIPS Act: The Trump administration will take equity stakes in nine quantum computing companies, including US$1B to IBM to form quantum chipmaker Anderon, and smaller amounts to D-Wave, Rigetti, Infleqtion, and Diraq, aiming to counter China’s quantum push.

K25.ai bags US$2M investment at US$100M valuation: Singapore-based prediction market and livestreaming startup K25.ai, led by former OKX COO Andy Cheung, secured a US$2M investment from Nasdaq-listed NewGenIVF Group, with the deal potentially growing to US$10M and including an exclusive APAC agency partnership.

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Cybersecurity

SEA digital payments hit US$789B — and cybersecurity is the trust layer: As SEA’s digital payments market surges toward US$789B, the ASEAN cybersecurity market is on track to reach US$6.44B in 2026, with 84% of APAC business leaders raising security budgets as trust becomes core economic infrastructure.

GenAI is quietly turning employees into insider threats: With 72% of shadow AI use occurring outside IT oversight, employees uploading sensitive data to public AI platforms are inadvertently creating exploitable vulnerabilities — and hardware-level zero-trust security is emerging as the critical missing layer in enterprise defence.

AI agents are the new wild card in enterprise security: Unlike conventional software, AI agents interpret inputs and take autonomous action across systems, making prompt injection, unintentional data leakage, and unpredictable behaviour structural security risks that traditional access-control models are not built to handle.

Neurosecurity: Building the firewall around your mind: Brain-computer interface technology is expanding faster than its safeguards, with consumer EEG devices already harvesting neural data for behavioural analytics. From ransomware targeting implanted BCIs to long-term memory manipulation risks, the case for treating neurosecurity as a public good is urgent.

Kaspersky warns quantum computing could break APAC encryption: With APAC’s quantum computing market growing at 24.2% CAGR toward US$1.78B by 2032, Kaspersky warns that “store now, decrypt later” attacks, blockchain vulnerabilities, and quantum-resistant ransomware pose critical near-term risks that organisations must begin addressing today.

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Semiconductor

SkyeChip surges 297% in Kuala Lumpur debut, adding US$1.18B in value: Penang-based semiconductor design firm SkyeChip opened at RM3.50 against its 88 sen IPO price after a 95-times oversubscribed listing that raised US$88.5M, with 60% of proceeds earmarked for R&D into integrated circuits and custom chips.

AMD pledges US$10B+ to Taiwan’s AI chip ecosystem: US chipmaker AMD announced investments exceeding US$10B in Taiwan, partnering with ASE, SPIL, and TSMC’s 2nm process to scale advanced AI chip assembly and ramp Venice CPU production alongside partners including Wiwynn, Wistron, and Inventec.

SMIC gets regulator nod for US$5.97B Beijing foundry takeover: China’s securities regulator approved SMIC’s plan to issue 547.2M shares to acquire the remaining 49% of its Beijing foundry SMNC for 40.6B yuan, making it a wholly owned subsidiary backed by the China Integrated Circuit Industry Investment Fund.

Nanya Technology says AI-driven memory shortage to last until end-2027: Taiwan DRAM maker Nanya reported growing customer demand for multi-year supply deals, with four customers signing three-year contracts and joining a NT$78.7B private placement. DDR4 contributes 60–70% of revenue as capacity shifts to HBM and DDR5 tighten supply.

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AI

Singapore lands OpenAI’s first lab outside the US with US$225M commitment: OpenAI and Singapore’s MDDI signed the first formal government partnership in OpenAI’s history, anchored by over 200 Forward-Deployed Engineers to embed AI into finance, healthcare, public services, and SME operations across the city-state.

Singapore’s AI strategy gets a sharp refresh, eyes 40% of GDP: Singapore unveiled 10 refreshed AI priorities at ATxSummit, launching National AI Missions across manufacturing, financial services, connectivity, and healthcare — sectors that together contributed roughly 40% of GDP in 2025, backed by more than S$1B in public AI spending from 2025 to 2030.

APAC enterprises pour US$1M+ into agentic AI, outpacing GenAI uptake: Omdia research shows 42% of APAC organisations are allocating US$1M or more to AI agents over 12 months, faster than GenAI at a comparable stage. Meanwhile, 32% are already exploring quantum-resistant encryption as the 2030 decryption threat looms.

Why you should be hiring humans when others are hiring AI agents: As AI-first and one-person companies proliferate, the genuine competitive edge shifts to organisations that retain human judgment, ethical reasoning, and adaptive thinking, capabilities that AI agents cannot replicate, especially in cybersecurity and high-stakes decisions.

