Singapore-headquartered enterprise AI company Whale has raised a US$40 million extension to its Series C round, bringing the total Series C financing to US$100 million, as it looks to expand deployments across Asia Pacific and North America.

The extension was led by CMB International, through an investment fund focused on AI and frontier technology, and SMBC Asia Rising Fund, the corporate venture capital arm of Sumitomo Mitsui Banking Corporation.

Other investors in the extension include Krungsri Finnovate, Singtel Innov8, Hyundai Motor Group, and Charisma Partners.

Also Read: Why most enterprise AI in APAC is still stuck in the proof-of-concept room

Earlier participants in the Series C included Bosch Ventures, MTR Lab, MDI Ventures, Gentree Fund, and Linear Capital.

Whale said the new capital will support team expansion, enterprise partnerships and platform integrations with local infrastructure. The company operates across Japan, Indonesia, Malaysia, Thailand, and other Asia-Pacific markets, alongside a growing North American base. It also plans to enter the Middle East, North Africa and Europe.

Founded as an enterprise AI company, Whale builds what it calls an AI Operating System for business operations. Its core pitch is that large companies need AI systems that do not merely analyse documents, chat logs or internal databases, but also interpret signals from physical environments such as stores, showrooms, restaurants, factories and commercial facilities.

From cameras to operational decisions

Whale’s technology is built around its proprietary Business World Model, which it describes as an AI model designed to process signals from cameras, sensors and audio in a way comparable to how large language models process text.

Its main products include SpaceSight, which uses cameras and IoT sensors to track foot traffic, dwell time, engagement and compliance in physical locations, and Echo, which analyses frontline sales conversations to identify performance patterns and training needs. Other products cover content distribution, workflow automation, knowledge management, compliance, AI infrastructure and governance.

The company says it serves more than 1,600 enterprises in over 45 countries and manages more than 600,000 edge AI nodes globally. Its customers operate across retail, automotive, food and beverage, manufacturing, financial services, healthcare, fashion and apparel.

Jerry Ye, founder and CEO of Whale, said the round is intended to deepen existing work rather than fund a new direction.

“Enterprises across regions are grappling with rising operational costs, and the urgent need to turn unstructured operational data into decision-ready intelligence,” he said. “We’re scaling our teams globally, deepening enterprise partnerships, and expanding our platform integrations with local infrastructure.”

The comment points to a wider shift in enterprise AI. After two years of intense interest in generative AI pilots, large companies are now under pressure to show measurable returns. That is particularly relevant in Southeast Asia, where retailers, banks, logistics firms and manufacturers often operate across fragmented markets, uneven infrastructure and highly localised customer behaviour.

Southeast Asia’s physical economy is the test case

Whale’s Southeast Asian relevance lies less in the novelty of its model and more in where it is being deployed. The region remains a heavily offline economy despite rapid digital adoption. Google, Temasek and Bain have projected Southeast Asia’s digital economy could reach about US$1 trillion in gross merchandise value by 2030, but a significant share of commercial activity still runs through physical stores, bank branches, dealer networks, food outlets and service counters.

Also Read: Enterprise AI hits barriers as privacy, sovereignty demands grow

That makes AI systems for physical operations attractive to enterprises trying to improve productivity without adding headcount. In markets such as Indonesia, Thailand, Malaysia and Vietnam, companies often face labour shortages in skilled frontline roles, high staff turnover and rising wage pressure. AI tools that monitor service quality, compliance, customer engagement and sales execution could appeal to large retailers, quick-service restaurant chains, automotive distributors and financial institutions.

At the same time, the opportunity comes with constraints. Southeast Asian regulators are paying closer attention to AI governance, data localisation, privacy and biometric surveillance. Singapore has taken a relatively pro-innovation approach through frameworks such as AI Verify, while Indonesia, Thailand, and Malaysia have been developing or updating personal data protection regimes. Any system that relies on cameras, audio or sensor data will need to address consent, retention, explainability and cross-border data processing.

That is where Whale’s strategic investors may matter. Krungsri Finnovate brings links into Thailand and ASEAN through Bank of Ayudhya and MUFG. Singtel Innov8 can offer telecommunications and enterprise connectivity channels. SMBC and CMBI provide access to banking and corporate networks in Japan, China and broader Asia.

Palida Artispong, Acting Managing Director and Head of Portfolio Growth and Investor Relations at Krungsri Finnovate, said the investment reflects Whale’s ability to support “a full-suite, omnichannel product across the entire customer journey”, adding that Krungsri’s footprint in Thailand and ASEAN could help the company expand regionally.

A crowded market with different entry points

Whale is entering a competitive field. In physical space analytics, companies such as RetailNext, Trax, and Verkada have built businesses around in-store intelligence, inventory visibility, computer vision and security. In industrial and connected operations, Samsara and other IoT platforms help enterprises collect and act on sensor and fleet data. In voice and sales intelligence, players such as Observe.AI, Gong and CallMiner focus on customer conversations and performance coaching.

China-born computer vision companies such as SenseTime and Megvii have also spent years selling AI into retail, transport and security settings, though geopolitical concerns and regulatory scrutiny have affected their global expansion. In Southeast Asia, enterprises often rely on a mix of local systems integrators, cloud providers, CCTV vendors and point solutions rather than a single AI operating layer.

Whale’s challenge is therefore not just technical. It must persuade enterprises to consolidate operational data into its platform, integrate with legacy systems and trust its governance controls. That can be a slow sales cycle, especially in regulated sectors such as banking and healthcare.

SMBC’s Mayoran Rajendra, Managing Director and Head of AI Transformation Office, said Whale’s ability to structure data from physical environments was the key attraction. He said combining Whale’s technology with SMBC Group’s client network could help deliver value “across industries and regions”.

Also Read: The big flip: Why being “smart” isn’t enough for enterprise AI in 2026

For Whale, the US$100 million Series C gives it capital and strategic distribution at a time when enterprise AI budgets are becoming more selective. IDC has forecast continued double-digit growth in AI spending across Asia-Pacific, but buyers are increasingly demanding use cases tied to cost reduction, compliance, productivity and revenue conversion.

The next phase will test whether Whale can move beyond impressive deployment numbers and prove durable enterprise outcomes across different regulatory, linguistic and operational environments. In Southeast Asia, where physical commerce remains central to the economy, that may be the difference between another AI platform story and a business that becomes embedded in how companies actually run.

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Food waste is a US$1T global problem, and Southeast Asia sits at its bleeding edge. Hotels and commercial kitchens across the region discard tonnes of food daily, not from carelessness, but from an absence of data. That gap is exactly what Singapore-based Lumitics was built to close.

Winnow’s acquisition of Lumitics is not just a tuck-in deal. It signals something more structurally important: that AI-powered operational tools built for and in Southeast Asia are now attractive enough to command the attention of category-leading acquirers from Europe.

Lumitics had already deployed its computer vision waste-tracking system across major hotel chains in Singapore and the wider region. Winnow, which counts IKEA and Hilton among its clients, now gains an Asian foothold it would have taken years to build organically.

For the SEA ecosystem, the message is clear. Deeptech solutions targeting unglamorous but high-cost operational problems (food waste, energy, and supply chain leakage) are real acquisition targets. This is not a story about climate tech optics. It is a story about enterprise procurement, measurable ROI, and the moment a regional niche becomes a global category. More of this, please.

