Posted on Leave a comment

Bitcoin at US$63,386: The geopolitical storm Wall Street missed

Bitcoin currently trades at US$63,386.87 after experiencing a 1.24 per cent decline over the past 24 hours. This downward movement mirrors a broader one per cent contraction in total cryptocurrency market capitalisation. These short-term price fluctuations are predictable reactions to external macroeconomic shocks rather than systemic failures.

The current sell-off lacks any crypto-specific negative catalyst. Traditional institutional selling pressure and escalating global tensions dictate the immediate price action. We must separate the fundamental progress of distributed technology from the temporary noise of global political theatre.

The primary catalyst driving this risk-off sentiment is the collapse of ceasefire negotiations between the United States and Iran over the weekend. New military warnings from United States President Donald Trump and Tehran’s subsequent decision to close the Strait of Hormuz again severely shook recent optimism about technology. This geopolitical friction immediately triggered a reversal across global equity and commodity markets. United States equity futures fell sharply following the Juneteenth holiday.

S&P 500 futures dropped 0.5 per cent while Nasdaq 100 contracts declined 0.7 per cent. Asian markets reflected this same anxiety. The Japanese Nikkei 225 opened slightly lower at 71,067.15, then fluctuated up to 72,133.88 as overnight futures provided local support. South Korea’s KOSPI dropped more than 1.1 per cent in morning trading, with chip giant Samsung Electronics leading losses, sliding over three per cent. Australia ASX 200 also slumped early as investors digested weekend energy transport disruptions. Heavyweight BHP faced a steep sell-off following massive cost overruns. Bitcoin simply reacts to this same global liquidity contraction.

Also Read: 81% correlated with gold: Is Bitcoin just another macro derivative now?

Commodity and currency markets highlight the exact nature of this macroeconomic stress. Crude oil surged amid severe supply chain anxiety. Brent crude rose over one per cent to top 81.50, and West Texas Intermediate jumped nearly three per cent to trade near 78. This energy shock strengthens the US against most major currency peers as investors seek safe-haven assets. The British Pound weakened 0.2 per cent on widespread speculation that United Kingdom Prime Minister Keir Starmer might resign following political defeats. Investors clearly demand stability.

Beyond immediate geopolitical triggers, markets also brace for the crucial United States Core PCE inflation release on Thursday. The Federal Reserve under new Chair Kevin Warsh recently executed a hawkish pivot. Policy paths now hint at potential 2026 interest rate hikes. This traditional financial tightening directly pressures risk assets, including cryptocurrencies. The Nasdaq-100 quarterly rebalance takes effect today. The index added major tech players such as CoreWeave and Rocket Lab while removing legacy firms such as Charter Communications. These structural shifts in traditional equity markets force institutional portfolio managers to rebalance their broader risk exposure, inadvertently dragging digital assets into the sell-off.

We must also address the persistent institutional selling pressure weighing heavily on Bitcoin. United States spot Bitcoin funds recorded a record US$6.35 billion in net outflows over the past 30 days. The daily pace of these outflows recently slowed, but this persistent drain removes a massive source of traditional demand from the market. I maintain that integrating digital assets into traditional financial wrappers introduces legacy market behaviours into our ecosystem.

Traditional financial tests, such as the Howey test, remain entirely unsuitable for evaluating these distributed crypto systems. Regulators fail to understand that digital assets operate on fundamentally different architectural principles. When traditional institutions face geopolitical shocks or margin calls in equity markets, they initially liquidate their most liquid alternative assets. Bitcoin currently absorbs this traditional market fragility. The asset reacts to macro risks and a withdrawal of institutional capital rather than any fundamental deterioration in network activity. This dynamic shows that digital assets remain tethered to the whims of global equity markets until we achieve true decentralisation.

Also Read: Why tech giants are crashing while Bitcoin surges to US$67,000

Technical indicators and derivatives data reveal a market structure that remains weak but entirely orderly. Bitcoin currently trades below its seven-day simple moving average of US$63,823 and its 30-day simple moving average of US$64,037. This positioning confirms short-term bearish momentum across all major timeframes. The Relative Strength Index reading of 30.06 shows the asset sits in oversold territory without reaching extreme capitulation levels. The derivatives market provides further clarity on ecosystem health.

Total open interest fell by 4.56 per cent in the last 24 hours, while Bitcoin liquidations dropped by an impressive 46.54 per cent. These numbers signal lower speculative leverage and eliminate the risk of an immediate squeeze. The market unwinds excess leverage in a controlled manner rather than experiencing a chaotic cascade of mandatory selling. This orderly deleveraging creates a healthier foundation for potential recovery. Speculators cleared out weak positions, leaving only dedicated capital in the market to support future price discovery.

Traders examining the near-term market outlook must focus entirely on specific price levels to gauge the next directional move. The critical support zone is at US$63,200, representing the recent 24-hour low. If buyers successfully defend this zone, a rebound toward the swing high resistance at US$64,506 becomes highly probable. The path of least resistance remains downward unless Bitcoin fund flows turn positive.

A definitive break below the US$63,200 support could trigger a quick test of the psychological US$62,000 level. The bias remains neutral to bearish until Bitcoin reclaims and holds above the US$64,500 resistance area. We must also monitor any escalation in the situation in the Strait of Hormuz or sudden reversals in daily Bitcoin fund flows. 

This short-term bearish pressure ultimately tests network resilience and separates fleeting speculative capital from genuine believers in distributed financial infrastructure. We currently stand on the precipice of a truly human-focused, highly practical application layer that transcends legacy market volatility.

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.

Join us on WhatsAppInstagramFacebookX, and LinkedIn to stay connected.

The post Bitcoin at US$63,386: The geopolitical storm Wall Street missed appeared first on e27.

Posted on Leave a comment

After a bank cyberattack, the real risk is restoring the wrong version of the truth

Banks often treat cyber recovery and regulatory reporting as separate workstreams. One team restores services. Another drafts the incident report. That split may look tidy, but in practice, it creates risk.

Both activities deal with the same problem. Facts are incomplete, pressure is immediate, and decisions must be made before anyone fully understands what has been damaged, altered, or trusted too quickly. A bank can bring systems back online and still restore a corrupted operating state. It can notify regulators quickly and still create a record it later struggles to defend. The real challenge is not speed alone. It is disciplined speed under uncertainty.

