SEA of Startups

Two stories from Southeast Asia this week, and almost nobody connected them.

The Philippines unveiled the marker for the Pax Silica industrial hub in New Clark City. Twenty plus companies expressed interest. A dozen are billion-dollar US firms. And on the same day, Manila publicly rejected the US request for diplomatic immunity and US legal jurisdiction over the zone. The hub will operate under Philippine law.

Malaysia rewrote the rules of how startups go public on Bursa. VC firms can act as listing agents. Retail investors can participate for the first time. A real funding escalator from regulated crowdfunding to LEAP Market to ACE Market.

But the Malaysia story is part of something bigger. Singapore signed an SGX-Nasdaq dual listing bridge last November. The ASEAN-6 signed a cross-border depository receipts MOU in December 2024. Indonesia is tightening listing rules to chase quality. The whole region is rebuilding its public markets for venture-backed companies at the same time, and almost no one is tracking it as one story.

This episode walks through the two races happening in Southeast Asia right now. The industrial race for the AI economy, and the capital markets race for venture-backed exits. Each country is making different bets. Each country is solving for a different segment. Where you build matters now in a way it didn't five years ago.

I'm bullish on the Philippines. But the country has a gap on the capital markets side, and closing that gap is the work of the next two years.

Real. Raw. Relatable.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit seaofstartups.substack.com

There’s a version of this week that looks like a good week for Southeast Asia’s startup ecosystem.

The Q1 2026 funding report shows the highest quarterly capital raised since late 2022. Malaysia’s hottest IPO in sixteen years prices and lists next week. OpenAI and Anthropic both announce major new enterprise offerings backed by some of the biggest names in global private capital.

Here’s the version where you actually read the numbers.

One data centre deal accounts for over 70% of the quarterly funding total. The chip company getting 95 times oversubscribed has three-quarters of its revenue coming from China and a tax exemption that expired eight months ago and hasn’t been renewed. And the AI labs building $4 billion services arms are, if you read what they’re actually saying, admitting that their models are not easy to deploy in the real world.

Three stories. Let’s take them properly.

* * *

The Real Q1 2026 Funding Number

DealStreetAsia dropped their Q1 2026 Southeast Asia funding report this week. It’s making the rounds. The headline: $2.81 billion raised, the highest quarterly total since Q4 2022.

One deal, DayOne, a Singapore-based data centre operator, raised $2 billion in a Series C. I’ll put a mild caveat on that: this is a data centre, not technically a startup, and it was spun off from an existing entity. It’s in the numbers because it carries a Series C label. That’s fine. But it’s worth knowing what you’re looking at.

Strip it out. You have just under 100 deals and under $800 million combined. The lowest quarterly deal count in at least eight years.

That’s the actual funding market founders in this region are navigating right now. Not the headline. The actual market.

On the Singapore Number

The report shows Singapore capturing 91.5% of total capital. I’m honestly always a little skeptical of that figure in isolation, and here’s why.

Singapore is the home of the holdco. If you’re a founder in Malaysia or Indonesia or Vietnam trying to raise international capital, you’re not going to stay registered in your home jurisdiction. You’re going to put a holding company in Singapore, because the legal and regulatory environment is cleaner, because international investors are more comfortable with it, because that’s just how it’s done. Your operating company may still be fully onshore in your home market.

So some portion of what gets reported as “Singapore funding” is actually capital going into companies operating across the region, just routed through a Singapore holdco. How much? Hard to know. But it’s worth holding that nuance when you see the 91.5% figure.

What it definitely does tell you is that the Singapore jurisdiction matters, for capital access, for legal infrastructure, for institutional credibility. That part is real regardless of the holdco effect.

Malaysia: Signal or Noise?

The report calls out Malaysia as a bright spot, ranking second in Southeast Asia by deal volume for the first time. Eighteen deals, the highest quarterly count since Q3 2024.

I’m active in the Malaysian ecosystem. My honest read: take this with some salt. When you dig into what drove the number, a meaningful portion came from small cheques through a single accelerator programme. That’s not nothing, but it’s not the same as organic deal activity across the ecosystem.

I don’t want to be the one pouring cold water on every green shoot, and I’m not saying the Malaysian ecosystem isn’t moving. But there’s a difference between an ecosystem inflection and a batch of accelerator cheques inflating a quarterly number. We’ll know more by Q3.

Where the Money Is Actually Going

If you’re a founder asking where capital is flowing: AI. Specifically agentic AI, automation of workflows, tasks that execute with limited human oversight. Not chatbots. Actual agents doing actual work.

AI and ML deals came in second by volume in Q1 with thirteen transactions. The biggest was Amity’s $100 million Series D. Worth noting: Amity has a long-standing relationship with CP Group, one of Thailand’s largest conglomerates, which is the lead investor. That context matters for how you read the round. It doesn’t diminish the achievement, it’s still a strong signal of appetite in the space, but it’s worth knowing.

The message for founders: if you’re building real enterprise automation, real measurable productivity gains, there is capital. Not a lot. But it exists and it’s consistent.

The Quiet Problem Nobody Names

There’s something that doesn’t get said clearly in this ecosystem, so let me say it.

There is a growing number of zombie companies across Southeast Asia. Not failed companies, companies that can’t raise new capital, can’t grow meaningfully, but won’t die. They exist in a kind of operational limbo. Technically alive. Burning slowly.

Part of what sustains this is that down-rounds almost never happen here. The funds across the region are still relatively young. The LP relationships are new. Nobody wants to be the one writing a markdown into their portfolio, having that conversation, taking that medicine. So instead, they hold the valuation flat, keep the paper TVPI looking reasonable, and wait.

You can talk about your book value multiple all you want. If the company can’t raise and can’t grow, the number isn’t real.

The downstream problem: there are cases where this dynamic is actually blocking deals. An investor who doesn’t want to see a down-round may resist a transaction that would otherwise be good for the company, because accepting it means acknowledging the valuation they’ve been carrying is wrong.

Sometimes you have to take one step back to take two steps forward. That’s not a comfortable thing to do. But it’s more honest than pretending nothing is wrong until there are no options left.

* * *

SkyeChip and Malaysia’s Chip Moment

I want to start this one with genuine enthusiasm, because it deserves it.

SkyeChip Bhd lists on Bursa Malaysia’s Main Market on May 20th. The public tranche closed 95 times oversubscribed. Total retail demand hit RM 3.04 billion. The largest retail subscription in Malaysia since Petronas Chemicals in 2010, sixteen years ago.

The whole AI and chip investment wave has been impossible to ignore. NVIDIA’s share price trajectory. The compute boom. The data centre buildout. And now, emerging from Penang, a Malaysian company that sits right in the middle of that stack. That’s a big deal for this ecosystem.

Upfront caveat: I’m not a semiconductor expert. What follows is based on my research into the prospectus and what’s been circulating in the analyst and retail investor community. Take it in that spirit.

What SkyeChip Actually Does

Malaysia’s semiconductor sector has historically been dominated by the back end: assembly, testing, packaging. Important work. But it’s the low-margin end of the chain. The government has pushed for years, through NIMP 2030, through IC design parks in Selangor and Penang, through various national initiatives, to move the industry up the value chain into front-end design.

SkyeChip is the poster child for that ambition. It’s a fabless IC design company, it doesn’t manufacture chips, it designs silicon intellectual property. Reusable building blocks that chip makers integrate into their own products.