Read the full story here.

REGIONAL

Rize raises US$31M to scale low-emission rice farming in SEA: The climate agri-tech startup targets methane reduction across paddy farms in Vietnam, the Philippines, and Indonesia, where rice cultivation accounts for a significant share of agricultural emissions.

CapBay, MDEC launch US$47M debt pool for Malaysian tech firms: The financing facility targets Malaysian tech SMEs underserved by traditional bank lending, combining CapBay’s supply chain finance platform with MDEC’s mandate to grow the digital economy.

Tighter digital rules could cut Malaysian startup VC funding by 26%: Oxford Economics warns that proposed platform regulations risk deterring foreign investors at a critical moment for Malaysia’s startup ecosystem, with potential GDP impact running into billions.

Crypto.com secures US$400M from Citadel Securities: The Singapore-headquartered exchange lands a high-profile strategic backer as it pushes for broader institutional credibility ahead of a potential public listing.

Whale raises US$40M, lifts Series C to US$100M: The Singapore fintech targets MENA and European expansion after building a wealth management platform for affluent retail investors across Asia.

pQCee raises US$9.3M to enter post-quantum cybersecurity: The Singapore-based startup is among the first in SEA to commercialise quantum-resistant encryption, positioning the city-state in an emerging global security race.

Startupbootcamp’s Singapore sustainability cohort targets real impact: Unlike earlier climate-tech batches, the latest Singapore cohort focuses on ventures with measurable emissions outcomes and enterprise-ready solutions, reflecting a broader maturation in how accelerators select for climate relevance.

Temasek offloads 2% stake in Lenskart for Rs 1,945 crore: The partial exit values the Indian eyewear unicorn at roughly US$5B, with Singapore’s state investor trimming its position as secondary market activity in Indian tech picks up pace.

GovTech Singapore retrenches 93 staff in two-year workforce shift: The restructuring reflects a deliberate pivot towards smaller, higher-skilled headcount as the agency automates more functions and consolidates its technology stack.

GenAI to affect 80M ASEAN workers, but mass job losses stay absent: A new ILO report finds AI will reshape tasks rather than eliminate roles wholesale across the region, though low-skilled service workers face the steepest displacement risk.

Malaysia faces a 163,000-worker AI skills gap: Only 37% of Malaysian firms are actively training staff on AI tools, leaving a structural talent deficit that risks slowing the country’s digital economy ambitions.

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INTERVIEWS & FEATURES

IPHatch turns dormant MNC patents into startup equity across Asia: The Singapore platform matches underused corporate IP with early-stage startups, exchanging licensing rights for equity, a model gaining traction as MNCs seek non-cash innovation returns.

21 Singapore startups investors can’t stop funding: e27’s deep-dive profiles the city-state’s most consistently backed ventures, spanning fintech, deep tech, and climate, revealing where conviction capital is concentrating in 2026.

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INTERNATIONAL

Uber’s US$14.8B Delivery Hero deal would nearly double its footprint: The proposed acquisition would hand Uber dominance in food delivery across dozens of markets, including several in Southeast Asia where Delivery Hero’s Foodpanda brand still operates.

Apple Intelligence approved for China launch via Alibaba’s Qwen AI: Beijing’s approval marks a significant regulatory breakthrough, with Apple required to partner with a domestic AI provider, a model that could set precedent for other markets including in SEA.

DeepSeek in talks to raise US$1.5B, valued at US$51.9B: The Chinese AI lab is moving to formalise external investment ahead of a public listing that would reshape how global markets value open-weight AI development.

Anthropic and Blackstone bet the next AI trillion is in implementation: The two firms are jointly backing enterprise AI deployment over foundational model development, a thesis with direct implications for how SEA system integrators and B2B SaaS players position themselves.

Indian AI coding startup Emergent becomes a unicorn in just over a year: Emergent’s rapid ascent to a US$1B valuation underscores the accelerating pace of AI startup formation in South Asia, with implications for SEA’s own developer-tool ecosystem.

BP shuts its corporate venture arm after 20 years: The closure of BP Ventures signals a broader retreat of energy majors from direct startup investment, a trend that could reduce a funding channel for SEA climate and energy-tech startups.

Visa expands crypto push with new stablecoin platform: Visa’s stablecoin infrastructure move accelerates the mainstreaming of digital currency payments, with particular relevance for SEA markets where cross-border remittance and e-commerce volumes are high.

Alpaca raises US$135M for tokenised stock infrastructure: The crypto brokerage’s raise backs a platform enabling retail access to tokenised equities, a model that could accelerate capital markets democratisation across SEA’s underbanked populations.

DeepMind CEO calls for independent body to regulate frontier AI: Demis Hassabis’s proposal for an international AI standards body echoes calls from SEA regulators grappling with how to govern foundation models without stifling local innovation.

UK regulator to probe TikTok’s child safety measures: The ICO investigation into ByteDance’s platform follows similar actions in the EU and sets a regulatory precedent that SEA governments, several of which are drafting platform safety laws, are likely watching closely.

Paytm remains majority Indian-owned for second consecutive quarter: Paytm’s ownership data is significant given India’s fintech sovereignty concerns, and mirrors debates in SEA over foreign control of domestic payment infrastructure.

SpaceX aborts second Starship v3 launch after ignition: The unexpected abort raises questions about the timeline for Starship’s commercial readiness, with implications for satellite launch costs and LEO connectivity plans across SEA.

SF mayor pushes for tougher rules after Waymo traffic fiasco: The regulatory response to autonomous vehicle incidents in San Francisco is being watched by SEA city planners exploring AV pilots in Singapore, Jakarta, and Kuala Lumpur.

Sheryl Sandberg leads US$10M investment in AI vehicle inspection: The funding round backs an AI-powered inspection platform targeting fleet operators and insurers — a use case with direct relevance to SEA’s large two-wheeler and ride-hailing vehicle markets.

Google renames NotebookLM to Gemini Notebook: The rebrand consolidates Google’s AI tools under the Gemini umbrella, signalling a push for deeper product integration as competition with Microsoft Copilot and OpenAI intensifies across enterprise and education segments.

Bitcoin at US$63,780: on-chain signals point to continued bear pressure: Despite short-term price stabilisation, key on-chain metrics suggest Bitcoin has not yet formed a genuine macro bottom, with exchange inflows and miner behaviour indicating persistent selling pressure.

Is the US$63,619 Fibonacci level enough to halt Bitcoin’s unwind?: Technical analysis examines whether a key retracement level can absorb continued selling, or whether Bitcoin risks sliding back towards US$62,498 in the near term.

Bitcoin at US$63,780: buying opportunity or trap?: The analysis weighs bullish accumulation signals against macro headwinds, arguing that retail buyers entering at current levels may be absorbing distribution from larger holders.

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CYBERSECURITY

Deepfake fraud losses hit US$3.7B as scams spread beyond social media: AI-generated identity fraud is migrating from consumer platforms into corporate finance and KYC processes, raising urgent questions for SEA fintechs and banks reliant on digital onboarding.

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SEMICONDUCTOR

The Nvidia clampdown is a warning for SEA’s AI boom: US export restrictions on advanced chips expose a critical vulnerability in Southeast Asia’s AI infrastructure ambitions, forcing governments and hyperscalers to rethink supply chain and compute strategies.

