Southeast Asia is trying to do something rare in tech: scale fast without pretending risk doesn’t exist.

A study titled “AI in Southeast Asia: An era of opportunity” by McKinsey and the Singapore Economic Development Board argues that regional coordination is positioning Southeast Asian countries as responsible AI leaders, primarily through ASEAN’s non-binding governance approach.

Also Read: Southeast Asia’s AI boom is built on steel, not startups

But “responsible AI” in Southeast Asia faces a structural problem: the region is fragmented by regulatory frameworks, languages, and data practices. If cross-border AI scale is the goal, governance cannot remain an afterthought.

ASEAN’s approach: guidelines instead of penalties

The report lays out a global contrast. Some jurisdictions (such as China and the European Union) pursue enforceable AI-specific regulation. Others (including ASEAN, Canada, and Japan) focus on principles, guidelines, and voluntary commitments.

ASEAN’s key milestone is its Guide on AI Governance and Ethics (2024), designed to promote consistent standards across borders and align countries on responsible use.

This is pragmatic for a region where economies are at different development levels. But nonbinding guidelines only work if enterprises and governments treat them as operational requirements, not press-release accessories.

The cross-border data problem is the whole game

AI at scale needs data flows. Southeast Asia has spent years talking about digital integration; AI sharpens that urgency. Models trained and deployed across markets will collide with:

• data localisation rules
• sector-specific regulations (especially finance and healthcare)
• varying enforcement capacity
• inconsistent data quality and metadata standards

Singapore’s Minister for Digital Development and Information, Josephine Teo, said: “Recognising the importance of cross-border data flows, we got the ASEAN community to agree on a data management framework.”

Also Read: Momentum without maturity: Southeast Asia’s AI reality

That is the right direction. But frameworks must translate into interoperable compliance processes, not just shared vocabulary.

Sovereignty is rising because foreign dependence is obvious

The report notes a potential imbalance: international tech companies pushing AI in Southeast Asia could leave local firms dependent on imported models, infrastructure, and standards. It cites moves by governments such as Malaysia’s and Singapore’s to invest in sovereign AI infrastructure through national AI centres, partly to retain strategic control and tailor AI to local contexts.

Malaysia’s NAIO head Sam Majid uses an analogy in the report that captures the governance logic: “The braking is the governance part, the responsible part, which makes you realise the creation of the car brake allows the car to go faster.”

That line is more than rhetorical. In regulated industries, governance is the precondition for deployment speed. Without it, organisations slow down because risk becomes unmanageable.

Enterprises are already getting hurt by AI risk, and responding

Responsible AI is not hypothetical. The report says 41 per cent of companies have experienced adverse consequences from AI inaccuracy, and 21 per cent report cybersecurity incidents.

It also shows active mitigation:

• 61 per cent addressing AI inaccuracy
• 58 per cent strengthening cybersecurity
• 46 per cent working on regulatory compliance

This is the shape of the next phase: not “do we adopt AI?” but “how do we operate AI safely across markets?”

Singapore’s role: governance export, not just infrastructure

Singapore is positioned in the report as a regional nerve centre—home to extensive AI CoEs and a strong regulatory environment. That combination creates a potential export: governance tooling and standards that can travel.

Also Read: AI is now a budget line. It’s still not a profit line

The report references initiatives such as AI Verify Foundation, which aims to promote testing frameworks for responsible and trustworthy AI.

If Southeast Asia’s AI future is cross-border, tools like AI testing, model evaluation standards, and incident reporting mechanisms become part of regional competitiveness, not just compliance.

The inclusion challenge: “responsible” also has to mean “not just for big tech”

The report repeatedly warns about uneven outcomes: MSMEs are the backbone of Southeast Asian economies, yet they risk being left behind by the complexity and cost of AI adoption.

Responsible AI cannot be defined only by safety and ethics. In Southeast Asia, responsibility must include access:

• affordable tools
• multilingual support
• practical onboarding
• shared data assets and sector collaborations

Otherwise, the region builds a two-tier AI economy: governed, scaled AI for big enterprises—and ad-hoc, risky AI use for smaller firms.

