In a livestream on X and YouTube, the company’s embodied AI model and self-developed High-Performance 6-Axis Robot Arm autonomously identified, picked, reoriented, and fed highly variable parcels into a live sorting workflow, achieving 1,816 parcels per hour with over 98% accuracy.

SHENZHEN, China, Aug. 13, 2026 /PRNewswire/ — X Square Robot, an embodied AI company building general-purpose robots and foundation models for real-world environments, has demonstrated a system that automates one of the hardest front-end jobs in logistics: moving parcels from the messy piles left by truck unloading onto the sorting line. In a livestream on X and YouTube on August 12, the company’s proprietary WALL-B AI foundation model worked with its self-developed High-Performance 6-Axis Robot Arm to identify, pick, organize, and feed parcels one by one onto a conveyor for scanning and automated sorting.

Parcel induction is a highly labor-intensive “3D” task — dull, dirty, and dangerous, with operators facing high labor demand, turnover, and challenges in staffing night shifts and seasonal peaks. As labor costs rise, automation that can operate continuously offers a potential path to improving productivity and ROI.

This is the step where lab demos usually fall short. A parcel pile changes with every pick. Boxes and soft packages overlap, labels point the wrong way, and the best grasping surface is often buried. At the unloading dock, that messiness makes parcel induction a bottleneck for throughput and one of the most labor-intensive stages of sorting.

“The question in logistics automation is not whether a robot can make one clean pick,” said Wang Qian, Founder and CEO of X Square Robot. “It is whether it keeps making good decisions as the pile changes, recovers when something goes wrong, and keeps the rest of the operation moving. We designed the automation around the work itself, not around an idealized environment.”

At the core of this capability is X Square Robot’s proprietary embodied AI foundation model, WALL-B. In the live demonstration, the model showed how this learned understanding translates into real-time action: assessing each parcel and its surroundings, determining how it should be handled, and adapting the manipulation strategy as conditions change. Rather than relying on manually programmed rules for every parcel type, WALL-B enables the robot to respond to unexpected situations in the physical world — as demonstrated when its 6-axis arm dynamically intervened to rescue a misrouted parcel.

Turning these decisions into physical action is the High-Performance 6-Axis Robot Arm. Its multi-angle range of motion allows the system to approach packages from different directions to pick, flip, flatten and reposition them. Before a parcel reaches the conveyor, the arm can turn labels toward the scanner, smooth soft packaging and square up boxes. These may seem like small adjustments, but they can improve barcode scanning and reduce the returns and manual handling caused by poorly positioned packages.

Rather than asking one robot to perform every task, X Square Robot takes a purpose-built approach, designing the system around the specific demands of parcel induction. The result is a focused combination of speed, accuracy, and cost, matching the hardware and AI to the workflow rather than forcing the workflow to fit the robot.

For X Square Robot, the demonstration is ultimately about more than moving parcels. It reflects the company’s broader vision for embodied intelligence: making AI practical in the real world and enabling robots to perceive, reason, and act in complex physical environments.

About X Square Robot

X Square Robot develops general-purpose embodied intelligence robots with high-precision manipulation capabilities. The company is building foundation models for the physical world, integrating models, robotic hardware and scalable, model-driven high-quality data pipeline system. Its robots are designed to perceive, reason and act across long-horizon tasks in home and everyday environments, research and education, logistics and warehousing, and industrial operations.

For more information, visit https://x2robot.com/.

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SOURCE X Square Robot

The initial participating cohorts recorded a 50% increase in quarterly revenue, doubled their weekly customer appointments and achieved an average 35% improvement in competency scores

SINGAPORE, Aug. 13, 2026 /PRNewswire/ — enParadigm, an immersive AI talent solutions company, has rolled out its AI-powered capability-building intervention for one of Singapore’s top 3 banks. Following the initial success with the bank, the intervention is now being extended to more than 900 wealth advisers across APAC.

The intervention helped wealth advisers strengthen critical customer engagement skills through realistic simulations, repeated practice and immediate behavioural feedback. Among the initial participating cohorts, weekly customer appointments doubled, competency scores improved by an average of 35% and quarterly revenue per wealth advisor increased by 50%.

Ministry of Manpower data shows that while 28.5% of private-sector establishments had begun adopting AI, only 3.8% had integrated it into core processes. This reflects the wider shift Singapore is now encouraging, from AI experimentation to meaningful application within business processes. The intervention demonstrates what this can look like in practice, with AI embedded into workforce development and linked to measurable improvements in capability, workplace performance, and business outcomes.