Nvidia deepens Japan push with expanded AI partnerships: Nvidia’s latest Japan commitments, including the Toyota smart-cities deal, signal how the chipmaker is locking in strategic partnerships across Asia as US export controls reshape its global playbook.

AI

AI’s trillion-dollar lease overhang is off the books, not off the hook: The hidden liability embedded in long-term GPU and data centre leases by AI companies represents a systemic financial risk that investors and regulators have yet to fully price in.

The fatwa lag: AI is outpacing Islamic finance governance: Shariah advisory bodies are struggling to issue rulings fast enough to keep pace with AI-driven fintech products, creating a compliance vacuum in SEA’s large Islamic finance markets.

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THOUGHT LEADERSHIP

Asia turns football’s year-round calendar into a fan engagement war: Sports-tech platforms across the region are monetising expanded fixture schedules through live commerce, fantasy tools, and localised content, reshaping how clubs and sponsors reach Asian audiences.

SEA stopped waiting for the West; it built the rails: The article examines how regional payment infrastructure, logistics networks, and cross-border data frameworks have matured enough to power a new generation of home-grown platform businesses.

A zero-nuclear region is suddenly betting on reactors: With energy demand from data centres and AI infrastructure surging, several SEA governments are revisiting nuclear as a credible baseload option, a position unthinkable five years ago.

Gemini’s SEA growth puts local-language AI at the centre: Google’s expanding footprint in Southeast Asia is accelerating the race among AI assistant providers to achieve fluency in Bahasa, Thai, Vietnamese, and Filipino — languages long underserved by foundational models.

The sovereignty of judgement: why human intelligence is your startup’s last moat: In an era of AI commoditisation, the author argues that a founder’s capacity for contextual, values-driven decision-making, not proprietary data or models, is the only defensible edge left.

Sovereign alpha: an investment thesis for a scarcer world: The piece makes the case that resource scarcity, deglobalisation, and state-led industrial policy are creating a new class of investable assets that conventional VC frameworks are ill-equipped to evaluate.

AI and the crisis of recognition: do we still see the human behind the words?: The essay exploreshow AI-generated content is eroding the social contract of written communication and what that means for trust, authorship, and credibility in media and business.

Product symbiosis: when two features create unexpected value together: The author examineshow compounding feature interactions, rather than individual capabilities, drive the most durable user retention, drawing on examples from SEA’s super-app ecosystem.

Gen Z isn’t hard to manage. You just need to rethink how you lead: The piece challenges the assumption that younger workers are disengaged, arguing instead that traditional management frameworks are misaligned with how Gen Z processes authority and purpose.

Burnout isn’t just personal; it’s becoming an operations problem: The author reframes employee burnout as a structural systems failure rather than an individual wellness issue, with measurable impact on team output, retention, and product quality.

The new travel bottleneck isn’t booking; it’s staying operational: The piece identifies connectivity, device management, and remote-work infrastructure as the real friction points for business travellers in 2026, overtaking traditional pain points like ticketing and accommodation.

Your customers aren’t buying your product; they’re buying a better self: The author applies identity-driven consumer psychology to B2C startup positioning, arguing that the most effective SEA brands sell transformation, not features.

Can a Fortune 100 sales director actually close deals for your startup?: The piece dissects the mismatch between enterprise sales experience and early-stage startup realities, warning founders against over-indexing on pedigree when hiring their first revenue leads.

 

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Software is no longer the primary driver of alpha; physical sovereignty is. Market value is shifting from “software-only” models to “control points” where technology meets physical security and national resilience. In this new operating environment, capital is moving away from pure digital scalability and toward the “Sovereign Alpha”—the premium generated by infrastructure that ensures a nation’s ability to function under geopolitical duress.

Startup valuations in Southeast Asia (SEA) are being redefined. We are seeing a transition from revenue-based multiples (SaaS) to capacity-and-resilience multiples (Hard Tech). The new value is anchored in a unified “Sovereign Tech” stack defined by three pillars:

• Energy and utility resilience: Power and water access as mission-critical industrial capabilities.
• Embodied intelligence: The transition of AI from digital models (LLMs) into physical robotics and autonomous industrial systems.
• Secure infrastructure: Hardened digital frameworks, including “Pax Silica” semiconductor chains and Orbital Compute layers.

This shift moves the needle from “global efficiency” to “national resilience.” The primary product is no longer the code itself, but the secured power and resource access required to run it.

Energy as operational security: Beyond the utility model

Energy, water and connectivity have transitioned from back-office utility costs to mission-critical industrial requirements. The most significant signal of this shift is found in the private sector’s frontier: SpaceX/xAI has officially added water access to its IPO risk factors, noting that “significant water resources” are now a critical consideration in site selection. Water scarcity is now a direct bottleneck for AI compute capacity.

In the state sector, “Mission Assurance” is the new standard. The US Navy’s plan to power Naval Station Norfolk using the nuclear reactors of the USS Gerald R. Ford signals that grids are now treated as active battlespace vulnerabilities. For SEA investors, this means site selection for data centres and fabs is no longer about tax incentives; it is about “islanding” capability.

Also Read: Enterprise AI hits barriers as privacy, sovereignty demands grow

The energy-security nexus

The “Hormuz risk” is no longer an episodic crisis; it is a structural tax on SEA supply chains. Iran’s introduction of maritime fees creates a permanent cost layer. Consequently, startups must prioritise “energy-aware” site selection where domestic firm power—and water rights—are guaranteed.

Embodied intelligence: China’s industrial blueprint and the SEA response

The frontier has moved from “Software AI” to Embodied AI. China’s 2026 World Intelligence Expo provided the blueprint: a state-led push for 10,000 units of humanoid robots and the standardisation of intelligence across 100 high-value applications. This is a parallel to the COMAC C919 passenger jet program—evidence of a broader industrial-policy logic aimed at building an integrated, autonomous stack of aviation, robotics, and AI.

Investors should ignore the humanoid spectacle and focus on the boring control points that generate high margins and create defensive moats:

• Servo motors: High-precision components driving robotic dexterity.
• Harmonic reducers: Precision gearboxes essential for industrial torque.
• Torque sensors: The critical feedback loop for human-robot collaboration.
• Edge AI chips: Specialised silicon for local environment processing, reducing cloud dependency.

While China leads with state-directed deployment, SEA startups have a massive opportunity to localise these “Robot Stack” technologies for regional manufacturing, healthcare, and logistics. Localising these control points is the only way to build an industrial base decoupled from fragile, long-distance supply chains.

The geopolitical startup beta framework

Every startup now carries a “Geopolitical Beta”—the inherent risk or advantage gained from its host country’s alignment and infrastructure depth. We evaluate SEA startups using a 3×3 framework based on Infrastructure Depth (Power/Water/Logic) and Geopolitical Alignment (Sovereignty/Neutrality).

Also Read: The hard truth about Asia’s energy future: Why we need a new class of sovereign alternatives

• The winning quadrant (high alignment/high depth): Startups in neutral hubs like Singapore or Malaysia command a “sovereign premium.” Singapore’s gold-clearing ambitions and Malaysia’s local-currency settlement push are “Financial Sovereignty” tools that reduce dollar-dependence risk and insulate capital.
• The at-risk quadrant (low alignment/low depth): Startups in jurisdictions with failing grids and high political volatility face a “Geopolitical Discount.” These entities are treated as strategic liabilities rather than assets.