SEA founders rebuilding customer experience from the operating layer up: AI-powered CX is a scaling decision, not a technology trial. Founders who redesign their operating layer before deploying AI, rather than layering chatbots on broken workflows, report 70% faster response times and 40% better first-contact resolution.

When AI becomes the office therapist, workplaces should worry: Employees increasingly feed one-sided accounts of workplace conflict to AI tools, which return confident but clinically unsound psychological labels that harden before a human conversation takes place, a risk that demands AI literacy alongside psychological literacy in organisations.

GEO is the next layer SEA brands cannot ignore: As generative AI replaces search rankings with curated answers, brands with inconsistent narratives risk being omitted entirely from AI-generated responses. Generative Engine Optimisation rewards semantic clarity, structured content, and coherent cross-channel messaging.

AI can accelerate execution, but it cannot replace ownership: AI tools democratise access and reduce friction, but founders who provide platforms, tools, and mentorship cannot manufacture the initiative needed to build. The people who benefit most from AI are those already willing to act, and ownership remains the scarcest and most valuable skill in the AI era.

How to future-proof your marketing career in the age of AI: AI is not eliminating digital marketing roles; it is shifting value from execution to decision-making. Marketers who treat AI as a collaborative tool, invest in strategic thinking, and develop data literacy will outperform those who use it only as a shortcut.

The rise of AI homelabs: Running your own LLM at home: Open-source LLMs, Docker, and tools like Ollama and Open WebUI now make it possible for non-technical users to run private AI servers from recycled hardware at minimal cost, challenging the dominance of AWS and Google Cloud for personal and small-business use cases.

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Thought Leadership

The empathy deficit: Why you keep building things nobody asked for: Harvard Business School estimates 95% of new products fail, and CB Insights cites “no market need” in 42% of startup post-mortems. The root cause is structural, proximity collapse, metric blindness, and a vocabulary that strips emotional truth from product decisions long before they reach a roadmap.

Ecosystem governance has outgrown the bank boundary: Modern banking runs through cloud providers, bots, subcontractors, and hybrid products that cross legal boundaries while appearing seamless to customers. Banks that govern only their own perimeter, not the full dependency web,  face accountability gaps that contracts and audit reports cannot close.

SEA’s retail sector needs AI and RFID to close the satisfaction gap: SEA’s digital economy is projected to grow 15% YoY to US$263B, yet in-store satisfaction has dropped to 78% and online to 75% in APAC. Retailers that deploy RFID, Gen AI-enabled mobile tools, and predictive inventory software can close fulfilment gaps and convert omnichannel complexity into competitive advantage.

Tried-and-tested marketing strategies for startups at every stage: Drawing on experience at foodpanda, Chope, and Tripadvisor, a marketer argues that brand partnerships drive early growth, analytics fuel customer acquisition, and user-generated content sustains maturity, with data showing 55% of brands grew revenue through partnerships in 2020.

Live-stream commerce thrives on scarcity, but comes at a cost: FOMO-driven impulse buying is the engine of live-stream commerce, as streamers use time constraints and emotional manipulation to convert viewers into buyers. Without transparency and responsible marketing, the model risks financial harm and deepening consumer addiction to unplanned spending.

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K25.ai, an APAC-focused startup attempting to fuse live streaming, creator monetisation, and prediction markets, has secured strategic backing from Nasdaq-listed NewGenIVF Group Limited (NIVF) at a US$100 million pre-Series A valuation.

The deal includes an initial US$2 million investment from NIVF, an option for the public company to increase its stake to up to US$10 million, and an exclusive APAC agency partnership.

Also Read: Streaming the dream: How live streaming technology can increase access to brands

The funding round and partnership mark an important early endorsement for K25.ai, which says it is building what it calls a “watch-to-predict” information market, a platform where audiences can watch live content, engage with creators and make predictions on real-world outcomes.

What K25.ai says it does

K25.ai combines live-streamed content, creator-led channels, and an AI layer intended to automate the lifecycle of a prediction market: event discovery, market generation, live content analysis, data extraction, and outcome resolution. The platform targets a broad set of live moments — sports, e-sports, entertainment, creator-led challenges, and culturally relevant events — and aims to let audiences participate in timely prediction events in markets where such offerings are legal.