Think of it this way: TSMC makes the chips, NVIDIA designs what goes on them. SkyeChip is not saying they service either of those companies, but the analogy holds, they sell the blueprints for specific components that go inside chips. Their flagship IP is HBM3E: high-bandwidth memory interface technology, the memory architecture inside the AI accelerators that run the large language models powering frontier AI.

That’s the tie-in to the chip craze. And it’s why the hype is real. This isn’t fabricated. The technology is real.

The National Story

The government is leaning in hard, and in this case the support is substantive not just rhetorical. SkyeChip gets access to Arm Holdings design tokens through Malaysia’s Silicon Vision initiative, a national licensing arrangement that gives Malaysian companies access to Arm’s IP architecture. That’s a genuine strategic asset, not a marketing line.

The Deputy Minister attended the prospectus launch and talked about SkyeChip potentially reaching the level of Broadcom. Broadcom is a $700 billion company. SkyeChip is listing at RM 1.6 billion. The ambition is clear. The road is long.

But what matters is that this company is creating a visible proof point, that a Malaysian IC design house can be built, can reach a meaningful scale, can list on the main market, and can attract global attention. The next founder who wants to build something like this now has an example. That matters for the ecosystem in ways that go beyond the specific valuation.

The Numbers Worth Noting

Revenue more than doubled over two years. Profit margins around 30%. Analysts projecting roughly 31% earnings CAGR over three years, with the most bullish target price close to double the IPO price of RM 0.88.

The business model, IP licensing, is a proven high-margin, scalable model. Arm, Cadence, Synopsys. These are multi-billion dollar businesses built exactly this way: create the IP once, license it repeatedly. SkyeChip isn’t reinventing the model. It’s executing on it with new IP in a hot category.

The Risks That Deserve Honest Attention

China Revenue and US Export Controls

For the seven months ending October 2025, China accounted for 73.3% of revenue. Almost three-quarters of the company’s most recent revenue came from Chinese fabless IC companies selling advanced HPC and AI chips.

The prospectus explicitly acknowledges that if any of their customers are added to the US Entity List, supply must be suspended. None are listed today, but today is a snapshot, not a guarantee. The company is also planning to open US offices, which creates a real balancing act between serving Chinese customers and operating in a US regulatory environment that is actively tightening controls on exactly this category of IP.

The Tax Exemption Expired

This is the one I keep coming back to.

SkyeChip has been operating under a Pioneer Status tax exemption, effectively a 2.7% tax rate. That exemption expired September 9, 2025. They applied for renewal. As of the last published date in the prospectus, the renewal is still under review.

The IPO is priced at 44x FY2025 earnings. Those earnings use a 2.7% tax rate that no longer exists. Normalise to a standard 25% rate and you’re paying closer to 57x.

Most analysts will have noted this. But it’s worth being explicit about: the multiple headline is priced on a tax rate that hasn’t been legally valid for eight months and may not be renewed. That’s a material question sitting unresolved at the point of listing.

Revenue Quality and Customer Concentration

Top three customers represent around 60% of FY2025 revenue. More importantly, the revenue model is largely non-recurring, lump-sum contracts, one-off sales, high upfront. You need to keep winning new work to replace completed contracts.

Retail investors who have done deep dives on the prospectus, the i3investor and KLSE Screener community has been thorough here, have flagged that several of the largest customers from earlier years no longer appear as active. Replaced by new Chinese customers with sub-one-year relationships. Customer names are undisclosed so independent verification isn’t possible, but the pattern is worth understanding before you subscribe.

Where I Land

Malaysia needs stories like this. We need proof points that deep tech can be built here, that front-end design is achievable, that a Malaysian company can capture global demand in a critical technology category. SkyeChip creates that proof point. Congratulations to the team and their investors, genuinely.

The technology is real. The Arm access is real. The revenue growth is real. There’s genuine substance here and, looking at comparable companies globally, there’s still room for upside even from the IPO price.

The risks are also real. China concentration, an expired tax exemption, non-recurring revenue, some customer churn buried in the prospectus. None of these are necessarily deal-breakers. All of them require the optimistic scenario to hold.

Watch the listing day on May 20th. The market will be more honest than any analyst note about how much of the 95x was conviction and how much was leverage-financed retail applications planning a day-one flip.

* * *

OpenAI and Anthropic Just Told You the Hard Part

This is the most globally significant story of the week. And I think it has the most direct implication for founders building in Southeast Asia right now.

Within the same week, Anthropic first, then OpenAI, both companies announced they are building enterprise AI services companies. Not products. Not model updates. Not API pricing changes. Services companies. Engineers going inside client organisations and building AI systems for them.

What They Announced

OpenAI announced on May 11th. They’re calling it the OpenAI Deployment Company. Launching with over $4 billion in initial investment from 19 founding partners, TPG leading, with Bain Capital, Brookfield, Goldman Sachs, SoftBank, McKinsey, and Capgemini in the group. OpenAI also acquired Tomoro, an applied AI consulting firm, and brought roughly 150 engineers into the venture from day one. OpenAI retains majority ownership.

The model: Forward Deployed Engineers (FDEs) embedded directly inside client organisations. They work with business leaders and frontline teams to identify where AI can have the biggest impact, redesign workflows around it, and build production systems connected to the company’s actual data and infrastructure.

Anthropic announced a week earlier, backed by Blackstone, Hellman and Friedman, Goldman Sachs, General Atlantic, Apollo, GIC, and Sequoia. Same fundamental concept. Their framing specifically targets mid-market: community banks, mid-size manufacturers, regional health systems. Companies that could benefit enormously from AI but don’t have the internal resources to build and run frontier deployments.

When you look at the roster of investors across both of these efforts, you’re seeing a significant portion of global private capital touching large segments of the broader economy. This is not a side bet.

The Palantir Model

To understand why this matters, you need to understand what Palantir built over the last two decades.

Palantir’s entire model was built on one idea: you can’t sell complex software to complex organisations and expect them to use it well. You have to embed engineers inside the organisation. Work through the legacy systems, the internal politics, the messy reality of how things actually get done inside a large enterprise. Build something that functions in that specific environment.

That made Palantir extraordinarily sticky. Once you’ve had a team embedded inside an organisation for months, rebuilding core operational workflows around your platform, good luck ripping that out. The model is controversial. Critics call it consulting dressed as software. Believers say it’s the only honest way to sell software to organisations that don’t know what they need.

OpenAI and Anthropic are applying that same logic to AI. At scale. With billions behind it.

If the models were easy to deploy, these services arms would not need to exist. Full stop.

The Deployment Gap Is the Real Problem

Enterprise AI has a gap that doesn’t get enough honest discussion. The models work. Claude works. GPT works. The demos are genuinely impressive. But when companies try to deploy these systems into actual operations, into fifty-year-old legacy software, complicated permission structures, compliance requirements, and workflows that have developed organically over decades, the complexity is enormous.

The gap between “this model is impressive” and “this model is running reliably inside our organisation and measurably improving how we operate” is not a small gap. It is enormous. And closing it requires human expertise, people who understand the technology and the specific operational context of the organisation.

The fact that both labs are committing at this scale to closing that gap is an admission. Model quality is not the bottleneck anymore. Deployment is the bottleneck. And that reframes where value sits in the AI stack.