Capital Policy Signal: The potential upgrade of Vietnam to MSCI emerging-market status, contrasted with Indonesia’s downgrade risk, serves as a proxy for a nation’s “Capital Policy.” Nations that maintain market accessibility and clear “Sovereign Moats” attract the deepest pools of resilient capital.

Orbital infrastructure is the ultimate defensive moat. SpaceX’s 11-million-square-foot Gigasat factory and the AI1 satellite (150-kilowatt peak compute) represent the first “Orbital Control Points.” SEA startups must identify their “local control points” in this manner—bottlenecks in energy management or mineral refining that are as indispensable as ASML’s lithography tools.

Strategic outlook: Investing in the ready-to-build economy

The strategy has shifted from “Asset-Light” to “Infrastructure-Deep.” Execution capacity in the physical world is the only metric that matters. For Southeast Asia, we maintain high conviction in three specific sectors:

• Grid-interactive AI infrastructure: Data centres that incorporate their own baseload generation (nuclear/hydro) and treat water as a primary input.
• Defence-industrial co-production: Localised assembly of sensors, autonomous systems, and secure communications to reduce reliance on foreign primes.
• Resource-state value chain expansion: Moving from raw ore exports to domestic refining and precursor production (e.g., Indonesia’s nickel and Australia’s lithium-processing models).

To founders: Stop treating resilience as a cost centre; it is your primary product.

To VCs: Short-sell pure software scalability and prioritise companies that secure their own physical inputs.

In a world of contested chokepoints and utility scarcity, the Sovereign Alpha belongs to those who own the physical infrastructure of resilience. Prioritise execution capacity in the physical world over the digital mirage.

These signals were derived from the Geopolitical Action from Leaders weekly newsletter. 

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The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.

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Rize, a Singapore-based sustainable rice platform, has raised US$31 million in Series B financing to expand its work with smallholder farmers in Vietnam and Indonesia and push further into traceable, low-emission rice exports.

The round comprises US$20 million in equity led by BNP Paribas Asset Management Alts, with participation from The Rockefeller Foundation, Temasek, and Breakthrough Energy Ventures.

The remaining US$11 million comes as debt financing from UOB, BIDV, and Temasek Foundation.

This round comes two years after the firm closed its US$14 million in Series A, co-led by Breakthrough Energy Ventures, GenZero, Temasek, and Wavemaker Impact.

Also Read: Rize seeks to decarbonise rice cultivation in Asia with US$14M Series A raise

The fresh capital raise brings Rize’s total funding to US$47 million. The company said it will use the capital to expand export market linkages, improve field-to-buyer traceability, build AI tools for farmers and field teams, advance carbon certification, and enter additional markets in Southeast Asia.

Rize currently works with 17,000 smallholder farmers across more than 50,000 hectares in Vietnam and Indonesia. It says it has a 250-person field, agronomy, and technology team, and has shipped 1,500 metric tonnes of low-emission rice to buyers in Europe, Canada, Australia, and Singapore.

The company aims to reach more than 300,000 hectares and over 150,000 smallholder farmers by 2030.

Why rice is now a climate finance target

Rice is a staple food for more than half of the world’s population, but it is also one of agriculture’s most difficult climate problems. Flooded paddy fields create anaerobic conditions that produce methane, a greenhouse gas far more potent than carbon dioxide over a 20-year period.

Rize cites estimates that rice cultivation accounts for roughly 12 per cent of global methane emissions, comparable to the climate footprint of the aviation industry. The issue is especially material in Asia, which produces and consumes around 90 per cent of the world’s rice, according to the International Rice Research Institute.

For Southeast Asia, the problem is not abstract. Vietnam and Thailand are among the world’s major rice exporters, while Indonesia remains one of the largest rice producers and consumers. Governments in the region are under pressure to balance food security, farmer incomes, water use, and emissions reduction, a combination that has attracted climate investors but remains difficult to execute at farm level.

Rize’s core intervention is Alternate Wetting and Drying, or AWD, an irrigation method supported by the International Rice Research Institute and CGIAR. Instead of keeping paddy fields continuously flooded, farmers periodically allow fields to dry before re-irrigating them. Rize says the method can cut methane emissions by up to 50 per cent, reduce water use by 20 to 30 per cent, and raise farmer income by up to 30 per cent without reducing yields.

Also Read: Climate tech’s shift from doing good to doing well

Those figures are meaningful, but the commercial challenge lies in consistent adoption. AWD requires farmer training, water control, monitoring, and proof that practices were followed. In fragmented smallholder markets, that is often where climate agriculture projects fail.

From agronomy to export markets

Rize’s model attempts to link farm-level practice change with export-grade procurement and carbon finance. The company works with smallholders on AWD adoption, residue compliance, and traceability, while connecting output to buyers seeking lower-emission rice.

Maximum Residue Limit compliance is a key part of that strategy. Export markets in Europe, Japan, Singapore, and other higher-value destinations have strict requirements on pesticide and chemical residues. For smallholders, meeting those standards can be difficult without advisory support, input discipline, and predictable procurement.

The company says its rice is traceable to field level. That matters because low-emission commodity claims are increasingly scrutinised by buyers, regulators, and carbon market participants. Traceability is also becoming more important as large food companies face pressure to report Scope 3 emissions in agricultural supply chains.

“This investment allows us to unlock the next phase of growth by further expanding scale, investing in market linkage and exports, and cutting-edge technologies to deliver better decision-making, better productivity, and better outcomes across the whole value chain,” said Dhruv Sawhney, co-founder and CEO of Rize.

Rize emerged in late 2022 from a collaboration involving Temasek, 100×100, and Breakthrough Energy Ventures, with 100×100 involved in the early build. Its rapid scale-up, from launch to 17,000 farmers in roughly four years,  reflects both investor interest in climate-linked agriculture and the sizeable opportunity in Southeast Asian rice systems.

Carbon claims face a higher bar

The company is also building a carbon credit pathway. Its Sustainable Rice Production in Southeast and South Asia project has received a BeZero Carbon ex ante rating of A.pre, which indicates a high likelihood that future credits will represent one tonne of carbon dioxide equivalent avoided or removed. Rize said the project is progressing through Gold Standard certification, with more than one million credits forecast over the next five years.

That will be closely watched. Carbon markets have faced sustained criticism over project quality, additionality, permanence, and verification. Agriculture projects are particularly complex because emissions vary by soil, water regime, farmer behaviour, and local climate conditions. An ex ante rating is not the same as issued credits, and buyers will need confidence that claimed reductions are measurable and durable.

Still, rice methane reduction has become one of the more credible areas of agricultural climate mitigation because the mechanism is relatively well understood: less continuous flooding generally means less methane. The harder question is whether a company can verify and monetise that across thousands of smallholder plots without creating unsustainable monitoring costs.

Alexandre Martin-Min, Head of Natural Capital and Impact Investments at BNP Paribas Asset Management Alts, said Rize sits at “the intersection of sustainable agriculture, carbon finance, and verified commodity trade”. That intersection is also where competition is likely to intensify.