Regulators are increasingly recognising this reality. They are moving towards earlier notification with structured follow-up instead of waiting for perfect hindsight. In the United States, federal banking agencies require notification to the primary regulator as soon as possible and no later than 36 hours after the bank determines that a qualifying incident has occurred. Under DORA, firms must submit an initial notification, then intermediate reports as the incident changes materially, and then a final report. In the United Kingdom, the FCA’s finalised guidance issued in March 2026 also accepts an indicative root cause during the initial and intermediate phases, with confirmation expected later.

The most dangerous recovery is the fast but false recovery

A cyber event is not over when an application starts responding again. In a bank, the harder question is whether the institution has restored a trustworthy state.

A payment platform may be available while still operating on corrupted queues. A servicing system may be live while drawing on altered customer records. An authentication layer may be back while still containing poisoned privilege assignments. A reconciled ledger may look stable even though upstream dependencies remain inconsistent. NIST and CISA guidance both point to the same principle. Recovery is not just about bringing systems back. It is about restoring operations and data that the organisation can trust.

Banks therefore, need to be more precise in their language. The goal is not service restoration alone. It is state restoration. That means restoring data state, entitlement state, rules state, model state, queue state, and reconciliation state to a version the institution is prepared to stand behind. Banking systems do not only process transactions. They preserve institutional truth. Once that truth is in doubt, speed without integrity creates a new layer of risk.

Also Read: The truth behind the CLARITY Act lobby blitz: Crypto to the moon or banks compromise

Recover to a certified state, not merely the last available state

Many recovery plans still assume that a clean rollback point exists and that operational pressure will allow the bank to trust it quickly. In reality, corrupted states are often harder to isolate than outages. Damage may have spread across data stores, replication layers, configuration histories, privileged access paths, and operational decisions taken after the initial compromise.

NIST’s data integrity guidance is valuable because it goes beyond generic backup language. It stresses the need to consider integrity at the application and business process levels, to test backups through end-to-end restores, and to maintain a recovery catalogue showing which copies have been scanned and whether older copies may themselves be poisoned.

Banks should push that logic further. Critical services should not reopen simply because infrastructure has been rebuilt. They should reopen because a recovery authority has certified that the restored state is coherent enough for the bank’s control environment, customer duties, and regulatory obligations. The real question is not “can we restore?” but “which version of reality are we restoring, and what evidence makes us trust it?”

Reporting early does not mean pretending to know more than you do

Banks often feel trapped between two bad options. Either they delay notification while chasing confidence they will not have in the first few hours, or they report early with more certainty than the evidence supports.

Both are weak responses. Delay is not discipline. Overstatement is not defensibility.

Current regulation is actually more practical than many firms assume. DORA is built around staged reporting through initial, intermediate, and final submissions. The FCA’s latest guidance similarly distinguishes between early and later phases. The message is clear. Regulators increasingly expect early situational awareness followed by maturing updates, not a perfect narrative delivered too late.

The banks that handle this well do not report certainty. They report bounded truth. They distinguish what is confirmed, what is strongly suspected, what remains unknown, what actions have been taken, and what assumptions may still change. That is usually the most defensible position available in the opening phase of an incident.

Also Read: From policy to capital: How development banks are driving the climate x health agenda

The first report should state facts, impact, and decision

Many first reports fail because they try to be too complete too early. Forensic theory, customer impact, technical noise, and management reassurance all get blended into one unstable document.

A stronger first report is narrower. It should state what the bank knows about service disruption, data integrity, confidentiality exposure, and affected business services. It should explain what threshold triggered the notification and what actions have already been taken to contain the incident. It should separate confirmed impact from potential impact. It should record the current operating posture, whether services are suspended, partially restored, or running under restricted controls. It should also state the main uncertainties in plain language.

That is much closer to how current frameworks are written. Regulators want timely and structured information that shows material impact, current control posture, and the institution’s response, not an artificial sense of closure.

Recovery and reporting need one evidential spine

The biggest operational mistake is to let recovery teams and reporting teams build separate versions of the incident.

When that happens, technical teams speak in hypotheses, restoration checkpoints, and system states, while reporting teams speak in regulatory thresholds, customer impact, and executive language. Each account may make sense on its own, but together they create a contradiction. The bank then ends up with one account of what was restored, another of what was reported, and a third of what customers later experienced.

Banks need one evidential spine feeding both recovery and reporting. It should capture timestamped facts, material decisions, restoration checkpoints, confidence levels, changed hypotheses, customer impact estimates, and evidence sources. That is what allows the bank to explain later why it made the calls it made while the facts were still moving.

Also Read: Trump vs banks: How stalled crypto legislation is crushing market sentiment

Final thought

Cyber recovery in banking is becoming less about bringing systems back and more about deciding which institutional truth can safely be trusted again.

That is why material incident reporting and safe recovery should not be treated as separate disciplines. Both are exercises in disciplined honesty under uncertainty. The bank has to say what it knows before the picture is complete, and it has to restore only what it is willing to defend later.

The institutions that will do this well are not the ones that sound most confident in the first 24 hours. They are the ones that recover without replaying corruption, report without pretending to know the unknowable, and show afterwards that their early judgment was careful enough to deserve trust.

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.

Join us on WhatsAppInstagramFacebookX, and LinkedIn to stay connected.

The post After a bank cyberattack, the real risk is restoring the wrong version of the truth appeared first on e27.

Posted on Leave a comment

15 Thai AI companies betting on products, not hype

Southeast Asia’s AI scene is sprinting ahead, and Thailand is quietly becoming its laboratory. From generative spatial design and energy‑saving AIoT to sovereign Thai language models and an “AI nose” that tastes food, a new wave of startups is turning local problems into global products.

This list rounds up 15 homegrown companies that typify the region’s pragmatic, product‑first approach: enterprises solving real operational pain points for banks, CDMOs, contact centres and architects, not just flashy demos. Some are scaling fast with fresh funding; others are proving deeptech chops on international stages.

Also Read: AI is a game-changer, and here’s how your business can use it to win

Read on for a curated snapshot of who’s shipping, what they actually do, and why investors and enterprise customers are paying attention. If you’re tracking AI adoption in the region, these founders are the ones rewriting the playbook, one deployable model at a time.