The Inversion of SaaS

Here’s a framing I’ve been thinking about. The SaaS era was defined by software being light on the surface, an interface you accessed yourself. The software sat on top of your workflow but you still had to do the work. Self-service by design.

What these services arms represent is something different. The model is going deep into the workflow, understanding it, rebuilding it, and then leaving behind something that runs with minimal human intervention. You’re not delivering software. You’re delivering a running operation. Services as software.

If that model sticks, and the fact that it’s being backed this heavily suggests it will, the companies that win are not the ones with the best model. They’re the ones who can deploy the best model inside the most complex environments, with the most contextual understanding of how those environments actually work.

What This Means for Southeast Asia

OpenAI’s Deployment Company is starting in US enterprise. Anthropic is starting in US mid-market. Neither of them is starting in Southeast Asia.

That means the deployment gap in this region is not going to be closed by Silicon Valley in the near term. Someone local has to do it.

The bank in KL running a fifty-year-old core banking system. The Indonesian manufacturer with warehouses of paper records. The healthcare group operating across five countries with different languages and different regulatory frameworks in each market. These aren’t problems that a foreign firm can parachute in and solve. They require local knowledge, local language, local relationships, and long-term on-the-ground presence.

The two most credible AI labs in the world just confirmed there is a structural, multi-billion dollar opportunity for exactly this business. The window to build it before the global players get here is not unlimited.

If you are building an AI services or implementation company in Southeast Asia right now, this week’s announcements are a green light. Pick up the pace. The clients will move slowly, that’s fine, enterprise always moves slowly. You move fast. Get embedded. Build the local relationships. Develop the deployment expertise. Because once you’re in and the workflows are built around what you’ve built, it becomes very hard to replace.

And one more signal worth noting: when AI labs start building services arms, it tells you something about the model layer. If being the best model was a durable, defensible moat, you would not need a services company. You would just keep making the model better and let it sell itself. Both companies have genuinely good models. They’re still building this.

The future isn’t won at the model layer. It’s won at the integration layer, the workflow layer, the trust layer. For founders building AI companies in Southeast Asia, that’s the competition you’re actually in. And it’s a winnable one.

* * *

What These Three Stories Say Together

Put them next to each other and they’re telling one thing.

The funding market is leaner than the headlines suggest. Capital is concentrating, in Singapore, in AI, in infrastructure. The zombie problem is real and growing quietly. There are silver linings: Malaysia is moving, agentic AI has consistent demand, and the data centre boom is real even if it distorts the quarterly numbers.

SkyeChip is the most tangible proof point this ecosystem has produced in years that big, globally relevant deep tech can come out of Malaysia. Whether it becomes a durable business depends on questions the prospectus cannot yet answer. The execution has to turn the IPO moment into something lasting.

And the global AI labs just spent billions telling you that the hard part of AI isn’t the model. In Southeast Asia, the opportunity to do that hard part, the deployment, the integration, the on-the-ground expertise, is wide open and freshly validated.

The founders who understand that and move on it in the next twelve to eighteen months are the ones worth watching.

This post accompanies the SEA of Startups episode for the week of May 13, 2026. Listen wherever you get your podcasts.

Real. Raw. Relatable.

SEA of Startups | Kevin Brockland

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit seaofstartups.substack.com

This week’s episode is a news episode. No guests. Just four stories that I think every founder, investor, and operator in Southeast Asia should be paying attention to right now.

Here’s what we cover, and why each one matters.

1. China forced Meta to unwind a completed acquisition. Mid-honeymoon.

In December, Meta acquired Manus — the AI agent startup that went viral in 2025 as China’s answer to deep research tools. The deal closed. Manus’s website was already saying it was part of Meta.

On April 28th, Beijing’s NDRC told both parties to reverse it.

The Singapore-washing playbook — where Chinese founders restructure as Singapore entities to access US capital — is now provably dead. Beijing just proved it can reach into a completed acquisition, across jurisdictions, and pull the plug.

But the surface story is not the interesting story. The interesting story is the mechanics of what an “unwind” actually looks like. Money has already flowed through to investors and their LPs. Engineers have been working inside Meta for weeks. Knowledge transfer has happened. How do you reverse that?

And then there’s the Meta question. Did they make a mistake — or did they knowingly race the regulator, betting that if they got the technology embedded before enforcement could land, a slow unwind would be better than no acquisition? Their public statement — “the transaction complied fully with applicable law, we anticipate an appropriate resolution” — says absolutely nothing. Which might be exactly the point.

Singapore has been conspicuously silent throughout all of this. What that silence costs them is a conversation the episode goes deeper on.

2. eFishery. Nine years. And it still doesn’t feel like enough.

Gibran Huzaifah was sentenced to nine years on April 29th. Two other former executives received nine and seven years respectively.

The numbers, if you haven’t heard them: the company told investors it generated $752 million in revenue from January to September 2024. Actual revenue was $157 million. They reported a $16 million profit. The actual result was a $35 million loss.

SoftBank. Temasek. KWAP — Malaysia’s civil servant pension fund. All recovering less than ten cents on the dollar.

But this episode is not a crime recap. The eFishery story is a prompt for a harder question about what kind of ecosystem we’re building here.

Fraud exists on a spectrum. At one end: criminal fabrication at scale. At the other: things that happen every week across the region that would never see a courtroom — vanity metrics dressed as traction, pilots treated as revenue, LOIs presented as signed contracts. None of that is eFishery. But it is on the same continuum.

And it is not only founders. Investors do it too.

The reason this matters beyond the immediate case is economic. In a high-uncertainty market like Southeast Asia, trust is the operating system. When it erodes — when every investor assumes every founder is telling the most optimistic version of the truth — the whole system gets more expensive. More friction. More time on verification. Fewer deals done.

A high-integrity environment is a high-output environment. The ecosystem gets the standards it is willing to enforce.

3. Indonesia capped ride-hailing commissions at 8%. GoTo just posted its first-ever profit. Congratulations.

On May 1st — International Workers’ Day, timing very much intentional — President Prabowo signed a regulation capping the maximum commission ride-hailing platforms can take from drivers at 8%. Down from 20%. Drivers now get a minimum of 92% of every fare.

GoTo shares dropped nearly 6% on the news. Analysts estimated the ride-hailing segment accounted for roughly 48% of GoTo’s EBITDA. Grab, which derives about 20% of its total EBITDA from Indonesia, is also in the firing line.

Both companies will either raise fares, eat the margin hit, or some combination of both. None of those options is clean.

Here is the part that might be unpopular in a room full of investors: Prabowo is not entirely wrong.

Indonesia has around four million ride-hailing drivers. The platform without the driver is just an app with nowhere to go. The economics for drivers have been genuinely rough. The system was designed to extract maximum value from a class of workers with very little negotiating power.

The underlying question — how do we ensure the people who actually do the work get a fair share of what they create — is legitimate. If platforms do not answer it voluntarily, governments will answer it for them.

The risk, of course, is that fares go up, volumes drop, and drivers end up worse off than before. That is the irony of heavy-handed regulation. But that is a problem for GoTo and Grab to solve. They had the data. They should have got ahead of this before a president had to sign a decree on Workers’ Day.