A crowded but underbuilt market

Rize does not fit neatly into one category. It overlaps with agritech advisory platforms, sustainable commodity traders, carbon project developers, and supply-chain traceability providers. In Southeast Asia, companies such as AgriG8 have also targeted lower-emission rice and carbon-linked farmer programmes, while broader agritech players offer farm management, input, and financing tools. Globally, firms including Indigo Ag and other carbon farming platforms have tried to connect regenerative practices with corporate climate demand.

Large agribusiness groups may prove just as relevant as startup competitors. Commodity traders and food companies already control procurement relationships, logistics, and buyer access. If low-emission rice becomes a premium procurement category, incumbents may build or acquire similar capabilities.

Also Read: Funded: SEA climate tech has US$1.1B and a problem no one wants to name

Rize’s advantage, if it can sustain it, lies in combining field operations with export channels and verification infrastructure. The debt portion of the round also suggests lenders see some asset-backed or trade-linked potential in the model, not just venture-style growth.

The next test is execution. Moving from 50,000 hectares to 300,000 hectares will require not only capital but local partnerships, irrigation coordination, buyer demand, and farmer trust. For Southeast Asia’s rice sector, the stakes are clear: decarbonisation cannot come at the cost of food security or smallholder livelihoods. Rize’s new funding gives it a larger platform to prove that those goals can coexist.

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Startupbootcamp has graduated the first cohort of its Sustainability Singapore accelerator, backing nine pre-seed startups working across food and agritech, alternative finance, and trade and logistics.

The cohort pitched to investors, corporate partners and government agencies at a Demo Day held at Temasek Shophouse in Singapore, following a 12-week programme run through SBC Sustainability Singapore, the accelerator’s dedicated investment vehicle.

Also Read: Turning intimidation into innovation: Embracing sustainability’s new opportunities

Startupbootcamp said the vehicle plans to invest in 60 startups over six cohorts. It did not disclose the amount invested in each company.

The programme is anchored around three sectors that sit close to Singapore’s economic vulnerabilities: food security, supply chains, and finance. The city-state imports more than 90 per cent of its food, runs one of the world’s busiest transshipment ports, and has spent years positioning itself as a regional financial centre. Those same dependencies are increasingly being reframed as investable markets as climate shocks, trade fragmentation and financial exclusion create demand for new infrastructure.

“Singapore’s ambition to lead on sustainability can’t be delivered by policy alone, it needs a pipeline of founders solving the hard problems in food security, clean trade and inclusive finance,” said Ricardo Costa, Head of Singapore at Startupbootcamp.

Singapore’s resilience thesis

The accelerator’s focus is closely aligned with Singapore’s policy agenda. Under the Singapore Green Plan 2030 and the Singapore Food Story, the government has pushed for lower-carbon growth, stronger domestic food capabilities and more resilient supply chains. Its “30 by 30” target aims to produce 30 per cent of the country’s nutritional needs locally by 2030.

The commercial question is whether early-stage startups can build venture-scale companies around those priorities.

Southeast Asia has no shortage of sustainability ambition, but funding has become more selective. After the broader venture correction, climate and sustainability startups increasingly need to show commercial pull rather than rely on policy momentum. A Bain, Temasek, GenZero and Standard Chartered report has estimated that Southeast Asia will need about US$1.5 trillion in cumulative green investment by 2030, but only a fraction of that capital has reached early-stage companies.

This gap has created room for accelerators, corporate venture arms, and specialist funds to position themselves between policy targets and investable startups. In the region, players such as Wavemaker Impact, Circulate Capital, Antler and Iterative have backed climate, resource efficiency, circular economy and supply-chain companies, though with different fund models and risk appetites.

Startupbootcamp’s bet is narrower: identify pre-seed companies that can use Singapore as a capital, customer and credibility base while selling into regional or global markets.

The nine companies

The inaugural cohort includes three food and agritech startups.

AgroNest Ventures uses AI, drones, and sensors to help precision farmers reduce input costs and improve yields. The company claims its platform can lift yields by up to 40 per cent, though such productivity gains typically depend on crop type, farm size and adoption conditions.

AlgaTrop is building a seaweed processing business focused on tropical supply chains, turning smallholder harvests into standardised biostimulants. Seaweed has become a focus area for climate and agriculture investors because of its potential use in fertilisers, animal feed, biomaterials and carbon-related applications, but the sector still faces constraints around quality control, logistics and farmer economics.

Also Read: Why sustainability will be the biggest competitive advantage for startups in 2025

Everlend Agritech operates a seed-credit and marketplace model for smallholder farmers in East Africa. The company says it has financed 800 farmers and helped triple yields while increasing incomes by 45 per cent.

The fintech and alternative finance track includes four companies.

Bheja.ai is automating mortgage refinancing for Australian homeowners, targeting the so-called loyalty tax paid by customers who remain on less competitive rates.

Pramaanit Technologies is developing tamper-proof digital credentials for universities, governments and employers, a market that overlaps with digital identity, education verification and workforce mobility.

Receitly converts digital receipts into post-purchase data for retailers and consumers.

Sendcoins is building stablecoin-based cross-border payment rails for migrant workers, students and small businesses.

The stablecoin angle is particularly relevant in Southeast Asia, where remittances, cross-border commerce and fragmented banking infrastructure continue to create openings for non-bank payment rails. At the same time, companies in this space face a more demanding regulatory environment. Singapore has moved to regulate stablecoins and digital payment token providers more tightly through the Monetary Authority of Singapore, while other regional markets have taken varied approaches to crypto-linked payments.

The trade and logistics track includes Genesys One and ShypV.

Genesys One is building digital passports for mineral supply chains, creating traceability from mine to market. This sits within a wider push for supply-chain transparency as manufacturers, banks and regulators demand better evidence on sourcing, carbon exposure and labour standards.

ShypV offers an AI-powered platform for small and mid-sized retailers, claiming efficiency gains of up to 26 per cent.

From accelerator to commercial traction

The 12-week programme began in Bangkok, where Startupbootcamp participated as the official Startup and Investor Park partner for Money20/20. Founders then moved into a residential week in Singapore that included a site visit to The GEAR by Kajima, an investor dinner, a fintech meet-up co-hosted with This Week in Fintech, and a corporate-startup collaboration session at SGInnovate.

Startupbootcamp said more than 150 mentors supported the cohort across venture de-risking, commercial acceleration and fundraising preparation.

The accelerator brings a global network into the programme. Since 2010, Startupbootcamp says it has accelerated around 1,700 startups across more than 20 countries. Its alumni have raised approximately US$2.9 billion in funding, based on the company’s stated figure of €2.7 billion.

Also Read: Need of the hour: How agritech platforms can protect farmers from climate change

For Singapore, the test will be whether programmes such as this create companies that remain commercially tied to the region, rather than simply using the city-state as a fundraising stop. Many accelerators have struggled to convert demo-day visibility into sustained customer traction, especially in sectors where sales cycles depend on banks, governments, agribusinesses or logistics incumbents.

Still, the timing is not incidental. Southeast Asia’s food systems are exposed to climate volatility, its logistics networks are under pressure from trade shifts, and its financial systems continue to leave gaps for smaller businesses and cross-border workers. Startupbootcamp’s first cohort reflects where early-stage sustainability investing is moving: away from broad climate branding and towards specific infrastructure problems that can be priced, tested and scaled.

