The National Bank of Bahrain (NBB) has signed a memorandum of understanding with blockchain settlement network Partior to study whether the Bahraini dinar (BHD) can be settled on the Singaporean firm’s rails, with NBB acting as the currency’s settlement bank.

Read the fine print and the ambition shrinks to its proper size. The MoU commits the two parties to evaluate an operating model, implementation requirements and technical feasibility, and to work out what Bahrain’s regulators would require. There is no launch date, no live service and no disclosed financial terms. It is, for now, a feasibility study with a signing ceremony.

Also Read: Tokenised assets have moved on-chain. The liquidity has not followed

Still, the deal says a good deal about where Partior wants to go, and why a piece of Singapore-born financial plumbing keeps turning up in the Gulf.

The plumbing problem

Cross-border bank payments still run largely on correspondent banking: chains of banks holding accounts with one another (the “nostro” and “vostro” accounts of banking jargon), each link adding time, fees and opacity. A transfer can take days, and billions sit idle in pre-funded accounts around the world, waiting for business hours to overlap.

Partior’s answer is a shared ledger on which member banks settle with each other directly and around the clock, using tokenised commercial bank money rather than cryptocurrencies or stablecoins. Each currency is anchored by a settlement bank that holds the real money and issues its digital twin on the network.

The network currently supports three currencies, the US dollar, the euro and the Singapore dollar, through its founding settlement banks, as e27 has explained before.

Adding the dinar would therefore be a first on two counts: a new currency and a new settlement jurisdiction. NBB would do for the dinar what JP Morgan, DBS and Deutsche Bank do for the dollar, the Singapore dollar and the euro.

A Singapore idea, exported

Partior was set up in 2021 by DBS, JP Morgan and Temasek, building on the Monetary Authority of Singapore’s Project Ubin experiments with blockchain-based interbank settlement.

Standard Chartered led its Series A in 2022, and Deutsche Bank later joined as a strategic investor in a Series B that reached US$80 million.

Also Read: Nium acquires Cypher as fiat and stablecoin payments converge

The Gulf has since become its busiest expansion front. Emirates NBD went live with real-time cross-border dollar settlement on the network, with JP Morgan acting as settlement bank in the first phase. When Partior announced its Series B, it named the UAE dirham, the Qatari riyal and the Saudi riyal among currencies it planned to add, alongside the Malaysian ringgit. The dinar was not on that list, which makes NBB a new opportunity rather than a pipeline delivery.

Partior chief executive Humphrey Valenbreder framed the deal as building on the company’s “growing presence across the GCC”. NBB’s Vineet Munot was more guarded, saying the bank would weigh the technical, operational and regulatory considerations before deciding on its value. That caution is the most honest line in the announcement.

Why a small currency matters

The dinar is pegged to the US dollar at roughly US$2.66 per dinar, making it one of the world’s highest-valued currencies but a modest one by volume. For Partior, the prize is less the dinar flow itself than proof that a mid-sized jurisdiction can bring its local currency onto the network, with a local bank as anchor and a local regulator comfortable with the arrangement.

That proof matters for Southeast Asia. Every currency Partior adds beyond its founding trio is a dry run for the ringgit, the baht, the rupiah or the peso. Asia’s cross-border payment flows are enormous, pegged at a US$23.8 trillion opportunity in one contributor’s analysis, yet they remain split across currencies with thin direct liquidity between them.

The Gulf also hosts large communities of Filipino and Indonesian workers, so Gulf-ASEAN corridors are hardly abstract. But a caveat applies: Partior is wholesale, bank-to-bank infrastructure. Faster interbank settlement only reaches a migrant worker’s family if banks and remittance firms pass the savings on, and that has rarely been automatic.

A crowded field

Partior is far from alone. Its own investor JP Morgan runs Kinexys, a blockchain payments network for corporate clients. Swift is building a blockchain-based ledger with Consensys.