The regional playbook: collaborate or fragment

The report’s “way forward” agenda calls for collaborative ecosystem building across:

• government
• tech providers
• academia
• enterprises

It outlines enablers such as trusted data flows, talent pipelines, responsible AI at scale, sector collaborations, and infrastructure inclusion.

The message is simple: no single stakeholder can solve the scale problem alone. But the underlying reality is sharper: without collaboration, Southeast Asia will scale AI in pockets, not as a region.

That outcome would be familiar. It is what happened with many earlier digital transformations. AI raises the stakes because it rewards scale and punishes fragmentation.

Also Read: Everyone wants AI agents but few have the plumbing

Responsible AI in Southeast Asia will not be won by policy documents. It will be won by operational alignment: shared standards, cross-border data mechanisms, and enforcement-capable governance—built in a way that small firms can actually use.

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In hospitality, trust is everything. 

Imagine checking into your hotel room only to find out that your personal data has been leaked. Your vacation is ruined even before it begins! 

This isn’t fiction; it’s the reality facing millions in Southeast Asia’s booming digital economy.

And when incidents like this happen, the damage goes far beyond financial loss or regulatory penalties and breaks the guest’s sense of safety, the very trust that hospitality is built on. 

In an industry where comfort is the product, cybersecurity is no longer just a backend concern but a core part of the customer experience.

A trust layer that drives business growth

For too long, the hospitality industry has viewed cybersecurity as a technical shield, a series of defensive measures against digital attacks. However, our experience shows that cybersecurity is not merely a cost of compliance or a defensive necessity but a “trust layer” that drives business growth. By framing security through the lens of the consumer experience, we unlock the ability to expand their digital footprint and foster deep, lasting loyalty. 

At RedDoorz, our success, including a repeat booking rate of approximately 70 per cent, is built on the foundation that our guests feel their journey is safe and free of hidden surprises.

The rise of artificial intelligence (AI) has accelerated this conversation. AI depends entirely on data, and the quality of that data dictates the level of trust a customer can place in a platform. We leverage AI for critical functions such as property quality assessments during onboarding and sentiment analysis of guest reviews. By using AI to understand specific goals rather than making subjective judgements, we introduce objectivity and eliminate bias. This is to ensure that the property a guest sees on their screen is the same one they find upon arrival.

However, AI is a double-edged sword; although it enables us to personalise recommendations and secure payments, it also empowers bad actors to automate “human-like” deception at scale. We are entering an era where AI-driven scams and impersonation, through faked images, videos, or audio, will make it increasingly challenging to discern what is real. As CTOs, we must accept that “AI thieves” are becoming more sophisticated, which necessitates the development of “AI police”-tools capable of detecting and thwarting these advanced threats in real-time.

Also Read: From grid to code: Why good cybersecurity will help deliver net zero

Building the fortress: Security by design

To navigate this landscape, our security architecture is built on the principle of restraint. We treat cybersecurity as a multi-layered journey: it begins with safety and security on day one, then moves to privacy, trust, and finally, comfort.

One of our most significant strategic decisions has been to keep our AI workloads firmly within our own data warehouse. By ensuring that sensitive data never moves to external Large Language Model (LLM) platforms, we eliminate an entire class of privacy and leakage risks. All personally identifiable information (PII) is masked, anonymised, or aggregated before it touches a model, and a full audit trail backs every decision.

This philosophy extends to our customer-facing automation. Our chatbots that handle everything from bookings to payments are designed with narrow, time-bound boundaries because anything customer-facing will be tested by malicious actors. Therefore, we separate conversational context from sensitive systems like payments.

Authentication is not a “forever” state; access typically lasts only for microseconds during a specific session and expires the moment the job is done. We believe that convenience must never come at the expense of security; if trust cannot be established at any given step, the transaction simply does not proceed.

Cultivating a security-first culture

For a startup to truly treat cybersecurity as a trust layer, it must move beyond the “compliance checkbox” mentality. This requires a cultural shift across product, engineering, and data science teams. 

At RedDoorz, security clearance is a mandatory step in our release process. Every team member understands that a vulnerable tool or feature will not go live, regardless of the urgency of the launch.