WiseSight

Profile  Founder(s) Founding year
AI social‑media analytics platform, using proprietary NLP to deliver real‑time brand intelligence across Thai and regional channels. It recently secured US$7M in Series B to fuel ASEAN expansion. Kla Tangsuwan, Pnern Asavavipas, Warodom Dansuwandumrong, Ted Thirapatana, and Pawoot (Pom) Pongvitayapanu 2017

Ricult

Profile  Founder(s) Founding year
AI + satellite imagery for smallholder farmers: crop advisory, yield forecasts and market access serving 300k+ farmers. It recently raised US$2M pre‑Series A to scale precision‑agri tools. Usman Javaid, Gabriel Torres, and Aukrit Unahalekhaka 2015

Zwiz.AI 

Profile  Founder(s) Founding year
A conversational AI and chatbot platform powering messaging channels for 1,000+ businesses and 2M+ customers. Chanakarn (Art) Chinchatchawal 2017

Sertis

Profile  Founder(s) Founding year
Enterprise AI and data‑science firm specialising in computer vision, predictive maintenance and automated inspection for retail, manufacturing and energy. Thuchakorn (Tee) Vachiramon 2014

DataWow

Profile  Founder(s) Founding year
Computer‑vision and content‑moderation AI for image, video and text analysis at scale, used for identity verification and automated filtering. Jesdakorn Samittiauttakorn 2016

Spacely AI

Profile  Founder(s) Founding year
Generative AI for architecture: converts 2D plans or text prompts into photorealistic 3D renderings in seconds. A few weeks ago, it secured US$1M seed to launch its 2D→3D engine. Paruey Anadirekkul, Thanatcha Pojthaveekiat, and Thanapong Somjai 2023

MUI‑Robotics

Profile  Founder(s) Founding year
Deeptech firm building AI sensory tech (‘AI nose’ and ‘AI tongue’) that digitises smells and tastes for F&B and agriculture. It recently demoed at Startup Grind 2025 in Silicon Valley. Dr. Teerakiat Kerdcharoen, Wandee Wattanakrit, and Aim Phattananat Wongwan 2021

OsseoLabs 

Profile  Founder(s) Founding year
Medtech AI combining imaging, surgical planning and 3D‑printed patient‑specific implants to automate preoperative workflows. Dr. Vikram Ahuja and Dr. Patcharapit “Joe” Promoppatum 2021

iApp Technology

Profile  Founder(s) Founding year
Sovereign Thai AI provider: OCR, speech, TTS and Thai LLM (Chinda) for enterprise deployments. Dr. Kobkrit Viriyayudhakorn 2013

BOTNOI Group

Profile  Founder(s) Founding year
AI company delivering NLP chatbots, voicebots, digital humans and vision systems for major corporations and government. Dr. Winn Voravuthikunchai 2017

Gowajee

Profile  Founder(s) Founding year
Voice AI platform for contact centres, optimised for Thai and regional languages to automate downstream voice interactions. Pisuth Ren Huang 2023

AltoTech Global

Profile  Founder(s) Founding year
AIoT energy platform (Alto CERO) using reinforcement learning to optimise HVAC and cut energy use in hospitality and manufacturing. Warodom Khamphanchai 2022

GuardianGPT

Profile  Founder(s) Founding year
Generative‑AI and LLM specialist building RAG systems, AI agents and enterprise chatbots for Thai businesses. Sathapon Patanakuha 2023

Wisible

Profile  Founder(s) Founding year
ML‑powered sales‑intelligence platform that detects high‑risk customers and prescribes personalised retention strategies. Recent: US$900k Seed raise and enterprise client traction. Saroj Ativitavas 2020

AIRA

Profile  Founder(s) Founding year
Agentic AI recruitment assistant automating sourcing, screening and scheduling with continuous feedback learning. Recent: Launched automated job creation, LinkedIn sourcing and smart candidate search features. Justas Rinkevicius 2023

 

The post 15 Thai AI companies betting on products, not hype appeared first on e27.

Posted on Leave a comment

What nine AI workflow submissions reveal about Echelon Singapore’s builder pipeline

The useful test of an AI competition is whether it can repeatedly turn broad interest into specific, inspectable builder output.

That is the most important signal from the AI Workflow Competition at Echelon Singapore 2026. Nine other entries reviewed by e27 showed builders working through the harder middle ground of AI adoption: messy inputs, scattered knowledge, human approvals, cost constraints, data gaps, and workflows that must fit existing operations.

Also Read Inside the AI Workflow Competition at Echelon Singapore 2026

For sponsors, government partners, and future programme backers, that matters. The competition created a controlled channel where problem statements, sponsor resources, builder judgement, and submission criteria could be tested. Not every prototype was production-ready. The point is that the format generated multiple credible outputs that could be examined, improved, and rerun.

A testbed, not a showcase

The competition asked builders to work from operational challenges, including revenue growth and efficiency tracks, while showing business impact, cost thinking, safeguards, and proof of execution. Builders also had access to workshops, community support, and sponsor-backed resources from FPT AI Factory, Alibaba Qwen, Bitdeer AI, PixVerse, Notion, and AMD-backed cloud support.

The evidence was not uniformity. It was range. Customer support appeared often, but the better entries treated it as more than faster replies. They connected inboxes to knowledge bases, marketing signals, dashboards, reporting systems, escalation rules, and human review. Others moved into spreadsheet reconciliation, reseller reporting, and workflow education.

  1. Morning Wu of AfterWork Startup. Managed to build 1 workflow for each challenge statement. One workflow used AI to answer tickets, tag sentiment, and push weekly insight briefs to email, Slack, or Telegram. Another tackled reseller reporting for The Social Space by pulling fragmented data into reports. The claimed reduction, from 1.5 weeks to three minutes, still needs validation, but it identified a bottleneck.
  2. Alpa Parmar of Bots and Brand works and Hari Prasad of Boolean BeyondAdoption as a comprehension problem. Their six-node workflow classified tickets, searched a knowledge base, routed issues, drafted replies, flagged gaps, and generated knowledge-base entries. The submission’s key point was that AI workflows tested on sample data still need to connect with the systems where an organisation’s real work happens.
  3. Patrick Tan of Art Infinity Asia and Abel Choy of Atlantic Media reframed the inbox as a routing layer. It extracted fields from customer messages, searched company documents, interpreted intent through an AI model, and routed each item to a reply draft, Slack alert, CRM update, or knowledge-gap log. Their description of the inbox as “a goldmine of information” captured why these competitions can produce market intelligence: builders reveal where operational data is trapped.