Project mBridge, a multi-central-bank platform whose members include the Bank of Thailand and the central banks of the UAE and Saudi Arabia, settles in central bank digital currencies.

Project Nexus, incubated by the Bank for International Settlements, aims to link instant payment systems, including those of Malaysia, the Philippines and Singapore.

Then there are stablecoins, which are chasing the same corridors from the other direction. Circle has agreed to buy Singapore’s Tazapay for US$400 million, while SBI has backed dtcpay’s Japan-SEA stablecoin corridors. Partior’s quiet selling point is that it keeps money inside the regulated banking system, sidestepping the dollarisation worries that stablecoins raise for emerging-market central banks.

MoUs are cheap

Bank-led blockchain consortia have a mixed record. Trade finance networks such as we.trade and Contour were wound down after banks failed to route enough business through them. Partior has done better than most: it is live, it has several settlement banks and it is building round-the-clock liquidity with LSEG’s Digital Settlement House, with production targeted from early 2027.

Also Read: AI agents could help Southeast Asian firms untangle cross-border payment costs

The NBB agreement will be worth more than a press release only when two things happen: the dinar actually goes live, and banks outside the founding circle start sending real volume through it. Until then, Bahrain is a promising line on Partior’s map, not a corridor.

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Every humanoid robot looks brilliant in a launch video. The trouble begins on an ordinary weekday in a warehouse, when a parcel arrives in a shape nobody trained the machine for, a forklift reverses where it shouldn’t, and a worker strolls into its path while scrolling a phone.

That messy gap between the lab and the loading bay is what Hong Kong is now trying to turn into infrastructure. The Hong Kong Productivity Council (HKPC) has launched the Embodied AI International Applications Hub, with the Hong Kong Industrial Artificial Intelligence and Robotics Centre (FLAIR) as its technical lead.

Also Read: Ropedia raises US$22M to build the data layer for robots that understand the real world

HKPC bills it as the city’s first platform built for training, validating and deploying embodied AI. That is the industry’s term for AI housed in a physical body, such as a humanoid, a four-legged robot or an industrial arm, which has to act on the world rather than describe it.

The first phase brings in seven technology partners and eight international “scenario partners”. Scenario partners are the organisations that own the factories, warehouses, shops and public facilities where robots would actually be deployed. The hub targets five areas: manufacturing, smart logistics, retail services, inspection and maintenance, and public services.

A test track, not a showroom

The distinction HKPC is keen to draw is that this is not another glossy demo centre. The pitch is a proving ground. Developers get access to real operating settings, scenario data gets collected, and performance gets measured and fed back into the product.

FLAIR describes a closed loop. It starts with defining the scenario and moves through model adaptation and training, testing, evaluation, data feedback and iteration. The system is then validated again, and the cycle repeats. Systems will be scored on operational accuracy, execution efficiency, reliability, autonomous task completion, safety and how well they adapt to their surroundings.

That list reads like a diagnosis of where robotics keeps stumbling. A robot that behaves perfectly in a controlled lab can come apart when the floor layout changes, the objects differ, the workflow shifts or humans behave like humans. As e27 has reported before, the leap from pilot to production is where many robotics ventures quietly die. Repeated validation across varied conditions is supposed to expose those failure modes before a customer pays to discover them.

The use cases in the launch materials are specific. Logistics robots must handle parcels of all sizes and different warehouse processes. Manufacturing robots must cope with different production lines, equipment standards and safety rules. Inspection and public-facility work may require humanoid or quadruped robots to stay in control in cluttered, unpredictable environments. FLAIR is already showing a flexible embodied-AI production line and industrial robots across manufacturing, logistics, retail and public-service settings.

The quiet prize is data

The deeper value lies less in the hardware than in the data the hub generates. Investors and founders increasingly argue that the real battle in humanoid robotics is about data, not hardware. Real-world scenario data, gathered across many sites and many failures, is scarce and expensive to collect. A hub that systematically harvests it across industries is, in effect, building a dataset as much as a testing facility.