Also Read: AI and cybersecurity in healthcare: Building resilience for better patient care

For fellow CTOs and founders in the ecosystem, I offer a few practical “rituals” to embed this thinking:

• Prioritise minimum viable security: On day one, invest in the elements that could break your startup if compromised—namely, personally identifiable information and payments.
• The 10 per cent rule: Commit at least 10 per cent of your time to reviewing security risks and infrastructure to ensure that security remains a shared responsibility rather than a siloed task.
• Leverage off-the-shelf tools: Startups often lack the resources to build everything in-house. Use proven third-party tools for security coverage and employ ethical hacking or external audits to find your own loopholes before someone else does.
• Human-in-the-loop: Never treat AI as a self-learning experiment. We use human and subject-matter experts to regularly conduct quality checks on AI outputs, ensuring accuracy and accountability.

The path forward

The role of the CTO has become multifold and significantly more complex in the age of AI. We are no longer just architects of systems; we are the guardians of the customer relationship. We must constantly monitor for model drift, malicious data poisoning, and unauthorised internal access through strict role-based controls and logging.

In the digital economy, trust is the only currency that truly matters. Whether it is through showing honest guest reviews, ensuring secure conversational context, or protecting data at rest, every security measure we take is a brick in the wall of customer confidence. By treating cybersecurity as a foundational trust layer, we do more than just protect our businesses; we enable the innovation and growth that will define the future of Southeast Asia.

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The property investment landscape is evolving faster than ever as we approach 2026. Economic shifts, changing buyer behaviour, and technological innovation are redefining how investors evaluate and manage real estate assets. What once relied heavily on instinct and location alone is now driven by data, sustainability, and long-term strategic thinking. Understanding these changes is essential for investors who want to remain competitive in a dynamic global market.

The future of property investment will favour those who adapt early and align their strategies with emerging trends rather than relying on outdated models.

Evolving investor mindsets

Modern property investors are becoming more informed and selective. Instead of focusing solely on short-term appreciation, there is a stronger emphasis on stability, rental demand, and long-term value. Lifestyle changes such as remote working and flexible business operations have also influenced property choices, increasing demand for versatile spaces.

Residential investors are now looking beyond major city centres, while commercial investors are prioritising functionality and adaptability. Properties that can serve multiple purposes or attract diverse tenants are gaining stronger attention in the market.

The influence of technology in real estate

Technology is playing a central role in reshaping property investment decisions. Advanced analytics, virtual tours, and digital documentation have streamlined the buying and selling process, reducing uncertainty for investors. Access to real-time data allows investors to analyse trends, assess risks, and identify opportunities more efficiently than ever before.

Also Read: Why Southeast Asia’s fragmented property data is an AI opportunity, not a barrier

By 2026, technology is expected to impact property investment in several ways:

• Improved market forecasting through data-driven insights
• Faster and more transparent property transactions
• Enhanced tenant management and operational efficiency

These advancements are not only improving decision-making but also increasing investor confidence across different markets.

Sustainability as a core investment factor

Sustainability has shifted from being a niche consideration to a core investment requirement. Environmental awareness, government regulations, and rising energy costs are pushing investors toward eco-friendly and energy-efficient properties. Sustainable buildings tend to attract quality tenants and reduce long-term operational expenses, making them more appealing from an investment perspective.

Smart technologies such as energy monitoring systems and automated maintenance solutions are becoming standard features in modern developments. Properties that prioritise sustainability are more likely to maintain value and demand in the years ahead.

Market stability and risk management

While property investment remains one of the most stable asset classes, it is not immune to economic fluctuations. Interest rate changes, inflation, and geopolitical factors can influence market performance. However, investors who focus on fundamentals tend to navigate these challenges more effectively.

• A future-ready investment approach includes:
• Diversifying across property types and locations
• Conducting detailed market research before investment
• Focusing on long-term growth rather than short-term market movements

This strategic mindset helps reduce risk and supports consistent returns over time.