Turning AI-powered practice into measurable performance improvement

The intervention was delivered through enParadigm’s Catalyx, an AI-powered experiential learning and talent intelligence platform. It focused on a defined business challenge: helping advisers handle important customer conversations more confidently and consistently. Through AI-powered simulations, advisers interacted with virtual customer personas that responded dynamically to their pitch, asked tough questions and raised objections like a real customer would. The platform adapted each conversation based on the adviser’s responses, assessed specific behaviours in real time and provided immediate, personalised feedback. Advisers could then repeat challenging scenarios and refine their approach before applying the skills in live customer conversations.

“The strongest enterprise AI applications begin with a clearly defined business outcome, rather than with the technology itself. In this intervention, we focused on the behaviours that influence the quality of customer conversations and created a safe and scalable environment in which advisers could practise, receive feedback and continuously improve. The results demonstrate how capability building can be connected more directly to business performance with the help of the right tools,” said Jash Bajaj, Business Director and Head of APAC, enParadigm.

What other organisations can replicate

The intervention highlighted that a key constraint was not access to sales knowledge, but limited access to consistent opportunities to practice, receive timely feedback and benefit from just-in-time coaching. Advisers previously waited up to three weeks for supervisor-led coaching as each individual supervisor was responsible for as many as 10 employees.

Giving advisers an on-demand environment for repeated practice reduced their dependence on scheduled coaching sessions. It also gave managers greater visibility into individual capability gaps, allowing subsequent human coaching to focus on specific behaviours rather than broad or generic feedback.

This journey suggests that organisations can improve the effectiveness of AI-led capability initiatives by starting with a defined business outcome rather than broad technology adoption.

They can then identify the workplace capabilities most closely linked to that outcome, create realistic opportunities for employees to practise those capabilities and measure progress on role-specific behavior, KPIs and commercial performance. This broader evidence chain allows organisations to assess not only whether employees completed an intervention, but whether their behaviour and results changed afterwards.

“Over 16 years of building contextual simulations, we have seen technology transform dramatically, but the fundamentals of improving workplace performance remain unchanged. AI should not be adopted simply because a new tool is available. It must address a clearly identified performance challenge, enable measurable behavioural change and demonstrate impact through workplace outcomes. This provides a stronger basis for scaling AI investments and improving workforce productivity,” said John Cherian, CEO and Co-founder of enParadigm.

The approach can extend beyond wealth advisory and sales, with AI-powered simulations being applied to roles in which business outcomes depend on the quality and consistency of human interactions, including people management, recruitment, customer service, negotiation, healthcare, hospitality and frontline operations.

Learn more at https://www.enparadigm.com/catalyx-talent-intelligence-platform.

– END –

About enParadigm

enParadigm is a leading immersive AI talent solutions company helping organizations improve workforce productivity across the hire-to-grow lifecycle. At the core of its offerings is Catalyx, an AI-powered platform that enables organizations to assess talent, identify skill gaps, and build role-specific capabilities through realistic workplace simulations, personalized feedback, and performance analytics. Its broader portfolio includes Compass, which delivers facilitated and blended capability-building journeys, and Cockpit, an AI experience builder used to create customized talent solutions and track learner progress.

With more than 16 years of experience across 1000+ global enterprises in financial services, consumer goods, technology, healthcare, automotive, and retail industries, enParadigm has supported the development of more than one million professionals worldwide.

Website: www.enparadigm.com

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SOURCE enParadigm

APIA, Samoa, Aug. 13, 2026 /PRNewswire/ — HTX Ventures, the global investment arm of HTX, has released a new report titled Open Infrastructure, Closed Financial Rails: Open USD, Revenue Redistribution, and Participant Governance, examining the shifts underway in stablecoin revenue distribution, channel relationships, and governance following the June 30, 2026 unveiling of Open USD (OUSD).

The report finds that while blockchain technology has established open, global, and programmable technical infrastructure, the industry’s next phase will be determined by how participants contest control rights and the allocation of economic benefits. The technical layer has opened; the economic layer is only beginning to.

Closed Economic Structures atop Open Technology

Stablecoins have moved from settlement tools within crypto trading into instruments for cross-border payments, corporate treasury management, and institutional back-office clearing. Visa’s stablecoin settlement pilot reached an annualized run rate of approximately $7 billion by April 2026 across nine blockchains, while Swift, the Canton Network, Fnality, and Project Agorá explore how tokenized deposits and central bank money can settle within shared environments.