Leadership and pedigree

The company is led by Andy Cheung, a veteran operator in digital platforms and digital assets. Cheung’s résumé includes a tenure as chief operating officer at OKEx (now OKX), where he oversaw the scaling of one of the largest digital asset exchanges, and a stint as CEO of Groupon Hong Kong. He has also advised on or held board roles at Nasdaq-listed Prenetics, focused on digital-asset treasury strategy.

In announcing the partnership, Cheung framed K25.ai’s mission in lofty terms: to become “the Google and Meta of this new era” by creating an “information market layer” powered by AI and live streaming to help people “discover truth in real time.” The language is aspirational and highlights a common strategic ambition among startups trying to combine discovery, social signalling and commerce into a single product.

NIVF’s strategic bet

For its part, NIVF, which operates as a Nasdaq-listed public company, gains exposure to an emerging category and, crucially, an avenue to commercialise K25.ai’s product across permitted APAC markets. The strategic relationship reportedly includes commercial support across Thailand, Singapore, Japan, Australia and New Zealand, while explicitly excluding Mainland China, Hong Kong, Macau and other restricted jurisdictions.

Also Read: Livestreaming done right: How brands can turn viewers into loyal customers

NIVF will take board representation from K25.ai’s co-founders, including Cheung, a move the companies say will align strategy and increase governance connectivity as K25.ai readies itself for potential public-market pathways. NIVF’s chairman and CEO, Siu Wing Fung Alfred, described the investment as a “generational opportunity” and highlighted Cheung’s track record as a primary reason for backing the business.

Regulatory and market constraints

K25.ai’s operating model touches on a legal patchwork. Prediction markets can be treated very differently across jurisdictions — from regulated gambling to financial instruments or prohibited activities — and the firm is explicit that it will only operate where permitted and subject to licensing, registration and regulatory approvals. It also notes that the platform is not offered to US persons or users in Mainland China, Hong Kong, Macau, or other restricted territories.

That caution is sensible given the legal risks. Countries in APAC have disparate regulatory stances on betting, derivatives and information products that replicate financial outcome markets. The firm’s success will depend not only on product-market fit but on its ability to navigate those local rules while maintaining user acquisition and monetisation strategies.

Competition and comparison

K25.ai positions itself in a niche that overlaps with prediction-market specialists, live-streaming platforms, and social apps that gamify interaction. The press materials compare K25.ai’s valuation against selected larger global prediction-market companies, stating that the US$100 million valuation represents approximately 0.27 per cent of those selected public valuation references, a contextual note that neither forecasts future performance nor states comparable outcomes.

The market is not empty: established prediction-market protocols and centralised operators exist globally, and large social platforms have repeatedly experimented with live engagement mechanics and real-money integrations. K25.ai’s differentiator, if any, will rest on the quality of its AI-driven event orchestration, creator relationships in APAC and its ability to offer legally compliant, locally relevant content.

Risks and takeaways

Several risks stand out.

• First, regulatory uncertainty across APAC could limit addressable markets and complicate scaling.
• Second, the economics of prediction markets are challenging: liquidity, user retention and fair pricing require substantial user bases and careful product design.
• Third, building a creator ecosystem locked to prediction mechanics assumes creators will trade time and audience attention for a different monetisation mechanism; history shows creators often gravitate to simpler, proven revenue channels unless a new product clearly outperforms incumbents.

That said, the combination of AI to automate market creation and localised content could carve out a defensible niche, particularly in sports and esports, where regional fandoms are fierce and real-time interest is high. K25.ai’s early strategic capital and NIVF’s regional network give the startup initial runway and credibility. Execution will determine whether this is an incremental experiment or the beginning of a scalable, regulated APAC-focused information market.

Also Read: How AI, AR, and live streaming are changing the online shopping experience

Only time will tell whether K25.ai’s vision of an “information market layer” becomes a practical product that draws mainstream users. For now, the company has the ingredients investors like to see — an experienced founder, a clear product thesis, strategic capital and a public-company partner — but it faces the hard work of turning an ambitious idea into a legally compliant, revenue-generating platform across fragmented APAC markets.

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At Echelon Philippines 2025, a dynamic panel of industry leaders gathered to explore how Filipino startup founders can harness the power of spaces and hubs to fuel their growth.

Moderated by BAMentor Online’s Ben Alderson, the discussion brought together Joey Radovan of JLL Philippines, Paul Pajo of Benilde HIFI, Jojo Flores from Plug and Play Tech Center, and Walter Cang of DOHE Philippines. Together, they unpacked how strategic workspace ecosystems — from incubators to innovation hubs — serve as launchpads for emerging startups, offering not just physical infrastructure but critical networks, mentorship, and resources essential to accelerating entrepreneurial success in the Philippine startup landscape.