Also Read: Real estate meets AI: Why property agents need to adapt before they fall behind

Emerging opportunities in 2026

As urban development expands and infrastructure improves, new investment opportunities are emerging in growing regions. Secondary cities and developing markets are attracting attention due to lower entry costs and strong growth potential. Investors who identify these areas early may benefit from long-term appreciation and rising demand.

Additionally, alternative property segments such as co-living spaces, logistics facilities, and flexible commercial properties are expected to grow steadily. These segments align well with modern lifestyle and business needs, making them attractive options for forward-thinking investors.

Conclusion

The future of property investment in 2026 will be shaped by innovation, sustainability, and informed decision-making. Investors who embrace technology, prioritise long-term value, and adapt to changing market conditions will be better positioned for success. Strategic planning and adaptability are of utmost importance in navigating the evolving real estate landscape.

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Featured image courtesy: Canva

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As Southeast Asia’s digital economy enters a new phase of expansion, trust is transitioning from buzzword to core economic infrastructure.

According to Acua’s Southeast Asia Digital Payment Trends 2026 report, the regional digital payments market is projected to exceed US$789 billion in transaction value, reflecting rapid adoption across platforms and services. This growth is being fuelled by an increasingly connected population and the rise of mobile wallets, super-apps, and digital financial services that reach more than 700 million consumers and millions of businesses across ASEAN.

Yet this remarkable momentum also reveals a structural tension: as digital adoption deepens, so too do systemic vulnerabilities. Cybersecurity is now becoming the layer that enables trust, which in turn fuels adoption, innovation, and economic participation.

Digital adoption is outpacing trust infrastructure

Southeast Asia’s digital economy continues to grow at a double-digit pace. According to the e-Conomy SEA 2025 report, the region’s digital ecosystem is on track to sustain robust expansion, with gross merchandise value (GMV) growing by roughly 15 per cent year-on-year.

Digital payments illustrate this acceleration clearly. Acua’s data shows transaction value rising from under US$250 billion in 2023 to nearly US$789 billion by 2026, signalling not just broader adoption, but deeper integration into daily commerce and enterprise operations across the region.

This growth, however, is not driven by convenience alone. As digital services become embedded in everyday economic activity, expectations around security, low-friction experiences, and cross-border interoperability rise in parallel. Consumers and businesses increasingly assume that systems will protect their data, funds, and identities by default.

As usage expands, so does the cost of insecurity.

In ASEAN, the cybersecurity market is estimated to reach US$6.44 billion in 2026, with projections pointing to a nearly 17 per cent compound annual growth rate through 2031 — a trajectory that closely mirrors the pace of digital adoption. Enterprise priorities are shifting accordingly. A 2024 PwC survey found that 84 per cent of business and technology leaders in the Asia Pacific have increased their cybersecurity budgets, with total security spending in the region expected to reach US$52 billion by 2027.

Together, these trends point to a clear reality: enterprises leading in digital transformation are also investing ahead of threats, recognising that trust now underpins everything from customer retention to regulatory compliance and operational resilience.

Also Read: From grid to code: Why good cybersecurity will help deliver net zero

From innovation to execution: where trust is really built

Despite abundant cybersecurity innovation across Southeast Asia, a persistent challenge remains: moving beyond pilots to scalable, enterprise-ready execution.

Many promising security tools stall in proof-of-concept limbo because they lack clear integration pathways, governance alignment, or measurable implementation frameworks. When cybersecurity solutions sit on the periphery of enterprise workflows — rather than being embedded into them — trust becomes fragile or superficial.

This gap is particularly visible in markets like Indonesia, where public-sector and private-sector technology stacks overlap. State-owned enterprises (BUMN), digital service providers, and startups increasingly operate within shared digital ecosystems, making execution complexity the real barrier to trust.

One approach to addressing this challenge is through integrated threat intelligence that aligns startup capability with enterprise reality.

A recent example comes from the collaboration between Digiserve by Telkom Indonesia and Cyfirma, a cybersecurity company in the MDI Ventures portfolio. Through this cooperation, Cyfirma’s Cyber Threat Intelligence (CTI) capabilities have been integrated into Telkom Solution’s enterprise portfolio, allowing customers not only to detect threats but to contextualise risk and act earlier.