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Product teams usually discuss features as separate units of value. One feature improves activation. Another helps retention. A third supports monetisation. A fourth reduces friction in an important workflow. This way of thinking is useful for planning, but it quietly narrows how teams understand growth.

In live products, features do not sit politely beside each other. They interact. They change one another’s meaning. They alter the cost of usage, the confidence of the user, the timing of action, and the reason to come back. Sometimes two features that looked only moderately useful on their own end up creating far more value together than either team predicted when they were built.

This matters because some of the strongest engagement in a product does not come from a single brilliant capability. It comes from an accidental relationship between two capabilities that make each other more valuable, more usable, or more habitual. In other words, the product starts compounding value in places the roadmap never formally named.

Features do not just add value, they modify value

The first mistake in most roadmap thinking is the assumption that feature value is additive. A team launches Feature A and expects a certain lift. It launches Feature B and expects another lift. It then models the product as a stack of separate contributions.

That is not how many products actually work.

A feature can change the conditions under which another feature is used. It can make the user more willing to trust it, more likely to discover it, more prepared to use it properly, or more motivated to return because the second feature now feels more relevant. In that sense, features do not merely add value. They modify value.

This is why a product can look flat in isolated feature metrics and still become dramatically stronger in real usage. The relationship is doing the work, not the components in isolation.

This is also why some features disappoint in one release cycle and become strategically important later. They were not weak. They were waiting for the right counterpart.

The market often experiences the pair, not the parts

Inside the company, teams tend to know where one feature ends and another begins. There is a team owner, a delivery scope, a success metric, and a roadmap narrative attached to each. Customers do not experience the product that way.

Customers experience a sequence, a shortcut, a confidence pattern, a repeated behaviour that now feels easier or more worthwhile than before. They often cannot tell you which feature created the value. They simply know that something in the product has become more useful together.

This is important because product teams often miss relationships that are obvious from the outside and invisible from the inside. One capability helps users create something. Another helps them share it. A third helps them revisit it later. No single feature looks transformational alone, but together they create a loop of action, visibility, and return that changes the product’s role in the user’s day.

The engagement is not driven by one feature winning. It is driven by the product becoming more connected to itself.

Also Read: Seasonal product cycles: Why some features only work at certain times

There are several kinds of symbiosis, and they do not all look the same

Not every useful feature relationship works through the same mechanism. Some pairs reduce effort. One feature captures information, another reuses it later. The value is not excitement. It is the quiet removal of repeated work.

Some pairs transfer trust. One feature gives the user visibility or control, which makes them more willing to rely on another feature that previously felt too opaque or risky. In these cases, the second feature may already have been technically capable, but adoption stayed weak until another part of the product made it feel safe enough to matter.

Some relationships create recurrence. One feature produces output, another gives the user a reason to return to that output, revise it, share it, or act on it later. The first feature generates activity. The second turns activity into rhythm.

Others create identity inside the product. A user starts with a practical task, then another feature makes the result visible to colleagues, stakeholders, or customers. Now the original action carries reputational weight. It is no longer just a tool interaction. It becomes part of how the user is seen. Engagement often strengthens when product usage gains social meaning.

These are very different dynamics. Yet many teams lump them together under vague language like stickiness or synergy. That makes the pattern harder to act on.

Why accidental feature relationships are often more valuable than planned ones

Planned combinations can be powerful, but accidental relationships often carry a special kind of truth. They are less shaped by internal theory and more shaped by actual behaviour. They emerge because users found a way to make the product more useful than the original design story suggested.

That matters because real markets do not reward feature architecture. They reward utility in context.

When users create a relationship between two features on their own, they are effectively telling you something important. They are showing where the product’s real centre of gravity may be shifting. They are revealing that value is being created in the handoff between features, not only within them.

This is often where mature product leaders learn faster than everyone else. They stop asking only which features are performing and start asking which combinations are changing behaviour.

Also Read: The problem with ‘PM as CEO of the Product’: A myth that hurts more than helps

The real asset is not the feature pair, it is the behaviour pair

One reason companies misread feature symbiosis is that they focus too much on the interface and not enough on the underlying behaviour.

The important question is not simply which two features are being used together. It is the two behaviours are now reinforcing each other.

Is creation leading to sharing? Is visibility leading to action? Is the organisation leading to a revisit? Is control leading to trust? Is insight leading to habit? Is collaboration leading to accountability? These are the relationships that matter because they describe why the product is becoming more embedded.

If you only look at features, you may strengthen the surface and miss the mechanism. If you look at behaviours, you can often see how to deepen the relationship across the product more intelligently.

Product leaders should look for compound value, not just isolated wins

A stronger product discipline is to actively search for compound value inside the product. That means looking for places where one capability reliably increases the relevance, confidence, or recurrence of another.

It means asking where users who adopt Feature A become much more likely to retain Feature B. It means noticing where a previously quiet feature suddenly matters when paired with a stronger workflow. It means studying not just the most used features, but the most consequential combinations.

This kind of analysis tends to produce better strategic choices.

It can show which parts of the product deserve tighter integration. It can reveal that a supposedly secondary feature is actually a force multiplier. It can justify investment in connective work that would otherwise look unglamorous. It can even change packaging, onboarding, or sales positioning if the real value proposition is not one capability but a relationship between capabilities.

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The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.

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Generative artificial intelligence (GenAI) is set to affect the working lives of nearly 80 million people across ASEAN, but the technology has not yet produced the large-scale job losses often assumed in public debate, according to a new study by the International Labour Organization.

The report, Generative AI and labour markets in ASEAN: Significant exposure, limited disruption, uneven preparedness, estimates that 22.9 per cent of total employment in the region sits in occupations with more than minimal potential exposure to GenAI. Yet only 3.3 per cent of ASEAN’s workforce, or about 11.7 million workers, falls into the highest-exposure category.

Also Read: Beyond the hype: What generative AI is actually changing in startups

The distinction matters. Exposure does not automatically mean replacement. In many jobs, GenAI is more likely to alter tasks, compress workflows, or change skill requirements than eliminate roles outright. Around 67 per cent of ASEAN employment remains in occupations with no identified exposure to the technology, reflecting the region’s still-heavy dependence on agriculture, manufacturing, services, and informal work.

“The potential for labour market transformation is significant, but widespread disruption is not yet visible,” the report notes.

Singapore leads, but the exposure gap is regional

Among the nine ASEAN economies with available data, Singapore has the highest share of workers in occupations with more than minimal GenAI exposure, at 42.2 per cent of total employment. The Philippines follows at 28.1 per cent, reflecting its large services, business process outsourcing, and IT-enabled services base.

Indonesia stands at 21.7 per cent, Vietnam at 20.8 per cent, and Thailand at 20.6 per cent. The findings point to a familiar split in Southeast Asia: economies with larger formal services sectors and deeper digital adoption face earlier exposure, while those with bigger agricultural and informal workforces may see slower direct effects but also risk falling behind in productivity gains.

For Singapore, the finding is unsurprising. The city-state has spent years building AI governance frameworks, research capabilities, enterprise adoption schemes, and public-sector AI deployment. Its exposure is high because its workforce is more concentrated in professional, technical, administrative, and managerial roles — the very categories where GenAI tools can most easily automate or augment cognitive tasks.