That raises questions the launch materials do not answer. Who owns the scenario data? Can a developer take what it learns in a partner’s warehouse and use it to sell to that partner’s competitor? How are costs split between the government-backed centre, developers and scenario owners? These details will decide whether serious companies bring their best technology or only their safest demos.

Also Read: Why Asia’s Physical AI boom will be decided at the camera, not the model

For scenario owners, the model offers a lower-risk route. A factory or logistics operator can test robots on its own floor without committing to a full rollout. It can also see how a supplier copes with legacy equipment and existing safety procedures before signing a procurement contract. In an industry where purchase decisions are often based on slide decks, evidence collected on site is a useful corrective.

Hong Kong’s bridge play, again

Strategically, the hub fits a familiar Hong Kong script: the city as a bridge between mainland China and the rest of the world. HKPC argues that Hong Kong’s access to the mainland market, combined with its alignment with international standards, makes it a natural cross-regional testing base.

That pitch has a logic. Mainland China is building robot armies at a pace the West is struggling to match. Chinese makers looking to sell abroad, however, face buyers who want proof of safety and compliance on terms they recognise. A Hong Kong validation stamp could serve as that passport. It also extends a broader push in which the city has positioned itself as the place that solves tech’s final mile to market, and has openly courted Southeast Asia as a “super partner”.

At the launch, Secretary for Innovation, Technology and Industry Sun Dong said the government would keep backing AI through research investment, funding and infrastructure, with an emphasis on safety and compliance. HKPC chairman Sunny Tan framed the hub as taking FLAIR’s work in perception, autonomous decision-making, motion control and industrial applications out of the lab and into real operating environments.

What it means for Southeast Asia

Southeast Asia is not short of robotics ambition. Singapore leads the region in robot density, though e27 has argued that its robotics dominance is a warning sign dressed up as good news. Vietnam’s VinRobotics has taken its humanoids to the global stage, while Thai and Malaysian startups are raising rounds to move physical AI into malls and factories. What the region largely lacks is a shared, neutral venue where a startup can prove its machine works somewhere other than its own test bench.

If the Hong Kong hub opens up to regional players on fair terms, it could become a useful credential for SEA robotics firms that want to sell into China or use Chinese supply chains. If it turns mainly into a finishing school for mainland companies heading overseas, it becomes a competitor’s advantage instead.

Also Read: Hivebotics nets US$6M to take restroom-cleaning robot Abluo into volume production

Some scepticism is warranted. Fifteen partners is a modest start. “Alignment with international standards” is a phrase that sounds reassuring and commits to very little. The China Daily Hong Kong coverage echoed the official line that the centre will speed up the move from research to industry, but that is a stated goal, not an outcome.

The real test is simpler and harder. Will the trials produce benchmarks other people trust and can repeat, and deployments that outlive the ribbon-cutting? Robots are good at repeating the same task. The hub now has to show it can repeatedly turn pilots into real deployments.

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Singapore’s office workers answer a 10.47pm message within 90 seconds to prove their commitment. Their bosses barely notice.

The Jobstreet by SEEK Singapore Workplace Culture Study 2026, which surveyed 600 employees and jobseekers and 200 hiring decision makers, finds that 63% of staff signal dedication by replying fast, a behaviour only 39% of employers value. Some 52% stay reachable after hours; just 18% of employers rate it. What employers actually want is initiative and outcomes (49%).

The anxiety behind this is imported. AI and automation, followed by inflation and the cost of living, top both sides’ lists of workplace pressures. Employees fear for pay and job security; employers worry about AI’s impact on teams and restructuring towards leaner headcounts. That loop turns permanent availability into cheap insurance against the next round of cuts.

The payout is close to nil. Some 62% say always-on working has done nothing for their career, and 63% of those under pressure report lower energy. Yet 48% of employers who expect it have no plans to add support, and budgets favour AI training (34%) over wellbeing (14%) and manager development (12%). Until employers decide when staff may switch off, the late-night reply keeps costing workers dearly.