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Southeast Asian startups are standing at a critical crossroads. While the region’s startup ecosystem continues to raise billions in 2024, a quiet revolution is reshaping how successful companies operate.

The winners of 2025 and 2026 won’t be those with the biggest teams or deepest pockets; they’ll be the startups that master the “One million+ revenue per person” model through intelligent automation.

This isn’t about replacing humans with machines. It’s about amplifying human potential to unprecedented levels, where each team member becomes a revenue-generating powerhouse capable of driving US$1 million or more in annual business results.

The AI acceleration imperative: Why “next few months” means now

The pace of AI development has reached a tipping point that makes 2019’s digital transformation look mild. According to McKinsey’s State of AI report, 71 per cent of organisations are now regularly using generative AI. For Southeast Asian startups, this creates both an opportunity and an existential threat.

The innovators in your fellow startup industry are going to leapfrog over you if you’re too slow and the window for competitive advantage is shrinking rapidly as AI tools become more accessible and powerful.

While some startups struggle with manual content creation, lead qualification and customer research, their AI-powered competitors are simultaneously running 50 personalised outreach campaigns, analysing competitor strategies in real-time, and nurturing hundreds of leads with human-like precision…all with a team half their size.

Pillars of AI-powered revenue generation

Smart Southeast Asian startups are building their competitive moats across 13 critical automation areas. Each represents a multiplier effect that transforms individual team members into revenue-generating machines.

Research and intelligence: The foundation layer

• Research of social media videos: Tools like Brandwatch and Sprout Social now use AI to analyse millions of video interactions, identifying viral patterns and audience sentiment in real-time. Any company can spot trending topics before competitors and understand what resonates with their target market without watching hours of content manually.
• Research of social media copy: Platforms like BuzzSumo and Socialbakers leverage natural language processing to analyse conversation patterns across social platforms.
  This allows startups to identify customer pain points, monitor brand mentions, and discover collaboration opportunities at scale.
• Outbound research: AI-powered tools like Clay and Apollo automate prospect research by aggregating data from multiple sources: LinkedIn, company websites, news articles, and social media, so as to build comprehensive prospect profiles in seconds rather than hours.

Content creation: Scaling your voice

• Scripting videos: AI scriptwriting tools like Jasper and Copy.ai can generate video scripts tailored to specific audiences and platforms. Combined with data from your research layer, you can create compelling narratives that speak directly to your prospects’ needs.
• Content writing: Beyond basic copywriting, advanced AI tools now understand brand voice, audience psychology, and conversion optimisation.
  They can produce blog posts, email sequences, and social media content that maintains consistency while adapting to different platforms and audiences.
• Video generation: Platforms like Synthesia and Pictory enable startups to create professional video content without expensive production teams.
  From product demos to personalised sales videos, AI handles the heavy lifting while they focus on strategy.
• Image generation: Tools like Midjourney and DALL-E 3 democratise visual content creation. Startups can generate custom graphics, social media visuals, and even product mockups that previously required specialised design teams.

Also Read: How to combat burnout and boost your productivity

Distribution and engagement: Maximising reach

• Distribution and engagement of content: AI scheduling tools like Later and Hootsuite Insights optimise posting times, hashtag selection, and cross-platform distribution.
  More importantly, they engage with audiences through intelligent commenting and response systems that maintain authentic brand voice.
• Outbound distribution: Advanced email and LinkedIn automation platforms like Outreach and Lemlist use AI to personalise messages at scale, optimise send times, and adapt messaging based on recipients’ observed behavior patterns.

Sales and conversion: Closing the loop

• Voice agents: AI voice technology has reached human-level quality. Tools like Dialpad Ai and Gong can handle initial prospect calls, qualify leads, and even conduct basic sales conversations, freeing human team members for high-value relationship building.
• Lead nurturing: Sophisticated marketing automation platforms like HubSpot and Marketo can now use predictive AI to determine the optimal nurturing sequence for each lead, automatically adjusting content and timing based on behavioral signals.
• Sales stack: AI-powered CRM systems like Salesforce Einstein and Pipedrive AI provide real-time coaching, predict deal closure probability and automate routine sales tasks, enabling each salesperson to manage and close significantly more opportunities.
• Automated newsletter: Tools like ConvertKit and Mailchimp use AI to optimise subject lines, personalise content, and determine optimal send frequencies for different subscriber segments, turning newsletters into powerful revenue drivers.