4. Malaysia is building gas plants to power AI data centres. The energy transition did not plan for this.

This week, a Melaka-based company called DPS Resources — until recently primarily a furniture and property developer — announced it signed an MOU with an Alibaba affiliate to explore building a $1.1 billion AGI data centre in Melaka. 150 to 180 megawatts. DPS provides the land, the power, the infrastructure. Alibaba’s entity handles operations and brings the computing demand.

This deal is not an anomaly. It is a perfect emblem of what is happening across Malaysia right now. Everyone wants a piece of the data centre gold rush. The question not being asked loudly enough is whether Malaysia actually has the power to sustain it.

TNB’s pipeline is 7,500MW across 56 data centre projects. Current actual load from those facilities: 850MW. The draw-down is coming as facilities rack up through 2026. At the same time, 6,400MW of coal-fired generation is scheduled for retirement between 2029 and 2031.

To cover those retirements and meet rising demand, Malaysia needs roughly 12,000MW of new generation by 2031.

Right now, the Energy Commission has an open tender — NewGen26 — for new gas-fired generation to plug that gap. Bids close July 1st. Eight weeks away. This is Malaysia racing to build baseload capacity before the demand wall hits. The fact that it is gas, not solar, tells you everything about the timeline pressure.

The Iran conflict makes this personal. TNB’s Automatic Fuel Adjustment mechanism means global oil and gas price spikes feed directly into Malaysian electricity bills within 30 days. Data centres in Johor were approved on the premise of cheap, stable Malaysian electricity. That premise is now under pressure from a war on the other side of the world.

The deeper question is who actually benefits from this boom. DPS provides the land and the power. Alibaba keeps the data, the models, and the IP. Research consistently shows data centres create the lowest number of jobs per square foot of any major facility type. Thousands of construction roles during the build, then roughly 200 operational staff when running.

Malaysia is providing the real estate, the utilities, and the environmental cost. The hyperscalers are keeping the value.

That is not a reason to stop. But it is a reason to be far more deliberate about what we are trading and what we are getting in return.

Watch the episode

Four stories. One theme running underneath all of them: the rules are being rewritten. Who controls AI. Who controls capital flows. Who gets a fair share of the value created. Who owns the infrastructure the future runs on.

These are not settled questions. They are live negotiations — between governments, between companies, between regions.

Southeast Asia is not a passive observer in any of this.

[Watch / listen to the full episode → link]

SEA of Startups is a podcast for founders, investors, and operators building in Southeast Asia. Real. Raw. Relatable.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit seaofstartups.substack.com

Episode Title: The New Space Age Is Actually Here | Artemis II, SpaceX IPO & The Rise of Orbital Infrastructure

Episode Summary

Right now, four humans are flying around the moon. Not in a simulation. Not in a film. For real. Kevin uses the launch of Artemis II on April 1, 2026 as the jumping-off point for a deep dive into the most consequential shift in space exploration since the Apollo era — and why this time, it's not just governments leading the charge.

From SpaceX's against-all-odds origin story to the trillion-dollar IPO that just rocked public markets, this episode charts how the economics of space fundamentally changed, what that means for a new generation of startups, and whether the science fiction stories we grew up watching are finally, actually, coming true.

What We Cover

Artemis II — Who's on board, what they're testing, and why this 10-day lunar flyby matters beyond the symbolism

The cost collapse — How SpaceX drove launch costs from $10,000–$20,000/kg down to under $2,000/kg (and potentially below $100 with Starship)

The space economy by the numbers — $8B+ raised in 2025 alone, 154% YoY growth, 35,000+ companies globally, a projected $1T market by 2033

Startups reshaping the supply chain — Rocket Lab, Apex, Hadrian, The Exploration Company, and the infrastructure plays most people aren't watching

Earth observation goes commercial — How Planet Labs and others turned satellite data into a sovereign government revenue model

The SpaceX IPO — Filed confidentially the same day as Artemis II, targeting a June NASDAQ listing at a reported $1.5–2T+ valuation (potentially the largest IPO in history)

Starlink's numbers — 10M subscribers, $10B revenue in 2025, projected $24B by end of 2026, and what direct-to-cell really means

Orbital data centers — Star Cloud's H100 GPU satellite, Google's Project Suncatcher, Blue Origin's TeraWave, and why AI's energy problem might get solved in orbit

The moon as infrastructure — Lunar ice mining, the South Pole fuel depot play, and Lone Star Data Holdings building a data center on the lunar surface

The sci-fi question — Are the stories we grew up with finally coming true?

Key Numbers

StatFigureSpace tech funding raised in 2025$8B+YoY growth in space funding154%Projected space market by 2033~$1 trillionNew employees added in the past year~200,000Cost to orbit in the 1990s$10,000–$20,000/kgCost to orbit today (Falcon 9)Under $2,000/kgStarlink subscribers (end of 2025)10 millionStarlink revenue 2025$10BSpaceX IPO reported valuation$1.5–2T+Star Cloud Series A valuation$1.1B (18 months old)

Companies & Missions Mentioned

SpaceX · Artemis II / NASA · Rocket Lab · Planet Labs · Apex · Hadrian · The Exploration Company · Star Cloud · Lone Star Data Holdings · Blue Origin (TeraWave) · Google (Project Suncatcher) · xAI · Starlink

People Mentioned

Reed Wiseman — Artemis II Commander

Victor Glover — Artemis II Pilot; first Black person to travel to the moon

Christina Koch — First woman to travel to the moon

Jeremy Hansen — First Canadian to travel this far from Earth

Jared Isaacman — NASA Administrator

Elon Musk — SpaceX / xAI / X

Chad Anderson — Founder, Space Capital

Quotes Worth Sharing

"SpaceX didn't just build a business. It rewrote what was possible."

"The interplanetary story is no longer confined to Elon Musk's conference slide decks. It's in regulatory filings. It's in rocket test programs. It's in the hiring plans of hundreds of companies."

"The gap between what the stories promised and what actually happened at times felt like a wound. But now I look at what's actually happening and I find myself genuinely surprised."

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Most AI content gives you a framework. Tiwa York gives you a verdict.

The founder who built Kaidee to 35 million users and guided it to a successful exit sat down with SEA of Startups and said what most operators are afraid to say out loud: your team is probably performing AI adoption, not doing it. And the longer you stay there, the harder it gets to move.

Here’s what he actually said — the numbers, the examples, the provocations.

The 5 Levels of AI Maturity (And Why 1.5 Is a Trap)

Tiwa’s framework runs from 0 to 4. Most conversations stop at listing the levels. The more important conversation is why so many companies get stuck halfway through Level 1.

Level 0 — Unaware: No AI tools in use. Working like it’s 2019.

Level 1 — Curious: ChatGPT is bookmarked. It gets used for emails and translation. Actual work output: unchanged.

Level 1.5 — The Trap: This is where Tiwa spends most of his time on stage. A few people are experimenting. Strategy decks mention AI. But workflows, decisions, and output haven’t moved. He calls this adoption theater — and it’s where the majority of SEA companies currently sit.

Level 2 — Active: AI is genuinely built into daily work. Measurable productivity gains of 25–50%.

Level 3 — Integrated: Multiple AI tools connected in smooth workflows. The data analyst goes from one report a week to one a day. The PM tests ideas overnight with simulated customers. 2–3x productivity — and completely redesigned ways of working.