REGIONAL

SEA fintech funding triples to US$2.3B as deal count nearly halves: Four US$100M-plus rounds took 86% of capital, led by Ant International’s US$1.2B Series A. Seed funding fell 46% to US$53.3M, Singapore firms raised US$1.9B, and the region logged no fintech IPOs, per Tracxn.

Salary Hero raises US$7.6M Series A to take on Malaysia’s loan sharks: Cento Ventures led the round for the Bangkok-based financial health platform, joined by Kairous Capital and M Venture Partners. Salary Hero has also expanded its credit facility to US$10M with regional banks and lenders.

Parallel Loop nets US$6.6M to feed enterprise AI the context it lacks: Founders Yujun Chean and Prateek Jogani previously built Vouch Insurtech, parent of Thai insurtech FairDee, which raised a US$755,000 seed round in 2018. Eight years on, they return with a bigger cheque in a far more crowded field.

Antares Ventures passes US$50M for debut deep-tech fund, eyes US$100M: Family offices and corporate investors from Southeast Asia, Japan and Korea backed the second close. Fund I has already deployed about US$27M across nine companies, including Singapore’s VFlowTech, spanning energy, compute, industry and urban infrastructure.

TalentHero, DeeMoney form Thai JV to link hiring, payroll and payments: The Singapore-headquartered firm, co-founded by Oliver Lewis and James Miles, targets the post-hire grind of local entities, compliance and payroll, plus the cross-border money transfers that slow companies expanding into Thailand.

85% of Singapore employers expect staff to be always on: Yet half of employees say they receive no organisational support, against 22% of employers who admit offering none. Always-on working rarely pays off: 62% of staff see no difference to their career progression.

Malaysia’s VentureTECH backs biosimilar maker and Sabah agritech firm: Hanan Medicare is moving into biosimilars, including insulin, while AgriData Portal runs a seed-to-market model for smallholders. The AgriData deal is the government-backed investor’s first Sabah bet, aligned with PuTERA35.

Cashku adds Muamalat Invest Shariah funds, including private credit: The Malaysian platform offers sukuk, equities, gold and money market funds with no sales charges. Malaysia’s Islamic capital market grew 4.31% to US$660B in 2025, about 63% of the domestic capital market.

Partior and Bahrain’s NBB study putting the dinar on its rails: The Singapore blockchain settlement network could gain NBB as a dinar settlement bank, but the MoU commits only to feasibility work. Neither side disclosed a live service, a launch date or financial terms.

Beenext, Lotus lead US$2M pre-seed for AI search startup Miracly: Miracly, from Swedish home decor operator The Wild Ventures, tracks brand visibility on AI platforms. Acclime and Pixi Beauty are early customers, and it faces rivals such as Profound and AthenaHQ in AI search optimisation.

INTERVIEWS & FEATURES

Manus’s US$500M round puts the AI startup back in Chinese hands: Boyu Capital and IDG Capital led the raise, months after Beijing ordered Meta’s US$2B acquisition unwound. The lesson for SEA investors: regulatory exposure follows founders and code, not the registered address.

JFrog’s Sunny Rao: tokens are the wrong yardstick for AI agents: Rao once sold the IVR and chatbot automation wave that left customers trapped in looping phone trees. He warns that enterprises measuring AI agents by token use risk repeating that mistake.

Six wallets are replacing cash-on-delivery across Southeast Asia: Cash-on-delivery, long the default where card ownership was thin, once made up about half of e-commerce. Shoppers are finally abandoning it, but each market is choosing differently, fragmenting checkout for merchants.

Employers buy AI tools while their managers are left behind: Jobstreet by SEEK finds 37% of Singapore employees quietly draw their own boundaries to cope with pressure. Employers, meanwhile, rank manager development near the bottom of their investment list, at 12%.