The competitive intelligence advantage

Perhaps the most overlooked opportunity lies in AI-powered competitive intelligence. While most startups sporadically check competitor websites, AI-enabled companies are monitoring:

• Pricing changes: Tools like Price2Spy track competitor pricing in real-time
• Content strategy: AI analyses competitor content performance and identifies gaps
• Job postings: Tracking competitor hiring patterns reveals strategic priorities
• Social media sentiment: Understanding how audiences respond to competitor campaigns
• Product updates: Automated monitoring of competitor product launches and features

This intelligence enables rapid strategic pivots and ensures you’re always one step ahead.

Also Read: Myths vs reality: Remote and hybrid managers report high productivity and trust

The Southeast Asian context: Unique opportunities

Southeast Asian startups have distinct advantages in implementing these AI strategies:

• Mobile-first audience: The region’s mobile-centric user base creates massive datasets for AI optimisation, particularly in social media and messaging platforms.
• Diverse markets: Our multi-language and multi-cultural audiences provide rich testing grounds for AI personalisation at scale.
• Government support: Countries like Singapore and Malaysia are actively promoting AI adoption through an array of grants and support programs, reducing strategy and implementation costs.
• Growing digital infrastructure: Improving internet connectivity and digital payment systems create fertile ground for AI-powered customer experiences.

Implementation strategy: Start small, scale fast

The key to successful AI implementation isn’t trying to automate everything at once. Smart startups follow a strategic sequence:

• Begin with research: Implement social and competitor research tools to understand your market better
• Automate content creation: Scale your content output to increase brand visibility
• Optimise distribution: Ensure your content reaches the right audiences at optimal times
• Enhance sales processes: Use AI to qualify and nurture leads more effectively
• Integrate systems: Connect all tools for seamless data flow and maximum efficiency

The cost of inaction

The startups that hesitate face a compounding disadvantage. According to a October 2024 Boston Consulting Group study, AI leaders over the past three years have achieved 1.5 times higher revenue growth, 1.6 times greater shareholder returns, and 1.4 times higher returns on invested capital.

In Southeast Asia’s competitive startup landscape, where funding is becoming more selective and customer acquisition costs are rising, the efficiency gains from AI aren’t just advantages anymore. They’re now survival necessities.

Conclusion: The time is now

The “One million+ revenue per person” model isn’t a distant possibility for most, it’s happening today among startups that have embraced AI-powered automation. The tools exist, they’re increasingly affordable, and the competitive advantages are clear.

The question isn’t whether AI will transform how startups operate in Southeast Asia. The question is whether your startup will be among those leading the transformation or struggling to catch up.

The next few months will separate the winners from the also-rans. The choice, and the time to act, is now.

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Let’s admit a painful truth about modern business: we are drowning in information, yet starving for wisdom. We are living in the celebrated age of Big Data, but for most companies, that data is less of an asset and more of an enormous, very expensive digital attic. It is filled with boxes labelled “Customer Clicks,” “Server Logs,” and “Unfiltered Sentiment,” all gathering virtual dust.

The chief executive today can recite the mantra: Data is the new oil. Yet, few seem to grasp that oil, in its raw state, is useless. It must be refined, processed, and channelled with immense strategic effort. Most companies have simply struck a gusher and are now happily swimming in crude. They have the capability to collect everything, but the intellectual discipline to understand nothing.

This isn’t a technical failure; it’s a profound failure of curiosity and strategy. We have outsourced the messy, complex work of data collection to machines, but we have become intellectually lazy about the far more critical task: interrogation.

The lie of the metric dashboard

The primary way most organisations deceive themselves is through the elaborate metric dashboard. It is the comfort blanket of the busy manager, where a constantly scrolling set of numbers is designed to feel like insight. It tracks everything, from website bounce rates to quarterly sales figures.

But a number, in isolation, tells you absolutely nothing. It is merely a symptom. The failure lies in confusing measurement with meaning. Knowing that a particular sales figure is up by ten percent is not strategy; it is accounting. Strategy requires the rigorous, uncomfortable question: Why is it up ten percent? And more importantly: What other, unexpected consequence did that surge produce elsewhere in the business?