As Roby Roediyanto, Director of MDI Ventures, noted, “One of the biggest challenges when startups work with enterprises or state-owned companies is ensuring from the outset that the solution truly addresses business needs and can be executed in practice. MDI helps match enterprise requirements with the most relevant portfolio solutions, then works with both sides to move the process from discussion to implementation and go-to-market.”

Similar approaches can be seen globally. In Singapore, Singtel Cyber Security integrates threat intelligence and managed security services directly into enterprise and telecom infrastructure across APAC, positioning cybersecurity as a foundational layer of digital trust rather than a bolt-on solution. 

Globally, major enterprise security players are adopting similar models. Palo Alto Networks integrates its Unit 42 threat intelligence directly into enterprise security platforms, enabling coordinated, real-time risk mitigation. Microsoft embeds threat intelligence into Azure, Microsoft 365, and Defender, ensuring security insights are woven into cloud and productivity infrastructure instead of operating as standalone tools.

This focus on relevance, execution, and repeatability — rather than theoretical innovation alone — highlights how cybersecurity increasingly functions as economic glue. When security capabilities are embedded into trusted enterprise channels with clear governance and go-to-market alignment, they strengthen confidence, accelerate adoption, and enable digital ecosystems to scale sustainably.

Governance: The often-overlooked half of trust

Technology without governance is like a vault without locks: it may be present, but it is not secure in a way that instils confidence.

To build repeatable trust in digital ecosystems, institutions are increasingly turning to structured governance mechanisms and transparent standards. In late 2025, MDI Ventures and AMVESINDO co-hosted Synergy Innovation Week, bringing together startups, corporate partners, and regulators — including OJK, Jamdatun, Bappenas, and Komdigi — to discuss governance alignment and trust frameworks that can support sustainable collaboration.

Initiatives like this, coupled with certifications such as ISO 37001 (Anti-Bribery Management System) and recognition like the Indonesia Trusted Company award — both achieved by MDI Ventures — illustrate how formal governance practices can strengthen stakeholder confidence across complex partnerships.

Also Read: In Southeast Asia, cybersecurity is booming but funding is not

Across the region, governments are also strengthening formal governance frameworks to support digital trust. Singapore’s Cybersecurity Act, for example, imposes stricter compliance and reporting obligations on operators of critical information infrastructure, reinforcing accountability in sectors such as finance, telecoms, and energy. By formalising oversight and incident reporting, such regulatory frameworks signal that cybersecurity is not optional but foundational to economic stability.

At the corporate level, global firms are also embedding governance into their cybersecurity strategies. Microsoft’s Secure Future Initiative, for instance, integrates security accountability across product development and executive oversight structures, signalling that governance is becoming embedded at the organisational core rather than treated as an afterthought.

Trust as repeatable economic infrastructure

As digital ecosystems scale across Southeast Asia, trust can no longer rely on informal relationships or one-off successes. It needs to be repeatable, institutionalised, and embedded into how partnerships operate.

This is especially relevant in environments where collaboration happens quickly and across many stakeholders. Trust is the foundation for consistent value creation — and for corporate venture capital (CVC) models in particular, governance and transparency are essential to maintaining credibility. This matters because interactions between founders, corporate partners, investors, and vendors often move at speed and with high intensity, leaving little room for ambiguity or misalignment.

When governance frameworks and transparent processes are in place, trust becomes less dependent on individuals and more anchored in systems. This allows collaborations to scale, reduces friction in execution, and increases confidence among ecosystem participants that partnerships can be repeated and expanded over time.

In this sense, trust functions much like economic infrastructure: it supports digital participation, enables long-term collaboration, and underpins sustainable growth. Without it, even the most advanced technologies struggle to deliver lasting impact at scale.

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Deliveroo’s decision to exit Singapore after an 11-year run is being read across the industry as a brutal referendum on food delivery economics.

In this interview, Varun Saraf and Rishabh Singhvi (co-founders of WhyQ, a leading workplace F&B platform in Singapore and a partner of Deliveroo), explain why the model breaks: the average basket is about SGD20, platforms may take 25-30 per cent (roughly SGD7 to SGD9), and last-mile delivery alone can swallow SGD7 to SGD9 before marketing, tech, or overhead even enters the chat.