Auto finance loses buyers in gaps that AI agents could close: Up to 80% of SEA cars are bought on credit, yet only about 10% of prospects complete financing, X Star’s Shawn Yang told AIMCONNECT 2026. Delegates ranked connectivity across institutions first as the fix.

INTERNATIONAL

Netflix cuts about 1,000 jobs as YouTube and TikTok eat into viewing: The roughly 6% cut falls mostly on product, tech, legal and HR teams. It follows Netflix losing the Warner Bros. Discovery bidding war to Paramount Skydance earlier this year.

US EV sales grow for a third straight quarter after tax credits end: EVs took 6.1% of the US market, per Cox Automotive, led by Toyota, Rivian and Subaru. Tesla’s sales fell 20% year-on-year, though it still sold over half of all EVs.

Amazon’s Panos Panay tells founders to fail, then harvest the lessons: Panay cited Microsoft’s Surface RT, which triggered a nearly US$1B write-down, as proof that failures stem from decisions made years earlier. His advice: adjust course by 30 degrees, not 180.

CYBERSECURITY

Singapore wants Google’s AI to stop scams inside the phone: Google unveiled two initiatives with the Singapore Government, shifting part of the anti-scam fight onto users’ devices, away from police operations centres, bank back offices and platform blocking rules.

Spyware makers turned online ads into a zero-click hacking pipeline: Citizen Lab says Israeli firm Discover-Tech let Candiru and Bindecy target victims through ad networks. One campaign hit at least 45 computers at Al Jazeera; exposed bidding records show ads reached military devices.

FBI arrests OpenAI staffer over hidden device in executive boardroom: Prosecutors charged Saudi national Abdulrahman Alfozan with intercepting oral communications after a device turned up in a TV’s USB port. OpenAI says it has no sign of stolen weights or customer data.

Ping An Digital Bank reports 96% deepfake detection in HKMA sandbox: Built with OneConnect, the platform checks customer selfies for forged faces during verification. The bank published no methodology or false-positive rates, and gave no deployment date beyond the trial.

SEMICONDUCTOR

SK Hynix’s Solidigm ties US fab plans to China equipment approvals: Reuters reports Solidigm wants more US tools for its Dalian plant while weighing a NAND factory in upstate New York. The unit is reportedly eyeing a US$10B IPO in 2027.

Applied Materials opens AI chip R&D hub with TSMC, Intel, Samsung: The Sunnyvale centre houses nearly four acres of cleanroom, and Applied expects capital spending of about US$5B over time. Micron, SK hynix and five US universities also joined, but the company gave no timeline or spending breakdown.

Cerebras CEO says AI doomsayers are drowning out the benefits: Andrew Feldman told TechCrunch Disrupt the industry also failed to engage local communities over US data centres, fuelling NIMBY pushback, while countries such as Brazil, Finland and Mexico welcome the buildouts.

Japan to invest up to US$21B in two GlobalFoundries fabs in New York: GlobalFoundries will operate the plants, jointly owned by Washington and Japanese interests. The deal forms part of Japan’s US$550B US investment pledge, made in return for US tariffs on Japanese imports falling to 15% from at least 25%.

AI

Anthropic’s Singapore MOU puts AI safety testing ahead of reach: Opening its fifth APAC office, Anthropic counts GovTech, DBS, GIC, Grab and Sea as users. The MOU carries no investment figure or headcount, and Washington still holds the off switch on US frontier models.

Sea Labs gets Google’s frontier models before February pilots report: Google AI Futures Fund calls Sea Labs its first external lab partner, but no money, equity or milestones were disclosed. Sea cut fourth-quarter 2025 R&D spending 7.8% as revenue rose 38.4%.

Singapore bets AI agent assurance can become its next industry: IMDA unveiled new assurance measures for AI agents, reflecting regulators’ shift in focus from software that chats to software that acts, where a wrong refund or misdirected email becomes a liability.

Singtel, IMDA offer 10,000 SMEs free AI-ready document management: SMEs get six months of free access to Singtel’s SPACE plus workshops, aimed at organising messy business data first. Neither party disclosed sign-ups or measured productivity gains.