The Philippines presents a different issue. Its BPO sector has long been one of the country’s main employment engines and a major export earner. GenAI’s ability to handle customer support, summarisation, transcription, and basic content generation puts pressure on lower-value work, even if higher-complexity services may remain resilient. This is not an immediate cliff edge, but it is a warning for a sector built on labour-cost arbitrage.

Startups face an adoption market, not just a disruption story

For Southeast Asia’s technology sector, the ILO report is less a story about robots taking jobs than about uneven enterprise adoption. GenAI use remains concentrated in technology-intensive occupations, while uptake is still comparatively limited in office and administrative roles despite their high exposure.

That gap creates a commercial opening for startups building AI workflow tools, vertical software, compliance systems, customer service automation, education technology, and human resources platforms. It also creates a harder question: whether small businesses can absorb these tools without widening the productivity divide between digitally mature firms and everyone else.

Southeast Asia’s internet economy remains large enough to support this shift. Google, Temasek, and Bain & Company estimated the region’s internet economy at US$263 billion in gross merchandise value in 2024, with revenue reaching US$89 billion. But the benefits of AI adoption are unlikely to spread evenly across a region where micro, small, and medium enterprises still account for the bulk of firms and employment.

Also Read: Is generative AI the game-changer for productivity?

The competitive landscape is already crowded. Global platforms such as OpenAI, Microsoft, Google, Anthropic, and Meta are embedding GenAI into workplace software used by regional companies. At the same time, Southeast Asian and Asia-focused players in customer engagement, voice AI, workflow automation, and sector-specific software are trying to localise products for language, regulation, and enterprise budgets. Companies such as WIZ.AI, Kata.ai, Yellow.ai, and regional system integrators are competing for the same automation budgets that banks, insurers, retailers, and contact centres are now reassessing.

Gender exposure is a policy problem

The ILO study also identifies a significant gender gap. Women in ASEAN are more than twice as likely as men to work in occupations with high GenAI exposure, largely because they are concentrated in clerical, administrative, and professional roles.

This finding complicates the common assumption that AI disruption will primarily hit male-dominated technical or industrial jobs. In the near term, it may instead affect office-based roles where women are heavily represented, including administrative support, routine documentation, customer operations, and clerical functions.

Young workers aged 15 to 24 and adult workers show broadly similar exposure levels, according to the report. That suggests the challenge is not limited to new labour-market entrants. Reskilling policies will need to cover mid-career workers as well, especially those in roles where GenAI changes the value of routine knowledge work.

Christian Viegelahn, ILO economist and lead author of the report, said the outcome will depend less on the technology itself than on institutional choices.

“Harnessing the benefits of GenAI requires more than access to technology,” he said. “Productivity gains depend on investments in human capital and social protection. Ultimately, future labour market outcomes will depend less on exposure alone than on the policy choices to build the preparedness and resilience of workers, enterprises and institutions.”

Preparedness may decide who benefits

The ILO report argues that ASEAN’s priority should be human-centred governance, broader access to skills training, support for MSMEs, and stronger knowledge exchange across member states. That agenda is not new, but GenAI makes it more urgent.

The risk for Southeast Asia is not simply job destruction. It is a two-speed labour market in which Singapore and digitally advanced firms use AI to raise productivity, while smaller companies and lower-income workers face task displacement without the tools, training, or social protection to adjust.

Also Read: Generative AI in daily life: A practical guide

For founders and investors, the next phase of the AI market in ASEAN will depend on whether products can move beyond pilots and productivity claims into measurable enterprise adoption. For policymakers, the test is whether AI strategies translate into worker-level preparedness rather than headline infrastructure announcements.

The ILO’s message is sober: GenAI is already relevant to tens of millions of ASEAN workers, but disruption is not predetermined. The region still has time to shape the outcome. Whether it does so will depend on execution, not rhetoric.

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The global cryptocurrency market experienced a profound structural shift over the past 24 hours, staging a major relief rally that directly challenged recent bearish momentum. Bitcoin led the charge, surging 4.10 per cent to reach a spot price of US$64,884.04 and outperforming the broader digital asset market, which posted a robust 3.71 per cent increase.

This sudden influx of buying pressure pushed the aggregate crypto market capitalisation up by 3.43 per cent, bringing the ecosystem’s total valuation to an impressive US$2.22T. Unlike isolated, native crypto events that occasionally spark volatility, this collective upward movement stemmed directly from external macroeconomic forces, signalling a tightening bond between digital assets and traditional financial markets.

The broader investment landscape witnessed a highly synchronised cross-asset response, with a remarkable 91 per cent correlation between cryptocurrency movements and the S&P 500 index and an 81 per cent correlation with Gold. These historically high statistical alignments indicate that digital assets are currently trading as a high-beta vehicle, deeply sensitive to global interest-rate expectations and broader dollar liquidity conditions.

The primary catalyst behind this aggressive market expansion was the highly anticipated release of the June United States Consumer Price Index data on July 14. In a surprise twist that caught many market participants off guard, the inflation print fell 0.4 per cent on a monthly basis due to lower energy costs, a metric that came in significantly cooler than the initial -0.1 per cent forecast.

This unexpected contraction cooled annual inflation down to a steady 3.5 per cent, delivering a massive wave of macro relief to participants who had previously feared aggressive interest rate hikes from the Federal Reserve. Because high interest rates typically drain liquidity from highly speculative, risk-on asset classes, this sudden disinflationary evidence sparked immediate expectations of future central bank rate cuts.

Traditional tech stocks and digital assets surged in tandem as capital rapidly rotated back into growth-oriented plays. For Bitcoin, this macro development reinforces its ongoing role as a sensitive atmospheric gauge of global monetary policy, meaning that any fundamental shift in the broader interest-rate outlook can trigger massive overnight capital reallocations.

Also Read: Why Bitcoin’s move to US$63K has nothing to do with crypto and everything to do with Iran

While the fundamental shift in macroeconomic sentiment laid the groundwork for the rally, the price action accelerated into a violent move due to a massive leveraged short squeeze in the derivatives markets. Traders who had positioned themselves aggressively for further downside were caught completely off guard by the positive inflation data, triggering a fierce feedback loop of forced buying.

Over the 24-hour window, the market saw a staggering US$104.12 million in Bitcoin positions wiped out by liquidations, with short sellers bearing the brunt, accounting for US$99.41 million of that total. This rapid cascading failure of short positions forced algorithmic buying engines to purchase spot and futures contracts at prevailing market rates to close out bankrupt accounts, adding immense artificial rocket fuel to the organic demand.

To complicate matters for bears, the average funding rate across major exchanges surged by an astronomical 158.42 per cent during this brief period, indicating an immediate and aggressive influx of bullish leverage as market participants scrambled to chase the breakout.

Simultaneously, the digital asset ecosystem enjoyed a healthy dose of sector leadership and speculative flow distribution that extended far beyond Bitcoin alone. Ethereum spearheaded this internal rotation by posting a notable 5.8 per cent weekly gain, significantly outperforming Bitcoin’s 2.02 per cent weekly return. This capital divergence was heavily amplified by social media chatter that framed Ethereum as a form of sound money uniquely positioned to thrive in a lower-rate economic environment, quickly establishing the Layer 1 narrative as the top-trending sector in the industry.