Level 4 — Transformative: Creating value streams that simply didn’t exist before. Tiwa estimates this is roughly 2% of the global workforce today.

The goal isn’t to inch from 1.5 to 2. It’s to move from 1.5 to 3, and then to 4. Anything less is rearranging deck chairs.

The Mental Model That Changes Everything

Tiwa’s most useful reframe isn’t a framework — it’s a metaphor.

Think of AI as the most capable but most forgetful intern you’ve ever hired. It can do almost anything better than any employee on your team. But the moment it leaves a conversation, it remembers nothing. Zero context. Starting from scratch.

This metaphor matters because it tells you exactly what your job is: you’re not a user of AI. You’re a systems designer for AI. Your task is building the handoff infrastructure — the context-carrying mechanisms, the memory systems, the structured prompts — that prevent that amnesia from killing your output quality.

Tiwa draws a direct parallel to the Toyota Production System. You’re not optimising one conversation. You’re building a manufacturing process for intelligence, with daily standups, continuous improvement loops, and institutional memory that compounds over time.

Most companies treat AI like a vending machine. High performers treat it like a factory floor.

The Numbers That Should Stop You Mid-Sentence

If you think the efficiency gap between good and great AI usage is somewhere between 20–30%, Tiwa has a number for you.

The difference between a 30% productivity gain and a 300x productivity gain isn’t the model you’re using. It’s how you’re using it.

That’s not a typo. 300x. The delta between someone using AI as a faster search engine and someone who has built genuine fluency — with context management, iteration discipline, and system-level thinking — is not incremental. It’s categorical.

On token economics specifically, Kevin cited Jensen Huang’s framing directly: a developer earning $500K annually should be spending roughly $250K a year in AI tokens. That’s the ratio of a high-performance AI-native engineer. For context: serious power users are already spending $500+/month on tokens. Some AI-native startups are at $1,000 per person per day.

If your developers aren’t asking for AI budget, Tiwa’s take is unambiguous: that’s a performance issue.

The Hiring Freeze Argument (And Why It’s Not Crazy)

The most provocative position Tiwa took in the recording:

Freeze all hiring until your AI implementation is complete.

The reasoning is mathematical. Communication pathways explode non-linearly with headcount:

* 5 people → 10 pathways

* 10 people → 45 pathways

* 20 people → 190 pathways

Every person you add before you’ve stabilised your AI workflows creates coordination overhead that compounds. You’re layering human complexity on top of unresolved process complexity. The problems don’t add — they multiply.

The implication for most early-stage SEA founders: your instinct to hire for growth may be the thing slowing your growth. A team of 6 people who are genuinely at Level 3 will outrun a team of 15 people stuck at Level 1.5, every time.

The Middleware Trap: A Warning for Builders

Tiwa is an investor. He’s pattern-matching on where value will be captured — and where it will evaporate.

His verdict on horizontal and middleware AI companies: 18-month obsolescence risk. The major frontier models are absorbing middleware functionality as a matter of course. If your moat is sitting between the model and the enterprise, that’s a shrinking gap.

The defensible positions he sees in SEA:

* Vertical solutions with deep workflow integration and hard-to-replicate domain understanding

* Regulated, complex legacy environments where switching costs are real and proprietary data is locked in

* Physical AI — Tiwa cited MUI Robotics, which has deployed an AI tongue (taste and smell sensors) across dairy companies, water utilities, and hotel renovation monitoring, and is currently running a research project on early liver cancer detection through smell. 300+ clients. 50+ multinationals. That’s not a middleware play.

The common thread: proprietary data, physical integration, or regulatory complexity. If you can be replaced by a model update, you’re not building a business — you’re building a feature.

Two Real Examples, Not Hypothetical Ones

The Jira/Confluence Replacement: A software development house replaced its entire project management stack — Jira, Confluence, the lot — in four days using AI-assisted development. Annual savings: $24,000. More importantly, they own the system now. No vendor dependency. No per-seat pricing. No waiting for a roadmap that doesn’t match their workflow.

The HubSpot Replacement: A friend of Tiwa’s replaced their entire HubSpot instance with a custom-built CRM in eight hours of AI-assisted coding. Eight hours. The off-the-shelf tool cost thousands annually and didn’t fit the workflow. The custom solution does — and it cost a weekend.

The pattern here isn’t “build vs. buy.” It’s “stop buying things that make you dependent when you could own the thing in a day.”

What AI-First Actually Requires From Leadership

Tiwa’s framework for leaders isn’t about tool selection. It’s about accountability architecture.

The key shifts:

Every function owns its own transformation. This can’t live with the CTO alone. Engineering, product, marketing, finance, customer success — every team lead is responsible for their own AI integration roadmap.

Model the behaviour publicly. If leadership isn’t visibly using AI — and visibly failing with it, learning from it, sharing what they found — no one else will take the cultural signal seriously.

Measure outcomes, not activity. Logins aren’t fluency. Licenses aren’t execution. The metrics that matter: workflow velocity, decision speed, output quality. Not hours of AI training completed.

Daily continuous improvement. Not a quarterly AI review. A daily standup cadence for what’s working, what broke, what gets refined tomorrow. Toyota didn’t build the production system in a sprint. Neither will you.

The Real Question

Tiwa closed with the line that stayed with everyone in the room.

“The question isn’t how do we find extraordinary people. It’s whether extraordinary people get unleashed inside this org — or leave to do it on their own.”

For founders in SEA: you probably already have the talent. The judgment is in the building. The only variable is whether you build the systems that let it operate at full power — or whether you stay at Level 1.5 long enough that the people who figured it out first come back to compete with you.

Watch the full conversation with Tiwa York on SEA of Startups

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit seaofstartups.substack.com

In the ever-changing landscape of technology and business, the term “SaaSpocalypse” has emerged to describe the recent downturn in public software stocks. But what does this mean for the future of SaaS companies, especially in Southeast Asia? In this blog post, we’ll explore the nuances of the SaaSpocalypse, the potential for growth amidst disruption, and what established and emerging companies can do to adapt.

Understanding the SaaSpocalypse

The term SaaSpocalypse refers to the recent significant decline in the valuations of publicly traded SaaS companies. This decline has raised concerns about the future viability of these companies. But is the doom and gloom justified?

The Current Landscape

- Valuation Adjustments: Many SaaS companies have seen their valuations drop sharply, leading to discussions about overvaluation in the sector. As Chris Birrell notes, some of these companies were indeed due for a correction.

- Growth Continues: Despite the downturn, many SaaS companies are still experiencing growth rates of 15-20% year-over-year, which, although lower than previous highs, indicates resilience in the market.

Key Insight: The SaaS market is not dying; it’s evolving. Companies that can adapt to new technologies, especially AI, may find new opportunities for growth.

The Role of AI in SaaS

AI is a game-changer for many industries, and SaaS is no exception. As the demand for AI integration grows, traditional SaaS companies must adapt.

Embracing AI Technologies

- Increased Demand for AI Solutions: Companies are under pressure to integrate AI into their workflows. This presents both a challenge and an opportunity for incumbents who can leverage their existing customer relationships to offer new, AI-driven solutions.

- The Risk of Disruption: While established companies may have a strong foothold, they are not immune to disruption. New entrants who can offer innovative solutions may quickly gain traction.