Disney offers US$20M for tech Google licensed for US$2.7B: Both deals cover a licence to Character.ai‘s technology, marking a fall of over 99% in just over two years. The chatbot startup has since filed for Chapter 11 bankruptcy.

Hong Kong opens embodied AI hub to test robots in real settings: HKPC and FLAIR have signed seven technology partners and eight international scenario partners across manufacturing, logistics and retail. Hong Kong wants the hub to bridge mainland robotics and global markets.

THOUGHT LEADERSHIP

SEA’s funding winter is real, but its builders have not stopped: Faheem Aizat Kamsan notes that zero regional PE funds closed in the first half of 2026. Yet he argues capital fleeing the region is not the same as founders downing tools.

Indonesian fintechs paid more for ASEAN expansion than they planned: Bobby Yulandika Putra revisits the 2018–2022 cohort, from Investree to Modalku, that pushed beyond Indonesia and hit a structural cost few had priced in.

DEFA lowers the cost of entry, but architecture decides cost of scale: Fathhi Mohamed warns that platforms in four ASEAN markets often run four data stores, four KYC flows and four sets of legal entities, so every new market multiplies complexity.

Singapore’s growth upgrade helps some sectors far more than others: MTI lifted its 2026 forecast from 2–4% to 4.5–5.5% in August. Boris Dzhingarov urges founders to read the sector breakdown, not the headline, before planning.

Founders now judge investors on what comes beyond the cheque: Chris Chen opens with a founder weighing two term sheets in one week, including a reasonable US$1.5M offer from a well-known regional VC, to show what founders actually buy.

Decide which decision predictive AI should change before buying tools: Daniel Tan argues startups begin too early with models, data stacks and dashboards. The first question is what decision a prediction changes; without that answer, he suggests, the rest is premature.

AI saves hours, but teams simply fill them with more work: Rubyni Karun warns that as organisations accelerate AI spending, time saved by automation simply gets refilled with tasks, leaving human capacity as stretched as before.

Audiences warm to ads as marketers lose faith in their own metrics: Prof. Aleks Farseev draws on Kantar’s Media Reactions study, built on interviews with 800-plus senior marketers, to ask why green dashboards cannot show teams what worked ahead of 2027 planning.

Human rights are getting lost in the ‘S’ of ESG: Adam Goulston notes the 2011 UN Guiding Principles have long required companies to find, prevent and repair human rights harms, yet the social pillar still dilutes or ignores them.

The West buys longevity scans while SEA still pays cash for basics: Americans pay up to US$2,499 for full-body MRIs, Maria Gaitanidou notes. In the Philippines, many families delay check-ups until symptoms turn serious, and public hospital beds are often full.

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For two decades, marketers obsessed over a single question: where do we rank on Google? A growing number now ask a stranger one: what does ChatGPT say about us when we are not in the room?

The Wild Ventures, the Swedish-founded company behind home decor brand Wild Palace, is betting that question will turn into a budget line. On October 14, it launched Miracly, an AI marketing platform, after raising a US$2 million pre-seed round.

Also Read: The EU called ChatGPT a search engine. SEA’s AI startups should worry about what comes next

The round was led by Singapore-based BEENEXT and Lotus, with participation from a Swedish family office. Existing backers include Stefan Lindeberg, founder of Nordic VC firm Creandum, and Alex Bouaziz, co-founder and CEO of payroll and HR unicorn Deel. The company did not disclose a valuation.

From wallpaper to software

The launch marks a notable turn for a company that, until recently, described itself as a house of brands. When The Wild Ventures announced itself in April 2025, it closed a US$750,000 angel round at a post-money valuation of around US$7 million. The plan then was to use AI and sharp branding to shake up “stale but big” categories such as wallpaper, pet accessories and paper packaging, through brands including Wild Palace, Poositive Pets and Future Paper.