Credible outputs under constraint

  1. Team Alpha Beta, led by Ayush K Pacheriawala and Tejas Chavan Maintainability at the centre. Its customer-support triage system separated high-confidence repetitive queries from uncertain issues requiring human judgement. The team used n8n, Google Sheets, FPT AI Factory access, and Alibaba Qwen or other LLM access. Their warning was direct: “The biggest barrier is not cost or technology — it is the gap between what AI can do and what an SME’s internal team knows how to build and maintain.”
  2. Morpheus Labs Fuseful team of Dorel D. Burcea, Thang Nguyen, and Lyn Ngan took an adoption-first stance. Its workflow lets staff keep using email and Google Drive while an AI layer handles triage, draft replies, knowledge-based updates, sentiment analysis, and insight generation. The submission avoided promising a new operating model.
  3. Wang Heng Xin Melson of Corezz Technology exposed another limitation: many companies already have basic bots, but those bots are not linked to useful shared knowledge. Using Alibaba Qwen partly because of cost and access considerations, the entry pointed towards database-connected, cross-team workflows rather than shallow customer-service automation.

Also Read From support inbox to signal feed: Inside the AI workflow that won at Echelon Singapore 2026

  1. Cayden Chai This submission was among the clearest examples of visible output density. Running on 70 customer tickets, its seven-step pipeline produced 35 drafted replies, 35 flagged gaps, 37 marketing signals, six theme clusters, six knowledge-base entries, and a monthly marketing intelligence brief. His framing was concise: “Most SME AI tools answer questions and stop — ours turns support volume into a continuous feedback loop for the business.”
  2. Connor Clark Lindh Targeted spreadsheet reconciliation, anomaly detection, and report generation. His submission referenced Alibaba Qwen, FPT AI Factory, Gemini, Google Apps Script, custom APIs, and four prototype automations. The next step he identified was time with end-users to shadow workflows and test solution flows. That is where repeatable adoption becomes real: where data is cleaned, reformatted, checked, and reported.
  3. Steve Ng of Digital Futures Consultancy Pushed furthest towards reusable implementation infrastructure. It treated a customer inbox as a self-improving customer-intelligence engine, supported by LLAMA, self-hosted n8n, ChromaDB, FastAPI, Streamlit, Docker Compose, and Swagger UI. The submission claimed 13 out of 13 end-to-end test results and 31 API endpoints. Its sharpest line made the category clear: “The inbox isn’t just people asking for help; it’s people telling you exactly what matters to them.”

These submissions show that not every workflow is ready to be dropped into a company tomorrow.

The AI Workflow Competition inside Echelon 2026 surfaced where AI adoption actually gets stuck: incomplete knowledge bases, disconnected inboxes, fragile reporting processes, uncertain handoffs, and teams that need systems they can maintain after the demo ends.

For sponsors and ecosystem backers, the signal is clear: when builders are given concrete problems, usable tools, and an avenue to show working outputs, an AI competition can become a repeatable mechanism for finding practical adoption pathways across Southeast Asia’s operating businesses.

=== 

Want updates like this delivered directly? Join our WhatsApp channel and stay in the loop.

The e27 team produced this article

We can share your story at e27 too! Engage the Southeast Asian tech ecosystem by bringing your story to the world.You can reach out to us here to get started.

The post What nine AI workflow submissions reveal about Echelon Singapore’s builder pipeline appeared first on e27.

Posted on Leave a comment

From support inbox to signal feed: Inside the AI workflow that won at Echelon Singapore 2026

Aaryan Kandiah and fellow AI Workflow Competition finalists, together with the judges and ecosystem partners, at Echelon Singapore 2026.

A customer support inbox usually looks like a backlog: questions to answer, complaints to resolve, and product details to clarify before the next message arrives.

For Aaryan Kandiah, it looked like something else: a live stream of business signals.

 That shift helped him win the AI Workflow Competition at Echelon Singapore 2026 with SignalDesk. A recent Nanyang Technological University graduate with a Bachelor of Engineering in Electrical and Electronics Engineering, Aaryan is also set to begin a Master of Computing in AI at the National University of Singapore. His winning workflow, built around Boldr’s customer support challenge, reflected that blend of engineering discipline and applied AI thinking.

 The point is not simply speed. If the AI cannot answer with evidence, it should flag the gap so the company can improve its knowledge base, FAQs, product pages, or internal documentation.

 If a question could not be answered, the system should not guess. It should flag a knowledge gap. Those patterns should become useful business signals.

Built from real SME friction

The competition was built around a practical premise: builders should work on real SME bottlenecks, not imagined use cases built for a stage demo. Over a 48-hour worksprint, participants were asked to build functional AI workflows for business problems faced by participating SMEs.

For Boldr, a Singapore-based watch micro-brand, the problem sat inside customer support. Like many small teams, Boldr deals with repeated enquiries across product information, policies, specifications, and purchase-related concerns. Together, these messages reveal what customers do not understand and where support teams lose time repeating answers.

 SignalDesk treats that inbox not as a queue to be cleared, but as a signal feed that can help the business learn. The workflow ingests a customer enquiry, identifies the likely intent, checks approved sources, and determines whether there is enough evidence to support a reply. If there is, it drafts a response for human approval. If there is not, it records the issue as a knowledge gap.

Also Read Inside the AI Workflow Competition at Echelon Singapore 2026

 That matters because customer support is not simply a language-generation problem. For an SME, one unsupported AI-generated reply can create confusion, damage trust, or create more work later.

Why it was not just another chatbot

Aaryan said the competition’s brief made it clear that builders were expected to go beyond a prompt-based chatbot.

That instruction made it clear that the expected outcome was a production-ready tool that is more complex than a detailed system prompt.

 SignalDesk’s most practical design choice is restraint. The workflow does not assume that every question deserves an automated answer. It first checks whether the business has enough verified information. If not, it stops short of responding and pushes the missing information back to the team.

That makes the human-in-the-loop layer central rather than decorative. A support agent still approves customer-facing replies, resolves missing information, and reviews suggested updates before publication.

In other words, SignalDesk does not remove human judgement from the process. It moves people away from repetitive first-draft work and towards decisions that require accountability.

The e27 layer behind the build

The workflow did not emerge in a vacuum. Before the worksprint began, the e27 team had turned SME pain points into structured challenge tracks, issued a Builders Kit, set submission requirements, and created official communication channels for announcements, questions, and peer support.

Builders were given two broad tracks. Revenue Rocket focused on sales, marketing, and customer acquisition, while Save-a-Hire focused on operational efficiency and task automation. Boldr’s challenge sat naturally within Revenue Rocket because repeated support questions can expose revenue leaks: unclear product information, weak customer education, or unanswered concerns that stop buyers from moving forward.

The competition also gave builders a clear operating frame: sponsor workshops with FPT AI Factory, Qwen, and Bitdeer AI, a virtual kick-off ceremony, and the timed release of official problem statements and sample materials on Day 1. Submissions had to show a working demo, business impact, cost analysis, safeguards, and proof of execution.