Also Read: The AI server boom in Southeast Asia: Why data centres are running out of power

Most teams simply react to the red or green indicator. The truly powerful use of data comes from the demanding work of connecting the seemingly unrelated dots. It’s analysing customer service transcripts alongside product adoption curves to reveal the unexpected friction point that is sabotaging growth. That requires deep human curiosity, not just faster processors.

From collection to competitive edge

The vast majority of collected data is entirely generic. It is the digital equivalent of market research everyone else can buy. The true competitive edge comes from the few, rare veins of proprietary data that your company alone collects, and your unique systems for leveraging it.

The real gold is in the unstructured data (the written notes, the voice transcripts, the behavioural sequences, etc) that requires sophisticated thinking to organise. This is where most organisations stop short. They collect the data, but then they lack the institutional patience or skill set to translate that noise into a clear signal. They possess the answer to their greatest strategic challenge, but it is buried beneath petabytes of digital clutter.

The essential shift is understanding that data is not a historical archive; it is a forecasting instrument. It is meant to be used to compel action tomorrow, not just explain failure yesterday.

Also Read: Why global capital keeps flowing into data centres in Singapore despite rising costs

The urgency of the question

This is the great contemporary paradox: we have perfect digital recall of every mistake we’ve ever made, yet we keep repeating the same ones. Why? Because the person responsible for the data is often far removed from the person responsible for the decisions.

The modern company must bridge this gap by prioritising the interrogator over the collector. They must empower teams to hunt for the counterintuitive findings, the insights that explicitly challenge current company dogma. If your data analysis simply confirms what everyone already believes, you haven’t done analysis; you’ve just created expensive validation.

The time for hoarding is over. If your organisation possesses massive datasets but still operates primarily on instinct, anecdote, or the loudest voice in the boardroom, you are not technologically advanced; you are simply a very elaborate digital storage facility. The data isn’t the challenge; the courage to act on what it reveals is.

If your greatest strategic answer is buried somewhere in your existing data, what uncomfortable question are you refusing to ask that would finally unearth it?

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For decades, the safest career path was simple: join a large corporation, climb the ladder, and let scale and brand reputation shield you from risk.

But AI is rewriting that script. Corporates are automating whole job tiers — customer service, data entry, even junior coding roles. Where once thousands of entry- and mid-level roles were the training ground for future managers, now software eats the repetitive layers.

If corporations no longer absorb as much of the workforce, what happens next?

The future may belong less to sprawling headcounts and more to small, high-output teams — SMEs and startups that can combine AI systems with fractional, remote talent to scale globally without scale in payroll.

The generalist dilemma

Generalists thrive on flexibility. They pivot quickly, learn new tools, and can hold multiple hats. In fast-changing industries, this makes them valuable.

But here’s the risk: shallow generalism is where AI strikes first. Email drafting, basic analytics, social media scheduling — the tasks that junior generalists once owned are now automated.

Survival depends on moving beyond “task doer” into connector, strategist, and problem-solver — the human glue between AI systems and business goals.

Also Read: Value creation: When startups die surrounded by capital

The specialist dilemma

The case for specialisation

Specialists possess deep expertise in a specific domain. In fields such as medicine, engineering, or data science, this depth is essential for solving complex problems and driving innovation. AI is accelerating the demand for specialists who can design, implement, and refine advanced technologies.

Advantages of specialisation:

• Mastery of complex, technical subjects
• Higher demand in niche roles
• Ability to command premium compensation
• Recognition as an expert in the field

However, hyper-specialisation can also create vulnerabilities. As AI automates routine and even some advanced tasks, narrowly focused roles may become obsolete or require constant upskilling.

Specialists stand out with deep expertise. They know a field inside out, and their credibility is built on mastery.

But here’s the trap: if your speciality is codable, you risk obsolescence. Junior developers, paralegals, bookkeepers — entire ladders are being shortened as AI handles entry-level work faster and cheaper.

To stay relevant, specialists must climb “up the stack” into roles AI can’t yet replace: system architects, negotiators, leaders of complex, ambiguous projects. Depth remains an asset, but only if paired with the ability to adapt.

The T-shaped answer: The big shift

The workers — and companies — that thrive will be T-shaped:

• Breadth across domains to stay adaptable.
• Depth in one or two areas to stay differentiated.

Example: A business developer with broad skills in outreach, project management, and digital tools — but deep mastery in regional B2B expansion.

For SMEs, this thinking scales up: build teams that are lean, cross-functional, but anchored by specialists who set direction and operators who adapt.