Miracly is a different animal. It is business software, sold to marketing teams rather than to shoppers.

The founding team helps explain the pivot, or at least the extension. Co-founders Arvid Lithander and Shannon Cullum come from advertising agencies including Saatchi & Saatchi, Wieden+Kennedy and MullenLowe, and are joined by Bjorn Bergstrom and Malin Renström. People who have spent careers fighting for share of voice tend to notice early when the arena moves.

The obvious sceptic’s question is whether a startup can build consumer brands and an enterprise software product at the same time on a pre-seed budget. The generous reading is that Wild Palace doubles as Miracly’s test lab: a live brand on which to try out AI visibility tactics before selling them to others. The company will need to show which reading is closer to the truth.

What Miracly actually does

Miracly said its software helps marketing teams track how brands appear on AI platforms and manage work across channels. In plain terms, it watches how chatbots and AI assistants describe and recommend a brand, then helps the team act on what it finds.

That second half matters. Monitoring alone is quickly becoming a commodity. The harder problem is turning “the chatbot thinks our rival is cheaper” into a coordinated response across a website, PR, social media and paid campaigns, without adding another tool to an already bloated.

Also Read: How earned media drives AI search visibility in ASEAN

Early customers include Acclime, an Asia-focused corporate services firm, and Pixi Beauty. The pairing is telling: one sells complex professional services, where buyers increasingly ask AI tools to compare providers; the other sells skincare, where an AI-generated product recommendation can make or break a purchase.

A crowded new channel

AI search is changing how brands are discovered online, handing marketers yet another channel to monitor and influence. When a user asks an assistant for the best accounting firm in Singapore or a moisturiser for humid weather, the answer usually arrives as a single synthesised reply rather than a page of links. A brand that is absent from that reply barely exists for that customer. It is why marketers have started asking what ChatGPT is saying behind their backs.

For Southeast Asia, the stakes are arguably higher. Discovery in the region is fragmented across languages, super apps and social commerce, and most brands already juggle multiple channels on thin teams. Adding AI answer engines to that mix is not optional, but it is not cheap either.

Miracly is far from alone. New York-based Profound is the category’s heavyweight: it raised a US$96 million Series C at a US$1 billion valuation in February, led by Lightspeed Venture Partners with Sequoia Capital and Kleiner Perkins participating, and serves more than 700 enterprise customers. Industry reports say it followed that with a US$180 million Series D at a US$1.8 billion valuation in September. Y Combinator-backed AthenaHQ, founded by former Google Search engineer Andrew Yan and ex-ServiceNow engineer Alan Yao, came out of stealth in 2025 with US$2.2 million in seed funding and pitches a cheaper, self-serve alternative.

Against that backdrop, US$2 million is a modest war chest. Profound has already moved from tracking into agents that execute marketing tasks, which is precisely the “manage work across channels” territory Miracly is claiming. Competing on features with a company that had raised more than 75 times as much even before its latest round is a losing game. Miracly’s better bet may be geography and price: mid-market brands and Asian firms that Silicon Valley’s enterprise-first players are not prioritising.

That may also be what BEENEXT, which has a long record of backing early-stage startups across Asia, sees in the deal.

The question nobody has answered

There is a deeper uncertainty hanging over the whole category. Search engine optimisation worked because Google published rules, however vague, and the results could be measured. AI models are less predictable: answers shift with model updates, phrasing and even the user’s location. Selling the ability to “influence” those answers requires proof that customers can repeat, not just a dashboard of anecdotes.

Also Read: AI didn’t replace Southeast Asia’s marketing agencies, it repriced them

And as AI platforms experiment with paid placements, the organic window that tools such as Miracly promise to optimise could narrow. If AI search becomes another pay-to-play channel, the winners may be ad buyers, not optimisers.

For now, marketers are paying to find out what the machines think of them. As AI agents rewrite the growth marketing playbook, Miracly’s challenge is to prove that knowing the answer is only half the job, and that it can deliver the other half.

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