That structure shaped the kind of solution that could win. SignalDesk was not rewarded merely for generating a neat answer. Its evidence checks, human approval queue, and knowledge-gap logging matched a judging lens that looked attechnical execution, SME value, cost realism, responsible AI, and clarity.

What the winner left with

The win gave Aaryan more than stage recognition. He left with more than US$16,000 worth of prizes, credits, and post-competition support intended to help continue the winning workflow beyond the event.

The package included an e27 editorial feature to tell the SignalDesk story across Southeast Asia and exclusive SME matchmaking with businesses looking for practical AI workflows. It also included a 3-month Notion Business Plan, valued at US$6,000 in workspace credits, to support documentation, workflow planning, and collaboration.

On the technical side, the package included US$1,000 in Bitdeer AI compute credits, US$500 in Alibaba Qwen cloud and AI credits, PixVerse credits worth 400 minutes of generated video for demos and product storytelling, and US$6,000 in AMD-based cloud credits to test and scale AI workflows.

For SignalDesk, those resources matter because the project does not have to end as a competition prototype. Editorial visibility can explain the workflow to a wider market, SME matchmaking can open commercial conversations, and the credits can support further testing, refinement, demonstrations, and deployment exploration.

From inbox to operating system

The broader lesson is not that every SME needs an AI support bot. It is that many SMEs already sit on operational data they are not using well.

SignalDesk shows one way to make that shift. It starts with a familiar pain point, adds evidence checks and human review, and turns unanswered questions into a system for organisational learning.

That is why the winning workflow fits the spirit of the competition. It does not treat AI as spectacle. It treats AI as infrastructure for a business problem that already exists. For Southeast Asian SMEs, useful AI stories may begin not with a model, but with unresolved work waiting to be understood.

=====

Want updates like this delivered directly? Join our WhatsApp channel and stay in the loop.

The e27 team produced this article

We can share your story at e27 too! Engage the Southeast Asian tech ecosystem by bringing your story to the world.You can reach out to us here to get started.

 

The post From support inbox to signal feed: Inside the AI workflow that won at Echelon Singapore 2026 appeared first on e27.

Posted on Leave a comment

Why the 30-year wealth playbook is breaking down

For decades, the path to wealth was presented as a long, disciplined sequence: work steadily, save consistently, invest patiently and let time do the rest.

While this advice is not wrong, it was built around a world where stable employment, affordable asset accumulation and predictable economic cycles made patience feel rational. For many younger people today, those conditions feel a lot less dependable.

Rising costs, economic uncertainty and geopolitical instability have changed how people think about wealth, risk and opportunity. Instead of just waiting for rewards later, many are looking for ways to take action earlier and take charge in shaping their financial future.

This behaviour is commonly seen as being impatient. But that misses the point. For these young investors, waiting patiently while the world feels unstable no longer seems like a viable strategy. So in reality, it’s their natural response to a very different financial environment.

The old model is being challenged

The traditional wealth model was built on three assumptions: time would compound gains, steady income would provide security, and stability would make long-term planning realistic.

The cost of living has risen, traditional routes to wealth accumulation feel slower, and uncertainty has become a more constant feature of financial life.

Understandably, the promise of delayed reward is harder to trust when the path itself feels less secure.

But this does not mean long-term thinking has lost its value. Patience and discipline still matter, but they feel harder to trust when people do not see meaningful opportunities along the way.

That is why younger generations are not only asking how to build wealth over 30 years. They also want to know how to participate earlier, understand risk better, and avoid being left behind as financial systems evolve.

Also Read: Why investors are auditing your operation architecture, not your org chart

When curiosity moves faster than education

This desire to participate earlier has drawn many new investors into emerging financial markets, including digital assets. But access is not the same as readiness.

Having spent years educating new investors in this space, a recurring pattern becomes clear: many beginners are genuinely interested in digital assets, but lack the foundational knowledge needed to participate with confidence.

This gap is most visible in areas such as volatility, risk exposure, custody, platforms, wallets and transactions. New investors may understand the broad appeal of crypto, but not the operational details that shape real outcomes.

When mistakes or losses happen, the asset class is often blamed. In many cases, however, the issue starts much earlier: unclear assumptions, limited preparation or decisions made without fully understanding the risks.

Healthier participation requires a more deliberate approach. Investors should know why they are entering a position, how much risk they are prepared to take and what role the investment plays in their wider strategy.

That means setting exposure limits, avoiding all-in decisions, separating conviction from hype and understanding the basic mechanics before committing significant capital.

The problem beyond theory

Another key observation is that knowledge does not always translate into successful execution. A beginner may understand risk management, diversification and custody in principle. But navigating an exchange, setting up a wallet, managing decentralised custody and avoiding operational mistakes can still feel overwhelming.

This creates risk beyond market volatility. In digital asset markets, users can make reasonable investment decisions and still face losses because of poor execution, confusing tools or avoidable errors. This reinforces a larger point: education alone is not enough. Users also need systems that reflect how people actually behave, especially when decisions are being made under pressure.

How systems shape financial behaviour

Financial outcomes are shaped not only by individual choices but by the systems around them.

When tools are fragmented or difficult to use, users are more likely to take shortcuts: copying trades, chasing trends, reacting to market noise or relying too heavily on online communities.

These behaviours are not always reckless. Often, they reflect systems that do not support clear decision-making. Better tools, stronger guardrails and trusted infrastructure can reduce avoidable errors and help users participate with greater intention.

Also Read: The capital cost strategy: Why high initial investment is your strongest protection

Why regulation and usability matter

The regulations which have been set in Singapore are now a part of the wider system that influences behaviour and discipline.

While regulation can feel restrictive, it can also support trust, security and long-term viability. It does not replace education or personal judgment, but rather, has the potential to create clearer expectations and more sustainable participation.

This thinking points toward what the space still needs most: platforms and infrastructure that bridge the gap between digital asset education and practical participation.

Crypto as part of a wider innovation cycle

Like many venture-backed startup ecosystems, crypto has developed through familiar stages: early scepticism, fragmented tools, rapid adoption and, only later, the deeper understanding and infrastructure needed for mainstream trust.

Its rise also reflects a broader shift in how people think about wealth, especially as traditional paths to financial security feel less certain.

More people want earlier access to opportunity, but access alone is not enough. It needs to be supported by education, better tools and stronger safeguards.

A longer view on a fast-moving space

Crypto is still something to think about over the long term, and not just a quick trade.

The space is still finding its shape, and that process is likely to stay volatile for a while. But the more important story is not just what the technology becomes. It is how people are changing their relationship with wealth, risk, and opportunity.