Example: Companies like Salesforce are well-positioned to sell AI-driven solutions, thanks to their existing customer base and established workflows.

Navigating Change: Strategies for SaaS Companies

As the industry evolves, SaaS companies in Southeast Asia must consider their strategies carefully. Here are a few key areas to focus on:

Focus on Core Competencies

- **Defensible Moats**: Companies with deep integrations into their clients’ workflows are better positioned to weather market fluctuations. Understanding what makes your service indispensable can help you maintain customer loyalty.

- **Avoiding the Surface-Level Solutions**: Companies that offer point solutions without deep integration risk losing market share to more comprehensive platforms.

Capitalizing on Regional Nuances

Southeast Asia is a unique market, and understanding local dynamics can provide a competitive edge.

- Local Expertise: Companies with founders who understand regional challenges are likely to succeed where larger, global firms may falter. This localized approach can help companies tailor their solutions to meet specific market needs.

The Future of SaaS in Southeast Asia

Looking ahead, what does the future hold for SaaS companies in Southeast Asia?

Opportunities Amidst Challenges

- Emerging Startups: As Chris mentions, startups that can build reusable software components tailored for AI-driven environments may find success. There’s a growing need for specialized solutions that can integrate seamlessly with existing workflows.

- BPO Evolution: Business Process Outsourcing (BPO) companies are also on the brink of transformation. By leveraging AI, they can enhance their service offerings and improve efficiency, setting the stage for a new era in service delivery.

Conclusion: Adapting for Success

In conclusion, while the SaaSpocalypse presents challenges, it also opens up avenues for growth and innovation. Companies that can adapt to the changing landscape—embracing AI, focusing on core competencies, and understanding regional market nuances—will be well-positioned to thrive in the future.

Key Takeaways:

- The SaaSpocalypse is not the end, but a transition.

- Embrace AI and focus on integration to maintain your market position.

- Understand regional dynamics to tailor your solutions for success.

---

Frequently Asked Questions

What is the SaaSpocalypse?

The SaaSpocalypse refers to the significant decline in valuations of publicly traded SaaS companies, raising concerns about the future of the industry.

How can SaaS companies adapt to the changing landscape?

By integrating AI solutions, focusing on their core competencies, and understanding regional market dynamics, SaaS companies can navigate the challenges ahead.

Is the SaaS industry dying?

No, the SaaS industry is evolving. Companies that can innovate and adapt will continue to thrive.

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit seaofstartups.substack.com

Keywords

Meta, Manus, acquisition, Singapore, AI, geopolitics, startups, tech industry, business growth, investment

Summary

In this conversation, Kevin and Kim discuss Meta's recent acquisition of Manus, a Singapore-based startup, exploring its implications for founders in the region, the geopolitical landscape, and the evolving nature of AI in business. They analyze the rapid growth of Manus, the significance of Singapore as a tech hub, and the challenges posed by regulatory scrutiny. The discussion highlights the potential for Southeast Asia to emerge as a key player in the global tech ecosystem, while also addressing the complexities of company nationality and the future of AI amidst geopolitical tensions.

Takeaways

Meta's acquisition of Manus raises questions about the future of startups in Southeast Asia.

The deal signifies a shift in how tech companies navigate geopolitical landscapes.

Manus's rapid growth showcases the potential for startups in the region.

Acquisitions are not just about money; they often buy time and talent.

AI is changing the valuation landscape for tech companies.

Singapore is becoming a strategic hub for tech companies looking to scale globally.

The concept of 'Singapore washing' raises important questions about company nationality.

Geopolitical tensions could impact future tech acquisitions.

The success of Manus could inspire more founders in Southeast Asia.

Southeast Asia has the potential to be a significant player in the global tech ecosystem.

Titles

Meta's Bold Move: What It Means for Founders

Navigating Geopolitics in Tech Acquisitions

Sound bites

"They just bought time."

"Does it really matter? Not really."

"Singapore is the neutral zone."

Chapters

00:00 The AI Landscape and Major Players

02:45 Geopolitical Implications of AI Investments

05:53 The Role of Singapore in the Global Tech Ecosystem

08:54 The Evolution of AI and Market Dynamics

11:54 Regulatory Challenges and Market Valuations

14:17 The Future of AI and Founders' Perspectives

18:01 Navigating Nationality and Compliance in Tech

20:45 The Balance of Speed and Long-term Value Creation

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit seaofstartups.substack.com

Summary

In this conversation, Kevin and Kim discuss the recent merger of Elon Musk's companies, particularly focusing on the implications of combining AI and space technologies. They explore the potential of data centers in space, the evolving role of Tesla, and the regulatory challenges that come with these advancements. The discussion also touches on the future of sovereignty in space and the messy landscape of regulations that may arise as private companies take a more significant role in space exploration.

Takeaways

Elon Musk is merging his companies to simplify operations.

The merger signifies a shift towards a unified intelligence layer.

Data centers in space could revolutionize computing.

Tesla's role is evolving beyond just electric vehicles.

Regulatory challenges will complicate space exploration.

Sovereignty in space is a complex issue.

The landscape of space regulations is becoming messy.

Private companies will play a crucial role in space.

Non-terrestrial data centers are on the horizon.

The future of AI is tied to its infrastructure location.

Titles

The End of the Discrete Company Era

Merging AI and Space: A New Frontier

Sound bites

"AI just got X'd."

"Tesla isn't an EV company anymore."

"It's going to be messy."

Chapters

00:00 The End of the Discrete Company Era

02:07 The Merging of Tech Giants

05:48 Data Centers in Space: A New Frontier

09:53 The Unified Intelligence Layer

14:56 The Future of AI and Space Exploration

20:05 Regulatory Challenges in Space

24:54 The Wild West of Space Law

29:55 The Dawn of a New Era

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit seaofstartups.substack.com

Heyyyy guys,

🧠 TL;DR — What Actually Changed

* SGX × NASDAQ dual listing is a real regulatory breakthrough — but U.S. liquidity remains unproven

* The fintech “funding collapse” was actually capital consolidation into Singapore

* Southeast Asia is shifting from emerging → maturing, with real scaffolding for a capital stack

* Founders + investors have a 24-month window before this becomes table stakes

The Setup: Why This Moment Matters

SGX and NASDAQ just launched a dual-listing bridge — something Southeast Asia’s growth-stage founders have wanted for a decade.

But here’s the twist:

This isn’t about IPO convenience.It’s about Singapore silently building its own version of Silicon Valley’s capital stack — adapted for Southeast Asia’s geopolitical reality.

And it’s happening while the rest of the ecosystem is still parsing the headline.

We are at an inflection point,but not for the reasons most people think.

1. SGX × NASDAQ Dual Listing

Real Liquidity or Ego Liquidity?**

What It Is

A streamlined structure allowing ~$2.5B+ companies to list simultaneously on SGX and NASDAQ without:

* duplicate filings

* conflicting disclosures

* multi-jurisdictional legal chaos

A real regulatory achievement.

What Everyone Assumes

“Finally! A viable U.S. exit path for Southeast Asia tech.”

What It Actually Is

A partial solution — with one massive unanswered question:

Does this create real U.S. liquidity, or just better press releases?

Regulatory friction? Solved.Liquidity, analyst coverage, and market-making? Not solved.

Let’s be blunt:

* Who in New York is covering a $3B ASEAN B2B SaaS they’ve never used?