The duo also revisits WhyQ’s 2021 partnership with Deliveroo to bring Mix & Match to hawker centres, and why WhyQ ultimately pivoted in 2023 to corporate B2B: scheduled, high-volume drops where food safety, invoicing, and reliability become “infrastructure”, not “convenience”.

Also Read: Deliveroo’s exit is a profitability warning shot

Interview excerpts:

In a social media post, you called Singapore B2C delivery “extremely tough” with “razor-thin margins.” What, specifically, breaks the unit economics here (last-mile costs, discounts, basket sizes, or merchant commissions) and which lever is the hardest to fix without damaging demand?

Saraf: The math for B2C delivery in Singapore is a zero-sum game. If you look at the breakdown for an average SGD20 basket size:

A merchant typically pays ~25-30 per cent commission, leaving the platform with a take of about SGD7 to SGD9.

In the current landscape, last-mile delivery costs — even with significant optimisation and aggregation — regularly fall within the SGD7 to SGD9 range.
When your entire gross margin is consumed by the rider’s fee before you even account for marketing, tech, or overhead, the model is broken. The most challenging lever to fix is consumer price sensitivity. If you pass that US$9 delivery cost directly to the customer, demand craters. If you squeeze the merchant further, they leave.

Most platforms like Grab and Foodpanda have used B2C food delivery to generate consumer demand and drive revenue through ads (featured merchants) and to support ancillary services like payments, taxi, and mart.

If a premium-led player couldn’t make Singapore work long-term, what does that say about the ceiling for differentiated, higher-quality delivery models in Southeast Asia? Does “premium” need a fundamentally different business model (not just branding)?

Saraf: In Southeast Asia, food is a passion, but delivery is treated as a utility, and the “on-demand” model is too expensive for a utility service.

For premium meals, a model in which the consumer bears a larger share of the delivery fee makes more sense. While this will impact demand, if a consumer wants a premium product, they are usually willing to pay a higher delivery fee. This can be seen in models like the one run by players like Oddle.

You said EBITDA positive is the 2026 survival metric. What are the three non-negotiable operating metrics you think delivery and food platforms should publish internally (and perhaps externally) to prove sustainability — contribution margin per order, retention without promos, rider utilisation, or something else?

Saraf: Food delivery platforms survive on a few simple yet powerful economic principles.

1. The batching rate. It is the number of orders a rider delivers on a single trip. Since profits are very thin, riders need to provide multiple orders on the same route. When one trip covers two or three deliveries instead of one, the cost per order goes down, and margins improve.
2. Purchase frequency. It refers to how often a customer orders each month. The more frequently users order, the less the company has to spend on discounts and marketing to bring them back. Subscription models exist mainly to increase this habit and make customer demand more predictable.
3. The average order value (AOV). It is critical because it costs almost the same to deliver a small order as a large one. Delivering $10 meal costs nearly as much as providing a $50 meal. So platforms need customers to spend more per order to spread out the delivery cost. That’s why they set minimum order amounts or promote combo deals.

Also Read: How mobile marketing is powering the next phase of food delivery growth in Southeast Asia

You wrote that for Deliveroo for Work users, this is “not just a vendor change… it’s an infrastructure decision.” In practical terms, what breaks first during a transition — billing/invoicing, dietary coverage, delivery service-level agreements, or merchant continuity — and how should companies stress-test a replacement provider before switching?

Singhvi: In a corporate environment, the first thing that breaks isn’t a line item on an invoice — it’s food safety. When you transition between providers, you are essentially trusting a new entity with the health of your entire workforce. Most platforms treat food as a commodity, but at the corporate level, it is a liability. If a provider hasn’t institutionalised regular kitchen audits, temperature monitoring, or strict protocols to prevent food from being cooked too early and left sitting, the system is fundamentally fragile.