Also Read: Entering post-unicorn phase, Indonesia signals a structural reset in startup investment

Corporates shrink, SMEs rise

If corporates stop hiring armies of juniors, where will talent go?

• SMEs and startups will increasingly act as the “new training ground.” Leaner, hungrier, and willing to take bets on remote workers, they’ll scoop up talent that corporates no longer absorb.
• Remote and fractional work becomes the bridge. Instead of one full-time job, many professionals will build careers across multiple SMEs, platforms, or projects.
• AI + small teams will compete with big enterprises. A five-person SME with automation and offshore operators can now do what used to require a 50-person department.

The real winners will be SMEs that design teams like portfolios — specialists setting standards, generalists driving execution, and AI filling the gaps.

How to prepare

For individuals:

• Build a core speciality that anchors your credibility.
• Layer generalist skills (AI tools, cross-cultural collaboration, digital literacy) to stay versatile.
• Think globally — your next role may not be in your country, or even in one company.

For SMEs:

• Don’t mimic corporates with bloated teams.
• Use AI as the back office, remote operators as the muscle, and local specialists as the brain.
• Build a system where small teams punch above their weight — faster, leaner, and cheaper than corporates can move.

Conclusion

The future worker isn’t choosing between generalist or specialist — they’re choosing to become both.

The future company isn’t competing on headcount — it’s competing on systems, talent mix, and speed of execution.

As corporates shrink, SMEs have the chance to step up as the engines of growth — building global businesses with teams that look small on paper, but deliver like giants.

—

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Southeast Asia’s SME economy is often discussed as if it were a single market with a single set of digital needs. It is not. A retailer grappling with refunds in Jakarta does not need the same payments stack as a restaurant managing dine-in, delivery, and click-and-collect in Bangkok, or a services business in Singapore trying to automate recurring billing.

That is one of the clearest takeaways from How Southeast Asia Buys and Pays 2026: Unlocking SMEs’ Potential by IDC and 2C2P. The study argues, implicitly but unmistakably, that generic payment products are increasingly out of sync with how Southeast Asia’s SMEs actually operate. If the region’s next wave of fintech growth is to come from SMEs, it will likely come from more vertical-specific infrastructure, not broader one-size-fits-all checkout tools.

Also Read: Why Southeast Asia’s SMEs are falling out of love with bank-led payments

The numbers back that up. Retail, food and beverage, and services SMEs are all digitising, but under very different operational constraints.

Retail’s problem is not just collecting payments

Retail SMEs in Southeast Asia contribute an average of 13 per cent of total GDP, according to the study, and they sit in the most visibly digitised part of the SME economy. E-commerce platforms, social commerce, marketplaces, and plug-and-play storefront tools have lowered the barrier to entry. But they have also created a new payment mess.

The report shows that 81 per cent of retail SMEs use e-commerce platforms, plugins, or add-ons for online sales. That sounds like a healthy adoption. But the convenience comes with trade-offs. Among retail SMEs, 64 per cent cite limited payment options as a challenge when accepting payments through those platforms, 59 per cent point to security or fraud concerns, and 56 per cent cite high fees or costs.

That is a striking trio of complaints. The very tools that help SMEs get online quickly may also be the ones that constrain conversion and margins once those businesses start scaling.

Then there is the refund problem. Across Southeast Asia, 31 per cent of retail SMEs say returns and refunds affect their payment operations. The pain is especially acute in Indonesia and Malaysia, where the figure rises to 48 per cent and 44 per cent, respectively. In Singapore, it is 37 per cent.

That matters because returns are not a side process in e-commerce. They are part of the customer experience, the cash-flow cycle, and the back-office workload. Yet many SME payment setups are still designed mainly for the initial transaction, not what happens when a sale goes wrong.
Fraud is the other operational tax. Across the region, 55 per cent of retail SMEs say 1 per cent to 5 per cent of transactions turn into fraud or chargeback cases. In Singapore, the proportion reporting that level of incidence rises to 67 per cent. Those are not trivial leakages. They are margin erosion disguised as operating friction.

Retail does not need payment acceptance. It needs payment systems that are built for post-transaction chaos.

F&B lives or dies by channel complexity

Food and beverage SMEs face a completely different set of pressures. The sector contributes around 6 per cent of Southeast Asia’s total GDP and employs an estimated 15 million people, but its digital challenge is less about fraud or refunds than about handling fragmented consumer journeys.