This speculative appetite was further validated by a massive 107 per cent surge in overall derivatives volume, alongside a steady rise in open interest, indicating that fresh institutional and retail capital was actively flowing into leveraged altcoin positions. This distinct shift in internal market dynamics indicates that the 24-hour rally was not merely a passive, index-wide response to stock market trends but rather a calculated rotation into major alternative assets, which could signal a sustained period of altcoin momentum if the Ethereum-to-Bitcoin ratio continues to strengthen.

From a strict technical and structural standpoint, the near-term market outlook remains distinctively bullish but faces immediate hurdles that will test the true conviction of spot buyers. Bitcoin successfully broke above its critical 7-day Simple Moving Average of US$63,476 and is currently working to solidify the 38.2 per cent Fibonacci retracement level near US$63,619 as a new baseline of technical support.

If the asset can decisively hold its ground above this pivotal US$63,619 line, the immediate path of least resistance points directly toward the 23.6 per cent Fibonacci retracement level located at US$65,006. Analysts must remain cautious, as 24-hour spot trading volume decreased by 21.33 per cent during this breakout, indicating a slight divergence between price appreciation and absolute spot market participation.

A failure to attract consistent spot buying volume at these elevated levels could lead to a rapid unwind of recent leveraged gains, potentially triggering a swift technical pullback toward the 50 per cent Fibonacci support level anchored at US$62,498.

Also Read: Why US$1.4 billion in Bitcoin longs could drag Bitcoin down to US$53,500?

Looking at the digital asset market as a collective whole, the aggregate valuation is currently testing a monumental technical resistance ceiling at US$2.25T, a level that represents the recent swing high for the total crypto market cap.

The immediate future of this macro-driven momentum now hinges entirely on the upcoming Producer Price Index data scheduled for release on July 15. If the incoming wholesale inflation figures confirm the disinflationary trajectory established by the Consumer Price Index print, the market will likely gain the fundamental backing needed to clear the US$2.25T barrier.

A successful technical breakout above this overhead supply zone would officially open the doors for a broader market expansion targeting the US$2.31T to US$2.38T extension zone. If the wholesale inflation data springs an unpleasant surprise on investors, the market may face a stern technical rejection at the current ceiling, resulting in a healthy period of consolidation or a temporary retreat down to the well-established US$2.14T to US$2.20T support band.

This rapid market recovery proves that while internal crypto mechanics like short liquidations and sector rotations dictate the immediate velocity of price moves, global macroeconomic liquidity remains the ultimate puppet master of valuation. The immediate trading bias for the market leans toward continued bullish momentum, but this optimistic outlook demands absolute validation beyond a single day of frantic short covering.

To transform this sharp relief rally into a legitimate, long-term market recovery, Bitcoin must comfortably sustain its position above the US$63,619 technical floor while simultaneously attracting consistent, positive institutional exchange-traded fund inflows in the coming days.

Investors must closely monitor both the immediate technical pivot points and the incoming wholesale inflation data, as the tension between overhead technical resistance and shifting global interest rate expectations will determine whether this impressive rally marks the beginning of a prolonged expansion or simply a temporary pause in a broader macroeconomic correction.

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

The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of e27.

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For the longest time, I thought burnout was simply part of entrepreneurship. You work harder. You sleep less. You push through. If you’re building something meaningful, surely exhaustion is just part of the price of admission.

Like many founders, I wore long hours almost like a badge of honour. I wanted to build big companies, create impact and prove that I could make something significant. The bigger the business became, the more responsibility I carried. At the time, that felt like success.

It took me years to realise that I wasn’t burning out because I loved building. I was burning out because I had become the operating system.

Every decision flowed through me. Every approval required my attention. Every miscommunication became my responsibility. Even when I delegated work, I still carried the mental load of remembering, checking, clarifying and correcting. The work itself wasn’t always exhausting. Carrying everything was.

Burnout often begins emotionally, but it becomes operational

When we talk about burnout, the conversation usually revolves around mental health, resilience or work-life balance. Those conversations matter, but they’re only part of the picture. As founders, we often overlook another source of exhaustion: operational complexity.

The more a company grows, the more decisions need to be made. More meetings. More approvals. More context switching. More people are interpreting instructions differently. More time is spent ensuring that what was intended is actually what gets executed. Eventually, your brain becomes the glue holding everything together. That kind of cognitive load is incredibly expensive, not because the tasks are individually difficult, but because they never stop.

Also Read: Employee burnout is real and why it needs to be taken seriously

One of the biggest stresses wasn’t the work, it was losing control of the message

One of the hardest lessons I learned wasn’t about revenue or fundraising. It was communication. I would explain something clearly, only to discover later that what was delivered wasn’t what I had intended. Somewhere between my thoughts and execution, the message changed. Yet the responsibility still landed on my desk.

The bigger the organisation became, the more this happened. That isn’t a people problem. It’s an operations problem. Every additional layer introduces friction, more interpretation, more room for information to change as it moves from one person to another.

Founders often assume they’re overwhelmed because they have too much work. Sometimes they’re overwhelmed because they’re carrying too much operational complexity.

AI didn’t remove my workload, it changed what I needed to carry

People often ask whether AI has reduced my workload. The answer is yes, but probably not in the way they imagine. AI didn’t magically eliminate my responsibilities. It reduced the number of things my brain needed to constantly remember.

Instead of repeatedly explaining the same ideas, I could build systems that preserved context. Instead of relying entirely on memory, I could rely on documented knowledge. Instead of spending hours reviewing repetitive work, I could focus on decisions that genuinely required human judgment.

The difference wasn’t simply productivity. It was mental bandwidth. That’s an important distinction.

Also Read: How to combat burnout and boost your productivity

My definition of scale has changed

When I was younger, I thought building a successful company meant having more people, larger teams and bigger organisational charts. Today, I don’t see the scale that way anymore.

I still want to build ambitious companies. I still want to create meaningful technology. I still enjoy moving quickly. But I’ve realised that success isn’t measured by how many people report to you. It’s measured by how much value you can create without unnecessary complexity.

The best founders aren’t necessarily the ones who can carry the most. They’re the ones who design systems that don’t require them to carry everything.

Every mistake shaped how I build today

Looking back, I don’t regret the mistakes. I don’t regret the burnout. I don’t regret wanting to build something bigger than myself. Those experiences shaped the founder I am today. They also shaped the way I teach entrepreneurs, not because I’ve figured everything out, but because I know how expensive certain lessons can be.

Every shortcut I share, every framework I teach and every AI workflow I build is really an attempt to help someone else avoid mistakes that took me years to understand. Failure is part of entrepreneurship. Burnout doesn’t have to be.

The next generation of founders won’t just build better products. They’ll build better operating systems.

The conversation around AI often focuses on replacing work. I think that’s the wrong question. The more interesting question is this: what if AI allows founders to stop becoming the operating system of their own companies?

Because perhaps the future of entrepreneurship isn’t about working less. It’s about ensuring that the work only humans can do is where our energy is spent. Burnout will always have a human side. But increasingly, it also has an operational one. And perhaps that’s where the next generation of founders should begin redesigning their businesses.

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

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