How to stress-test a replacement: A one-week pilot is essential, but companies shouldn’t just look at the menu. They should stress-test for:

• Operational accountability: Is the delivery team in-house, or is it outsourced to the gig economy? Are the founders and support team available on WhatsApp for real-time updates?
• The “intelligence” layer: Does the provider meet complex dietary, budget, and packaging requirements? We use WhyQ Intelligence to ensure every meal is labelled with allergens and nutritional data—this is no longer “nice to have,” it’s a requirement for a modern workplace.
• Variety and reliability: Can they maintain merchant variety while consistently meeting delivery SLAs (no food safety incidents, no missing items, no incorrect items, no missing allergens or ingredients, sufficient portion size, no spillage, on-time delivery, and issue resolution) throughout the trial?

WhyQ positions itself around resilience: “2,000+ merchants”, “structured monthly invoicing”, and “operational discipline across food safety and delivery.” Which part is the hardest to build and maintain at scale in Singapore: merchant supply, logistics reliability, or enterprise-grade finance ops—and what do most consumer delivery platforms underestimate about that work?

Singhvi: Without question, the hardest pillar to build and maintain—and the one most underestimated by consumer platforms—is end-to-end food safety. When serving consumers, food safety is often treated as a merchant-level responsibility. At the enterprise level, that’s a massive risk. At WhyQ, we’ve built a proprietary safety infrastructure that starts long before a meal is even ordered. This is the hardest part to scale because it requires physical, boots-on-the-ground discipline.

What most corporate delivery platforms underestimate, and what makes our model unique, is the depth of our compliance:

• Expert audits: Every merchant undergoes a rigorous kitchen audit by food safety experts before they are even onboarded.
• Continuous monitoring: We don’t just audit once; we conduct quarterly site visits and maintain dynamic “merchant safety scores.”
• Chain of custody: We require merchants to retain daily food samples and to adhere to strict temperature-monitoring protocols. We ensure food is never cooked too early before dispatch—a common “hidden” risk in high-volume delivery.
• Full accountability: We maintain a database of all staff licenses and outlet certificates for our partners. In the rare event of an issue, we provide complete, transparent incident reports.

Deliveroo partnered with WhyQ in 2021 to bring Mix & Match to hawker centres. What did you learn from trying to productise hawker food for delivery—packaging, prep-time variance, peak-hour batching, pricing sensitivity—and what should platforms do differently if they want hawker economics to work?

Singhvi: We started this journey a decade ago. Our deep understanding of the Singaporean consumer is that there is a massive appetite for “Mix & Match” hawker dining. Still, it also showed why the B2C delivery model is fundamentally incompatible with hawker economics.

In the B2C world, the “on-demand” nature of the business is the enemy of the hawker. If you send a rider for a single SGD5 to SGD$7 order at 12:30 PM, the economics collapse. The platform’s take from a 30 per cent commission (SGD1.50 to SGD2.10) doesn’t even come close to covering the SGD7 to SGD9 last-mile delivery cost. To make it work, platforms have to charge high delivery fees that the mass-market consumer simply won’t pay for a “budget” meal.

Also Read: The future of food tech lies in building digitally autonomous restaurants

We realised that the only way to make hawker economics sustainable is to pivot to corporate B2B, which we did in 2023. Today, we work with leading tech giants and firms with over 50 pax daily orders across Singapore, in pockets like the Central Business District (CBD) and areas with limited access to good food, like Pasir Panjang, Science Park, and Paya Lebar Quarter. This moves hawkers from a “survival” model to a “growth” model through three key levers:

• High-volume predictability: Instead of the uncertainty of “on-demand” clicks, we provide hawkers with high-volume, 50-pax+ orders backed by fixed minimum order quantities (MOQs). This allows a solo operator to plan, prep, and batch with 100 per cent certainty.
• Off-peak utilisation: Corporate orders are scheduled. This allows hawkers to fulfil large-scale orders before their own peak walk-in lunch rush. We are effectively creating a “pre-lunch revenue shift” during hours that were previously underutilised.
• Segment access and sustainability: In a B2B model, we aggregate demand into a single “drop,” turning fragmented delivery into high-AOV infrastructure. This gives merchants access to a premium corporate segment they never had. Merchants are happy to offer sustainable commissions because the volume is incremental, efficient, and requires zero additional marketing spend from them.

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