Economic rights, however, remain distributed along established lines. Issuers mint stablecoins against user dollars and allocate reserves into cash and short-term Treasuries, with reserve yields accruing solely to them. Yet the system depends on exchanges and wallets for user access, payment companies to connect merchants, banks for fiat on/off-ramps, custodians for reserves, and market makers for secondary depth. These institutions bear integration, compliance, and liquidity costs, and currently capture revenue mainly through bilateral commercial agreements — where bargaining power depends heavily on their own user scale.

Three Institutional Shifts in OUSD’s Design

Under Open Standard’s framework, enterprises can mint and redeem OUSD free of charge and without volume limits. Open Standard charges a small management fee, with the remaining reserve yields earmarked for partners who adopt and promote OUSD, as well as select partners planning to join its board of directors. The published partner roster exceeds 140 entities, including Visa, Mastercard, American Express, Stripe, Coinbase, BlackRock, and BNY.

HTX Ventures breaks the design into three shifts:

From fee-based access to subsidized distribution, using reserve yields to offset the genuinely expensive investments in customer acquisition, liquidity, regional compliance, and fiat rails;From bilateral negotiations to network-wide revenue sharing, bringing mid-sized payment companies, regional banks, and vertical wallets into a unified framework where partners share revenue based on contribution;From issuer governance to participant governance, giving institutions that bear business and regulatory responsibility a voice in rule-making.

OUSD is slated for launch later in 2026. Notably, it shares the OUSD code with Origin Protocol’s Origin Dollar, launched in 2020, though the two are distinct products.

Execution Details Will Determine Whether the Model Holds

According to HTX Ventures, the model’s viability depends on several specific mechanisms. Revenue-sharing rules directly determine who captures value: allocation by balance favors institutions with greater capital resources, while allocation by transaction volume can be distorted by internal transfers that generate activity without real payments. A workable mechanism would weigh balance retention, actual payments, new customers, and regional compliance investments together. The governance arrangement likewise rests on what the board can actually decide, not on how many institutions appear on the roster.

More fundamentally, a considerable distance separates joining a consortium from migrating core business. What ultimately determines network value is stable balances, real payment volume, market-making depth, and smooth redemptions.

Value Chain Revenue Faces Redistribution

If revenue-sharing models generate sustained payment volumes, the room for issuers to retain the full reserve yield spread will narrow. Exchanges, wallets, and payment companies that control access to users, liquidity, and payment use cases may shift from distribution tools to participants in revenue-sharing and governance arrangements. For banks the impact is two-sided — deposits and correspondent banking revenue may erode, but stablecoins still require reserve custody, fiat on/off-ramps, and FX liquidity. Card networks face limited direct impact, given their role in authorization, fraud management, and merchant acceptance. Across clearing, custody, and data services, fees based on proprietary records may decline while services tied to security and liability expand.

The Next Dimension of Competition

Open USD raises a question that extends beyond stablecoins: when banks, payment processors, exchanges, asset managers, and custodians provide the underlying assets, customer relationships, liquidity, and compliance capabilities, how will the value chain distribute profits and control?

Such shifts are most likely in middle- and back-office infrastructure, where multiple institutions are required and no single platform can independently provide customer reach, regional licensing, fiat rails, and counterparty networks. Institutions need shared infrastructure, yet remain reluctant to cede core operations, client data, and risk authority to a direct competitor. Consortium governance and revenue sharing are therefore not ideological commitments to decentralization, but pragmatic commercial prerequisites for cross-institutional networks.

HTX Ventures notes that along this trajectory, stablecoin competition will move beyond issuance scale and on-chain liquidity toward who contributes network value, who shares infrastructure revenue, who retains customers and data, and who sets operating rules. The next generation of financial infrastructure need not be fully decentralized; more likely, it evolves from single-company control toward networks where regulated participants connect, share returns, and govern major decisions through tiered arrangements. As a research and investment firm with a long-standing focus on payment infrastructure and institutional settlement networks, HTX Ventures will continue tracking how this redistribution of revenue, customers, and rule-setting shapes the industry’s direction.

About HTX Ventures

HTX Ventures is the global investment arm of HTX, integrating investment, incubation, and research to identify and discover the best and most innovative projects in the market. Visit us here.

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SOURCE HTX Ventures