* Who is trading your stock at 2 a.m. EST?

* How do you compete for attention against trillion-dollar tickers?

In Singapore, you matter.In the U.S., you are… a symbol on a screen.

Who Wins (Right Now)?

* SGX — they can pitch “NASDAQ access” to the entire region

* Founders — they gain optionality and cleaner paperwork

Will U.S. liquidity appear?

TBD.

Yes, AvePoint dual-listed in 2025 — but one data point does not equal a trend.

2. The Fintech Funding ‘Collapse’ That Wasn’t

If you only saw the headline:“SEA fintech funding down 39% YoY.”

You missed the real story:

Singapore captured 84–88% of all fintech dollars.Capital didn’t disappear — it moved to safety.

The Numbers

* $829M raised (SEA fintech, first 9 months of 2025)

* Singapore → 84% (with multiple quarters at 88%)

* Mega rounds continued quietly:

* Thunes — $150M Series D

* Airwallex — $150M Series F

This isn’t contraction. It’s radical selectivity.

When markets tighten, capital flies to clarity.In Southeast Asia, clarity has a postal code — Singapore.

The Nuance No One Mentions

Many “Singapore rounds” are Singapore TopCos with operations elsewhere.But even adjusting for that, the trend is undeniable:

Singapore is becoming the gravitational center of SEAs capital stack.

If You’re Building Outside Singapore…

You need a Singapore strategy now, not “when we hit Series B.”

* Entity structure

* Regulatory setup

* Investor relationships

* Capital access

You cannot retrofit a cap table at scale.

If You’re a Seed Investor…

Your job just became extremely difficult.

You must identify the 10–15% of founders who:

* can reach late stage

* understand jurisdiction strategy

* can navigate regulatory complexity

* know how to design an intelligent capital stack

Most seed funds will not do this.The ones who do will win disproportionately.

3. From Emerging → Mature

Is Southeast Asia Finally Growing Up?**

Silicon Valley is built on a simple assumption:

Build → Scale → Exit on NASDAQ.Because the infrastructure exists.

Southeast Asia has never had that luxury.

Grab went to NASDAQ.Sea went to NYSE.No major regional champion listed on SGX — because the liquidity + coverage didn’t justify it.

What’s Shifting Now?

Singapore is positioning itself as the region’s public-market on-ramp:

* SGX × NASDAQ dual listing

* Extreme fintech capital concentration

* Temasek + GIC reallocating toward deep tech and infrastructure

* Robust IP protection

* $28B RIE2025 deep-tech plan

To become a mature ecosystem, you need:

* A complete capital stackSeed → A → Growth → Pre-IPO → Public markets

* Exit pathways that convertNot theory — execution.

* Signaling mechanismsReal wins → real returns → capital recycling.

We’re not fully there.But for the first time, the scaffolding is real.

4. The Implicit Geopolitical Subtext

U.S.–China decoupling has reshaped global capital flows.

China still owns ~75% of Asia biotech funding…but diversification is accelerating fast.

And Singapore is playing its hand masterfully- clever and very typical.

Singapore is now:

* Neutral

* Globally aligned

* Legally predictable

* Highly trusted

Signals:

* Biotech capital shifting to Singapore & South Korea

* Flagship Partnering × A*STAR: $100M deep-tech commitment

* Talent and IP migrating to strong-jurisdiction hubs

This isn’t incremental.It’s a generational repositioning. (See it now?)

5. What Founders Should Actually Do

(Immediately)**

1. Five-Decision Audit

Label your last 5 decisions: Offense or Defense.If you’re 4–1 defensive, you’re playing not to lose.

2. Entity Structure Review

Make your TopCo dual-listing ready:clean cap table → clean governance → clean audit trail.

3. Live Capability Target List

Every month, update your list of 10 companies/tech you may:Acquire → Partner → Replicate.

4. Board Transformation Agenda

Shift board meetings from quarterly KPIs → 3–5 year capability maps.

This is how category-defining companies build.

6. What Investors Should Do

Late-Stage Investors

Dual listing optionality changes your entire underwriting model:

* valuation ceilings shift

* secondary liquidity widens

* crossover investor interest increases

* exit horizons change

Audit portfolio readiness now.This advantage won’t last long.

Seed Investors

Your edge becomes:jurisdiction strategy + regulatory guidance + capital stack architecture.

This is no longer “nice-to-have.”It’s competitive advantage.

7. The 24-Month Window

Here’s the uncomfortable truth:

The founders and investors who move now will define the next decade.

Infrastructure windows don’t stay open:

* SGX is motivated today

* NASDAQ is paying attention today

* Capital is concentrating today

* Regulations are flexible today

In 3–5 years?

This either becomes table stakes —or a missed opportunity we’ll reference for a generation.

8. The Question Southeast Asia Has Been Asking Wrong

For years the ecosystem asked:

“Can Southeast Asia produce the next Google?”

Wrong question.

The real one is:

“Can Southeast Asia build systems that consistently produce category-defining companies?”

For the first time, the answer is trending toward yes — cautiously, but convincingly.

Not because of one unicorn.But because the infrastructure is finally being built.

* dual listing bridge

* capital consolidation

* sovereign repositioning

* regulatory maturity

* talent density

* deep-tech investment

Together, they form the early blueprint of a Southeast Asian capital stack.

Purpose-built for this region.Not imported.

Before You Go

This year stretched us — in the best way.

We decoded:

* orbital compute

* fintech infrastructure

* regional capital flows

* AI rails

* cross-border regulation

A pattern emerged:

Southeast Asia isn’t catching up.It’s reshaping itself.

We’re taking a short break — a reset, a recalibration (maybe even one day off our phones… maybe).

But 2026?We’re coming back with the founders building the next layer of infrastructure — the kind that defines decades.

Stay curious.Stay ambitious.Keep building.

The ecosystem is leveling up.All we need now is you.

— Kim & KevinSEA of Startups

SGX NASDAQ dual listing, Singapore capital markets, Singapore fintech funding 2025, Southeast Asia IPO pathways, SEA startup ecosystem, Singapore dual listing strategy, capital stack Southeast Asia, NASDAQ Asian companies, Singapore startup hub, venture capital SEA, fintech Singapore trends, deep tech Singapore RIE2025, Singapore TopCo structure, regional tech IPO strategy, Southeast Asia exits, liquidity Singapore market, Singapore economic strategy

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit seaofstartups.substack.com

THIS WEEK'S REALITY CHECK

Google just published research that makes every data center in Southeast Asia look obsolete.

Project Suncatcher: Space-based AI data centers hitting cost parity with terrestrial operations by 2035. Launch costs dropped from $10,000 to $1,500 per kilogram. SpaceX is targeting $200/kg.

This isn't science fiction. It's a $100 billion economic shift happening right now—and Southeast Asia has exactly 24-36 months to position itself as the ground station hub or watch the value flow elsewhere.

This episode breaks down why orbital compute is inevitable, what it means for AI and agriculture in the region, and the moves founders need to make before the infrastructure moats lock in.