For younger generations, the traditional 30-year playbook no longer feels as dependable as it once did.

The next wealth playbook will not be built on patience alone. It will need to combine long-term discipline with earlier access, clearer education, safer infrastructure and better systems that help people participate responsibly in a financial world that is changing faster than before.

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.

Join us on WhatsAppInstagramFacebookX, and LinkedIn to stay connected.

The post Why the 30-year wealth playbook is breaking down appeared first on e27.

Posted on Leave a comment

Value creation: The higher you rise, the deafer you get

You have spent hundreds of thousands of dollars learning what your customers think. You have never once understood who they are.

Try this. Ask someone on your executive team to draw the letter E on their forehead — fast, without thinking. Some will draw it readable to themselves. Others will draw it readable to the person facing them.

The direction is not random. In a 2006 study published in Psychological Science, Adam Galinsky and colleagues at Northwestern and Stanford primed participants with feelings of high or low power, then ran this exact test. Those primed with power were nearly three times more likely to draw the E, facing themselves — 33 per cent against 12. Power does not sharpen your ability to see from another’s perspective. It systematically destroys it.

The researchers called this a “power-induced impediment to perspective taking.” I call it the occupational disease of every successful leader.

The deafness is not a character flaw. It is a side effect of the chair.

A lighthouse has the same condition. It throws light miles into the dark with total conviction — and cannot hear the ship scraping its own rocks. Most companies, after a certain age, become lighthouses. They broadcast. They do not receive.

Every company is broadcasting, but no one is listening.

The reason is structural. Sales is broadcasting. Fundraising is broadcasting. Recruiting is broadcasting. Every pitch, every earnings call, every all-hands is won by whoever stands up and explains, with conviction, why the world should bend toward their idea. For years, you are paid — in capital, in talent, in headlines — to transmit. So the beam grows brighter. And the faculty that no one ever promoted you for goes quietly dark.

No one was ever made CEO for what they heard

Here is where it gets expensive. Because you are not ignoring your customers. You are listening to them — or so the invoice says.

Every year, companies spend hundreds of thousands of dollars on surveys, focus groups, and NPS dashboards, then present the findings in slide decks as proof of customer empathy. It is nothing of the sort. A survey is a document you designed, with questions you chose, framed in language that fits your existing categories, delivered to people who answer in the format you provide. You are not hearing the customer. You are hearing yourself, refracted.

Also Read: The AI trust gap: Why SEA startups need proof before they scale

The focus group is worse. You bring people into a room — your room, your agenda, your moderator — and call it listening. Nobody tells the truth in a room they were paid to enter. Nobody says what they actually do in a life they were not asked to live in front of you.

The most expensive research in the world is still broadcasting, dressed up as a question.

CB Insights read 483 startup post-mortems. The leading cause of death was not capital, nor the team. It was “no market need.” Forty-two per cent. They built what the survey said people wanted — and found no one waiting.

Why startups die 

Source: CB Insights, “The Top 12 Reasons Startups Fail.”

The leading cause of startup death is building what no one was asking for.

And the most dangerous signal is not the one you failed to survey. It is the one your own people already knew — and could not say.

When researchers interviewed 76 Nokia managers for a 2016 study in Administrative Science Quarterly, they found a company that had seen the smartphone threat clearly and could not speak. Engineers knew. Middle managers knew. Every report was softened on the way up until the truth reached the top floor, sanded into something survivable. Nokia did not lack the signal. It had built an organisation perfectly designed to dim it before it arrived.

Also Read: Great talent is what happens after AI creates the first draft

The market was talking the whole time. So were the people three floors below you.

There is only one way to understand a person. You have to go where they live, watch what they actually do — not what they say they do — and stay long enough to see the gap between the two. Nobody understands by watching from a distance. Nobody understands by asking. You understand by entering.

When Toyota redesigned the Sienna, the chief engineer did not commission a study. He drove 53,000 miles across North America — every US state, every Canadian province, into Mexico — because he believed he had no right to design for a life he had not lived inside. That is not a research method. That is a different idea about what understanding requires.

Hear. Then see. Then — only then — do.

Most companies stop at the first step and call it enough. Most never even get that far. They send a survey instead, then wonder why the product felt right in the boardroom and wrong in the world.

So before the next research budget gets approved, before the next focus group convenes, before you stand up at the all-hands and show the NPS score as evidence that the company is listening —

Draw the E on your forehead. Be honest about which way it faces. And ask yourself: when did you last enter a customer’s life, rather than summon them into yours?

This article is part of David Kim’s Value Creation column. It sits alongside the Asia Value Creation Awards, which aim to recognise PE and VC teams driving long-term, fundamentals-led value creation across the region.

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.

Join us on WhatsAppInstagramFacebookX, and LinkedIn to stay connected.

The post Value creation: The higher you rise, the deafer you get appeared first on e27.

Posted on Leave a comment

Gold, stocks, and crypto are all falling together: The correlation trap

The crypto market dropped 1.11 per cent to US$2.22 trillion over the last 24 hours. Bitcoin is now US$64,439.47; that’s after the first press conference by the new FED chair. Bitcoin led this selling pressure and dictated the broader downward trajectory across all cryptocurrency pairs. The cryptocurrency space currently shares a 63 per cent correlation with the S&P 500 and a 68 per cent correlation with gold. This shared macroeconomic movement defines the current environment and proves that digital assets now operate as a mature macroeconomic asset class.

The current downturn reflects a broader liquidity event rather than a fundamental failure of the underlying technology. Traditional finance and digital assets now move in tandem, reacting to the exact same macroeconomic triggers, employment data, and central bank policies that drive global capital flows. Investors must recognise that crypto no longer exists in a vacuum, and every tick in the bond market sends ripples through the blockchain ecosystem.

Bitcoin experienced a severe flash crash that wiped out over US$25 million in leveraged positions within a single hour. The price dipped below US$64,000 as the Royal Government of Bhutan transferred US$34.5 million in Bitcoin to Binance. This direct selling pressure, combined with technical breakdowns, accelerated the decline and triggered automated margin calls. Bitcoin maintains a 58.24 per cent market dominance, meaning any weakness in the primary asset pulls the entire ecosystem lower and drains liquidity from smaller tokens.

Traders watch the US$64,000 to US$65,000 support zone very closely right now to determine the next major move. If the price holds this level, the market might stabilise and find a local bottom for the week. A break below this threshold will likely trigger further liquidations and push the total market capitalisation down toward the US$2.1 trillion mark, causing significant pain for participants who use excessive leverage.