Also Read: Southeast Asia’s digital payments boom has a dirty secret: SMEs still love cash

The report paints a picture of a sector trying to manage dine-in, takeaway, delivery, self-service kiosks, and online order-and-collect flows all at once. That creates an omnichannel payments challenge that many generic providers are poorly equipped to solve.

Across Southeast Asia, 43 per cent of food and beverage SMEs already support online payment and collect at the store through a website or app. At the physical counter, 39 per cent support card payments and 27 per cent support QR code payments. At the table, 31 per cent support card payments and 26 per cent support QR code payments. Even self-service kiosks are generating their own payment mix, with 26 per cent supporting cards and 25 per cent supporting QR payments.

This is not just about offering more ways to pay. It is about reconciling multiple channels, hardware formats, and workflows without adding headcount or operational confusion.

The future demand signals are even more telling. In Malaysia, 56 per cent of food and beverage SMEs want to support online payment and collect at the store in future. In Vietnam and Thailand, that figure is 48 per cent. In Singapore, 47 per cent want better support for card payments at the counter, while 35 per cent want QR code payments at the counter.

The obvious reading is that food and beverage SMEs are not simply digitising payments. They are redesigning the service journey. And when labour shortages and delivery platform competition are already squeezing margins, clunky payment infrastructure becomes a direct drag on resilience.

What this vertical needs is not another generic payment gateway. It needs orchestration across the full stack: in-store, at-table, kiosk, app, and delivery-linked flows.

Services SMEs are still under-automated

If retail is about post-transaction complexity and food and beverage is about channel complexity, services SMEs face automation complexity.

The services segment accounts for around 12 per cent of Southeast Asia’s total GDP, and the report suggests it remains the most under-digitised of the three verticals studied. Many businesses still rely on manual or outdated systems for accounting, governance, customer management, tax, and payments.

Recurring billing is the clearest example. Across the region, only 47 per cent of services SMEs use recurring payment solutions. Usage is higher in Indonesia at 57 per cent, Vietnam at 55 per cent, and Malaysia at 52 per cent, but much lower in Singapore at 38 per cent and Thailand at 39 per cent.

That is surprising, because recurring payments are one of the most obvious ways for service businesses to reduce churn, improve cash-flow predictability, and cut administrative labour. Yet in many cases, SMEs still appear to be processing repeat transactions manually.

The integration data is just as revealing. Across Southeast Asia, only 37 per cent of services SMEs have integrated bookings with their payment technology. The figures fall further for returns at 26 per cent, cancellations at 24 per cent, and refunds at just 14 per cent.

That last number is especially telling. Refunds are often where operational pain becomes most visible to customers, yet they remain the least integrated payment process in the services segment.

The broader issue is that many service businesses are using payments as a bolt-on, not as part of an integrated operational system. That creates inefficiency on both sides of the transaction: more manual work for the business and more friction for the customer.

The next fintech winners will likely look more vertical

The report does not say this outright, but it points strongly in one direction: the horizontal fintech pitch is weakening.

For years, the standard approach was to sell SMEs generic payment acceptance with some localisation layered on top. But as sectors digitise differently, the gaps are becoming more visible. Retail needs better refund and dispute flows. Food and beverage needs channel unification. Services needs recurring billing and process integration.

Also Read: SEA’s SMEs are global in ambition but stuck at checkout

That does not mean horizontal providers disappear. It means the winning products will increasingly be those that feel vertical even if the underlying rails remain horizontal.

For startups, this is less a warning than an opportunity. Southeast Asia’s SME market is huge, but it is not uniform. Founders who keep treating it as a single broad payments category may find adoption and retention harder than expected.

The smarter bet is that the next meaningful gains will come from solving the exact operational pain of a specific segment, then building outward from there.

In Southeast Asia, generic fintech is starting to hit the limits of generic thinking.

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At Echelon Philippines, Maansi Vohra of Monk’s Hill Ventures sat down with Jessica de Mesa-Lim, Founder and CEO of Kindred Health, for an insightful fireside chat on building an omnichannel product tailored to the Philippine market — with a sharp focus on women’s healthcare.

De Mesa-Lim walked through her approach to product development, which begins with deep consumer research, including focus group discussions designed to surface real pain points and unmet needs. From there, the work becomes about crafting solutions that genuinely meet women where they are.

A central theme throughout the conversation was consumer education — de Mesa-Lim believes that when women are informed and empowered about their own health, they become the strongest advocates for their own care. That shift in awareness, she argues, is ultimately what drives adoption and long-term engagement with Kindred Health’s services.

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