WHAT WE COVER

🚀 The Economics That Just Flipped

Launch costs: $10K → $1.5K per kg (and falling to $200/kg by 2035)

Why Google's betting on orbital over terrestrial

8x more solar efficiency + free cooling in vacuum of space

How SpaceX made the impossible economically viable

☀️ Project Suncatcher Breakdown

What Google's actually building (and why now)

Technical challenges: maintenance, thermal radiation, data latency

Why StarCloud just launched NVIDIA-powered mini data center into orbit

The radiation hardening problem (and how it's getting solved)

🌾 The $400B Agriculture Angle Nobody's Connecting

How satellite-based Earth observation transforms Southeast Asian farming

Thailand could gain $8-12B annually from precision agriculture

Real-time insights: soil health, planting windows, pest prediction

Why AcerX raised $30M+ to build this infrastructure now

🏗️ Infrastructure Gets Its God's-Eye View

Mining companies using orbital imaging for mineral exploration

Utilities gaining real-time grid monitoring capabilities

Why Southeast Asia's equatorial position = massive strategic advantage

Ground station networks as the next critical infrastructure moat

💰 Who's Building What (And Who's Getting Funded)

AcerX (Singapore): $30M+ for satellite data platforms

One Orbit: $12M for environmental monitoring

LunaSat (Malaysia): Affordable small satellite manufacturing

Planet Labs: $500M raised, largest Earth observation constellation

⏰ The 24-36 Month Window

Why regional coordination matters right now

What happens when infrastructure moats lock in

Five tactical moves for AI, agriculture, and infrastructure founders

Policy frameworks that need to exist yesterday

KEY QUOTES

"While Malaysia debates water usage for data centers and Singapore worries about electricity grids, Google's preparing to bypass all of it with orbital compute." - Kim

"Southeast Asia is either positioning itself as the ground station hub for the orbital economy, or it's watching $100 billion in economic value flow elsewhere." - Kevin

"Agriculture in this region is a $400 billion industry that's been fundamentally inefficient for centuries. Space-based analytics running in orbit and beaming down real-time insights changes everything." - Kim

"The window for Southeast Asia to position itself in this ecosystem is 24-36 months. After that, the players are locked in and we're customers, not builders." - Kevin

"I have to give credit where it's due: Elon Musk basically came in and inspired everyone to look at space as economically viable. Nobody was thinking about private sector space before SpaceX." - Kevin

FEATURED DATA POINTS

🚀 Launch cost trajectory: $10,000/kg (2005) → $1,500/kg (2025) → $200/kg target (2035)

☀️ Solar collection efficiency: 8x more productive in space than terrestrial panels

💰 Economic opportunity: $100B+ potential GDP contribution to Southeast Asia

🌾 SEA agriculture market: $400B annually

📊 Thailand agriculture gains: $8-12B potential annual productivity increase

⚡ Power advantage: Constant solar (if positioned in dawn-dusk synchronous orbit)

❄️ Cooling advantage: Thermal radiation in vacuum = no water consumption

💸 Funding activity:

AcerX: $30M+ raised (Singapore satellite data platforms)

One Orbit: $12M raised (environmental monitoring)

Planet Labs: $500M raised (largest Earth observation constellation)

⏱️ Latency advantage: 1-7ms orbital (vs 150ms trans-Pacific)

🛰️ StarCloud: NVIDIA-powered orbital data center launched November 2025

TACTICAL TAKEAWAYS FOR FOUNDERS

If you're building AI:

Map which workloads could migrate to orbital compute (training jobs especially)

30-40% cost reduction potential on frontier model training

Build relationships with space tech companies now (AcerX, One Orbit)

Factor orbital into your Series B infrastructure assumptions

If you're in agriculture:

Pilot satellite data integration immediately (don't wait for perfect tech)

Partner with companies deploying Earth observation analytics

Operational knowledge compounds—5-year head start matters

Thailand, Vietnam, Indonesia = massive precision agriculture TAM

If you're infrastructure/utilities:

Real-time satellite analytics for grid monitoring, pipeline integrity

Ground station partnerships should be strategic priority

Asset tracking, disaster resilience, environmental compliance

Government engagement needed now for spectrum/site allocation

For all founders:

Don't assume compute stays terrestrial forever

Engage policy conversations on orbital infrastructure early

Build optionality: not all-in on space, but not ignoring it

The companies learning to operationalize space-based insights now win in 2030

For VCs:

Space tech is no longer government-only domain

Launch costs dropped to venture-backable levels

Regional companies competing against Silicon Valley with 1/10th the capital

Ground station infrastructure = strategic moat worth backing

RESOURCES MENTIONED

📄 Google X: Project Suncatcher Research Paper

📄 SpaceX Launch Cost Analysis 2025

📄 Southeast Asia Agriculture Market Report

📄 Singapore Space Agency: Industry Updates

📄 StarCloud: NVIDIA Orbital Data Center Launch Announcement

📄 Planet Labs: Southeast Asia Partnership Programs

📄 AcerX: Satellite Data Platform for SEA Supply Chains

📄 One Orbit: Environmental Monitoring Constellation

📄 Malaysia LunaSat: Small Satellite Manufacturing

COMPANIES TO WATCH

Building in Southeast Asia:

AcerX (Singapore): $30M+ raised, satellite data platforms for supply chains & agriculture

One Orbit: $12M raised, AI-powered environmental monitoring constellation

LunaSat (Malaysia): Affordable small satellite manufacturing for regional deployment

Global Players Seeking SEA Partnerships:

Planet Labs: $500M raised, largest Earth observation network, actively seeking SEA partnerships

StarCloud: Just launched NVIDIA-powered orbital data center (Nov 2025)

SpaceX: Targeting $200/kg launch costs by 2030

Blue Origin: Ramping up commercial launch operations

🔗 CONNECT WITH US

📧 Newsletter: https://seaofstartups.substack.com

💼 LinkedIn:

Kim (WeiiSyuen) Yeoh: https://www.linkedin.com/in/weiisyuenyeohacmacgma/

Kevin Brockland: https://www.linkedin.com/in/kbrockland/

🎧 Listen:

Spotify: [Link]

Apple Podcasts: [Link]

YouTube: [Link]

💬 Comment below: Is your five-year plan accounting for orbital compute? Or are you assuming infrastructure stays terrestrial forever?

TAGS

space tech, orbital computing, Google Project Suncatcher, AI data centers, SpaceX, satellite technology, Southeast Asia startups, agriculture technology, precision farming, infrastructure innovation, venture capital, deep tech, AcerX Singapore, space industry, renewable energy, AI infrastructure, LEO satellites, Earth observation, ground station networks, digital infrastructure, ELon Musk, Steve Jobs

WHAT'S NEXT

Next episode: Interviewing the CEO of a solar company that just IPO'd—directly relevant to space-based power infrastructure discussion.

Upcoming: More deep dives on infrastructure shifts reshaping Southeast Asia's tech ecosystem.

📌 PIN THIS: If you're building in AI, agriculture, logistics, or infrastructure in Southeast Asia, this episode is required listening. The decisions made in the next 24-36 months determine who participates vs. spectates in the $100B orbital economy.

Share this with:

Founders building deep tech or AI infrastructure

VCs evaluating space tech investment opportunities

Government officials planning digital infrastructure policy

Anyone who thinks data centers will stay on Earth forever

⚡ VIRAL SHARE QUOTE:

"Southeast Asia has 24-36 months to position itself as the ground station hub for orbital compute—or watch $100 billion in economic value get built elsewhere while we're still debating cooling systems."

This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit seaofstartups.substack.com