Also Read: SpaceX’s US$75B IPO will drain crypto liquidity. Here is what happens next

The pain extends far beyond the primary asset, affecting the entire altcoin ecosystem with brutal efficiency. Major tokens, including Cardano, XRP, AAVE, and CRV, fell between two per cent and four per cent, severely underperforming the broader market decline and exhibiting extreme weakness. The CMC Fear and Greed Index currently sits at 22, which indicates extreme fear among participants and a complete lack of buyer confidence.

Traders actively reduce exposure to higher-beta assets in this environment, where participants avoid risk and prefer to hold stablecoins or cash. The decline represents a massive sell-off across the board rather than an isolated incident, and we currently lack rotational support into alternative narratives. I will watch the Altcoin Season Index closely for any signs of recovery or shifting capital flows. A sustained rise above 50 will signal returning risk appetite, but we currently lack that momentum and must remain highly defensive.

The traditional finance world is experiencing severe turbulence, which directly impacts digital asset prices and overall market liquidity. US benchmarks slumped after Federal Reserve Chair Kevin Warsh held rates at 3.50 per cent to 3.75 per cent during his first FOMC meeting. The updated dot plot signals a potential rate hike by year-end, shocking many market participants who expected relief. The US two-year yield jumped 13 basis points to 4.18 per cent, marking the highest level since February 2025 and increasing borrowing costs across the economy.

Nine of the 18 FOMC officials pencilled in a rate hike for 2026, while only one official forecast a cut, highlighting a deeply divided committee. This hawkish stance contrasts sharply with the March summary of economic projections, which anticipated 25 basis points of cuts to support growth. The Fed also revised its 2026 inflation forecasts upward, projecting 3.6 per cent for headline PCE and 3.3 per cent for core PCE, up from previous estimates of 2.7 per cent. They also lowered GDP growth expectations to 2.2 per cent from 2.4 per cent, signalling severe stagflationary risks.

Also Read: Why US$60K is the most important number in crypto right now

This hawkish pivot crushed sectors that remain highly sensitive to interest rates and consumer spending power. The S&P 500 index, which weights all companies equally, fell 1.50 per cent, underperforming the benchmark that weights companies by market capitalisation by 29 basis points, as large tech stocks offered minimal protection. The Discretionary, Real Estate, Staples, and Communications sectors all dropped more than two per cent as investors sought safety and reduced equity exposure.

Commodities also felt the immense pressure from the stronger dollar and shifting geopolitical dynamics. Gold snapped a four-day winning streak and tumbled 1.7 per cent amid elevated real yields and a lack of safe-haven demand. The US Dollar index rose 0.8 per cent to 100.3, tightening global financial conditions. Brent crude slid for a fifth straight session to about US$78 per barrel, hitting its lowest level in three months as the US-Iran peace deal prepares for signing in Geneva.

Meanwhile, retail investors continue to treat the stock market like a casino and ignore macroeconomic warnings. They poured into US stocks at a record pace on the day of the SpaceX initial public offering, surpassing the previous record by 58 per cent. SpaceX itself experienced wild volatility, rising 5.9 per cent in early trade before finishing the session down 4.9 per cent at US$191.82. I have always viewed these speculative financial activities as a form of gambling, albeit one with slightly better odds than traditional casinos.

The immediate trajectory of both traditional and digital markets hinges on clarity from the Federal Reserve and Bitcoin price action over the coming weeks. The current downturn stems primarily from an event Bitcoin drove, and altcoin weakness and caution ahead of the meeting exacerbated the decline. A hold above US$64,000 could lead to consolidation, but failure will test the yearly low at a US$2.1 trillion total market cap. I monitor daily Bitcoin ETF flows and derivatives volume to gauge institutional sentiment accurately and anticipate the next major liquidity shift.

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.

Join us on WhatsAppInstagramFacebookX, and LinkedIn to stay connected.

The post Gold, stocks, and crypto are all falling together: The correlation trap appeared first on e27.

Posted on Leave a comment

Vietnam isn’t just inviting private capital in. It is structurally dependent on it

There is a number at the centre of Vietnam’s development ambition that does not get nearly enough attention: US$270 billion. That is the annual investment requirement the country will need to sustain by 2030 to meet its economic growth targets. This figure represents not just an aspiration but a hard structural constraint on Vietnam’s trajectory.

Today, Vietnam’s annual investment needs sit at approximately US$160 billion. According to the Vietnam Innovation and Private Capital Report by DO Ventures and Boston Consulting Group, that number is projected to grow to US$270 billion within five years, an increase of roughly 70 per cent in less than a decade.

Also Read: Vietnam’s biggest PE bet of 2025 was not on tech. It was on what 100M people eat every day

The drivers are well understood: a massive infrastructure deficit spanning roads, ports, airports, and urban transit systems; an energy transition that requires enormous capital to shift away from coal and scale up renewables; and the sustained fixed asset investment needed to support an economy targeting upper-middle-income status by 2030.

The arithmetic of this challenge is unambiguous. The Vietnamese state, however capable and motivated, cannot close a US$270 billion annual funding gap through public expenditure alone. Private capital, domestic and foreign, venture and institutional, debt and equity, is not a supplementary channel in this story. It is a structural necessity.

The infrastructure deficit is the immediate pressure point

Vietnam’s infrastructure has been a persistent drag on an otherwise exceptional growth story. The country’s road network, while expanding, remains inadequate for the volume and weight of industrial freight generated by its manufacturing sector. Port capacity in key export hubs is chronically congested. Urban public transport in Hanoi and Ho Chi Minh City, both cities with populations in the millions, remains largely dependent on motorcycles and private vehicles, with metro systems that have taken years to build and are only now beginning to carry meaningful passenger volumes.

The scale of the infrastructure backlog means that even sustained public investment, which Vietnam has prioritised, maintaining one of the highest public investment-to-GDP ratios in the region, cannot close the gap at the required pace. Public-private partnership frameworks have existed on paper for years. Still, the track record of PPP deal execution in Vietnam has been patchy, constrained by legal ambiguity, disputes over risk allocation between government and private partners, and a regulatory environment that has historically been more comfortable with state-led development than with market-driven infrastructure finance.

Changing that dynamic is not optional if Vietnam is to fund its 2030 ambitions. The capital markets deepening that comes with the FTSE Emerging Market reclassification in September 2026 will help by broadening the institutional investor base that can participate in infrastructure bonds and listed infrastructure vehicles. But bond market development, regulatory reform of PPP structures, and the creation of bankable project pipelines that meet international investment standards will all need to accelerate in parallel.

The energy transition is the long-term capital challenge

If infrastructure is the immediate pressure point, energy is the structural challenge with the longest time horizon and the largest capital requirement. Vietnam has committed to ambitious renewable energy targets and signed up to international climate frameworks that require a substantial shift in its power generation mix.

Also Read: Vietnam’s AI funding just grew 13x in two years. Now comes the hard part

Coal, which still accounts for a significant share of Vietnam’s electricity generation, needs to be progressively retired and replaced. This process is capital-intensive at every stage, from financing new renewable capacity to decommissioning legacy assets and constructing grid infrastructure capable of handling variable output from wind and solar.

The global energy transition investment market is enormous, and Vietnam is increasingly competitive for a share of it. The country’s renewable energy potential, particularly offshore wind along its extensive coastline and solar irradiance in its southern regions, has attracted serious interest from international developers and infrastructure funds. Several large-scale offshore wind projects are at various stages of development, though regulatory uncertainty regarding power purchase agreements and grid access has delayed final investment decisions.

Private capital will not flow at the required scale into energy transition projects unless the regulatory environment provides sufficient certainty for investors to underwrite long-duration assets. This is as much a policy challenge as a market one, and the speed at which Vietnam resolves outstanding regulatory ambiguities around renewable energy investment will be a significant determinant of how much of the US$270 billion annual target can realistically be mobilised from private sources.

Domestic capital markets must do more of the heavy lifting

One of the less discussed dimensions of Vietnam’s investment gap is the role of domestic capital. The country’s household savings rate is high, and Vietnamese investors have historically channelled a disproportionate share of their wealth into property and gold, asset classes that are familiar and culturally embedded but do not efficiently intermediate capital into productive investment. The development of deeper, more liquid, and more diverse domestic capital markets (such as equity, bond, and alternative investment vehicles) is essential if the savings of Vietnamese households are to be redirected towards the infrastructure, energy, and productive capacity investment that the economy requires.

The growth of Vietnam’s domestic securities market has been significant: daily trading volume reached US$1.2 billion in 2025, and the number of domestic brokerage accounts has grown rapidly. But the bond market, which is typically the vehicle through which long-duration infrastructure assets are financed, remains relatively thin and illiquid by the standards of Vietnam’s peer economies. Corporate bond market development, in particular, suffered a significant setback following several high-profile issuance scandals in 2022 and 2023, and restoring confidence in that market will take sustained regulatory effort and time.

The opportunity framing matters as much as the challenge framing

There is a temptation to read the US$270 billion figure primarily as a problem, an obligation that Vietnam may struggle to meet, with uncomfortable consequences for its growth ambitions if it falls short. That framing is incomplete. From the perspective of global capital allocators, Vietnam’s investment requirements are also among the largest and most clearly defined deployment opportunities in emerging Asia.

Investors who can navigate the regulatory environment, structure deals that align with government priorities, and adopt a sufficiently long time horizon are positioning themselves in a market where capital is both urgently needed and, increasingly, structurally supported by policy. The FTSE reclassification, ongoing capital market reforms, and the explicit recognition in government policy that private capital is necessary, not merely welcome, all point to a market that is progressively lowering the barriers to large-scale institutional investment.

Also Read: 48 PE investors, US$3.96B deployed, and not a single IPO exit in five years. Something is broken.

The gap between US$160 billion today and US$270 billion by 2030 is not a forecast of failure. It is a statement of intent and an invitation. The question is whether the global investment community moves quickly enough and whether Vietnam’s regulatory infrastructure matures fast enough to convert that invitation into deployed capital at the scale the country’s ambitions require. The clock, as the report makes clear, is already running.

The post Vietnam isn’t just inviting private capital in. It is structurally dependent on it appeared first on e27.

Posted on Leave a comment

Funded: The VC liked you, that’s not the same as yes

I’ve sat on both sides of that table.

The founder walks out thinking it went well. The VC was engaged, asked good questions, and said, “Really interesting space.” Nobody said no. The founder goes home and starts thinking about term sheets.

The VC closes their laptop and moves to the next meeting. They’re not being cruel. The deal just didn’t fit.

This happens hundreds of times a year across SEA. And in the impact and climate space, it happens even more, because the distance between a founder’s reality and what a VC can actually underwrite is wider than anyone admits publicly.

Here’s what the VC is actually thinking in that room. Nobody writes this down.

The problem isn’t the mission, it’s the shape

Impact VCs carry a double mandate. Financial return and measurable impact. That sounds like more reason to say yes to a great climate founder. It’s actually more reasons to say no.

The round size has to fit the fund. The stage has to match the thesis. The revenue model has to show a path the LP committee can follow. The impact has to be measurable in a way that satisfies the impact committee. That’s four filters before the founder’s deck gets to page three.

Most climate founders in SEA are building real things solving real problems. Solid waste, grid infrastructure, clean mobility, adaptation tech. The problem is the venture isn’t shaped for the instrument being offered. The VC isn’t rejecting the mission. They’re rejecting the misfit.

Also Read: The VC model isn’t broken, Southeast Asia’s LP ecosystem is

The gap nobody talks about

There is a layer of capital sitting between a climate founder’s current stage and a VC check that almost nobody in SEA is navigating deliberately. Catalytic grants. Development finance. Foundation capital. JETP-linked programs. Blended structures.

These aren’t consolation prizes. For a climate venture at the right stage, they are actually the smarter first move, cheaper, non-dilutive, and designed for exactly the proof points that make a VC say yes six months later.

But founders don’t know this map. And VCs aren’t drawing it for them. It’s not their job.

So the founder keeps pitching equity to people who can’t write that check yet. The VC keeps seeing deals that are one capital layer too early. Both sides leave the room frustrated. Nobody says why.

What actually needs to change

The meeting going well is not the problem. The problem is what happens before the meeting, how the founder structured the business, what proof they built, and what capital they used to build it.

A climate founder who walks into a VC room having already closed a catalytic grant, used it to hit a specific proof point, and can now show traction, that’s a different conversation entirely. That founder is raising equity to scale something proven, not to prove something unproven.

That’s the founder who gets the funding.

The ones who don’t aren’t less talented or less mission-driven. They just never got shown the door they should have walked through first.

That door exists. Most founders walk past it every week. And the VCs watching them do it don’t say a word.

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.

Join us on WhatsAppInstagramFacebookX, and LinkedIn to stay connected.

The post Funded: The VC liked you, that’s not the same as yes appeared first on e27.