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Sunrate and Mastercard Release White Paper on Agentic AI and the Future of B2B Global Payments

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SHANGHAI, July 24, 2026 /PRNewswire/ — Sunrate, the global payment and treasury management platform, and Mastercard, a global technology company in the payments industry, unveiled a joint white paper, Beyond Automation: Defining Agentic Global Payments, at the 2026 World Artificial Intelligence Conference (WAIC).

Among the first reports in the payments industry to examine the impact of Agentic AI on B2B cross-border payments, the white paper provides a comprehensive framework for understanding how AI agents are reshaping enterprise payment operations. It proposes that cross-border payments are evolving beyond digitisation and automation into a new stage: Autonomy—where AI agents with reasoning, planning, and execution capabilities can independently orchestrate and optimise end-to-end payment and treasury workflows within defined governance frameworks.

As businesses expand across borders, B2B cross-border payments continue to be constrained by fragmented workflows, disconnected systems, foreign exchange inefficiencies, rising compliance requirements, and complex reconciliation processes. While traditional automation improves individual tasks, the white paper demonstrates that Agentic AI represents a fundamental shift by enabling intelligent agents to coordinate entire payment journeys across systems, counterparties, and approval workflows.

Drawing on Sunrate’s global payment infrastructure and AI-native product capabilities, together with Mastercard’s expertise in secure payment networks and data intelligence, the white paper defines Agentic Global Payments — a new category of AI-native global payment infrastructure built to automate and manage complex enterprise workflows.

The report identifies 16 major pain points across the B2B payment lifecycle and outlines 13 high-value AI use cases spanning supplier onboarding, accounts payable and receivable, virtual commercial cards, payment routing, foreign exchange management, compliance screening, fraud detection, reconciliation, and conversational operational support. It also demonstrates how AI agents can automate complex workflows—from extracting information across multiple document formats and conducting compliance checks to initiating payments, optimising FX execution, and completing reconciliation—while operating within enterprise governance and control frameworks.

The white paper further highlights that trusted adoption of agentic payments depends on more than technological capability. It identifies governance, transparency, security, and ecosystem collaboration as essential foundations for enterprise deployment, supported by frameworks such as Know Your Agent (KYA), payment tokenisation, auditability, and cross-industry interoperability.

Sunrate.AI portfolio currently includes the Payment Agent, FX Agent, Compliance Agent, Onboarding Agent, and Chat Agent, designed to help enterprises automate and optimise critical payment and treasury processes while maintaining compliance and operational control.

Mastercard has also been actively building the foundations for trusted agentic commerce – combining AI capabilities with verifiable authorisation, clear accountability and proven payments security. Its work in this area, including Agent Pay (alongside Agent Pay for Machines) and Verifiable Intent, are proof points in how Mastercard is enabling AI to participate in commerce safely and transparently. 

“Our mission is to make global payments seamless, compliant, and intelligent,” said Paul Meng, Co-founder and CEO of Sunrate. “As businesses continue expanding internationally, AI agents will fundamentally reshape how enterprises manage global payments—enabling smoother capital flows, reducing operational friction, and embedding real-time intelligence into every payment decision. This white paper represents an important step in helping the industry understand how Agentic AI can be deployed responsibly at enterprise scale.”

“Agentic commerce is changing how businesses make and execute payment decisions, but speed without accountability creates new categories of risk,” said Anouska Ladds, Executive Vice President, Commercial & New Payment Flows, Asia Pacific, Mastercard. “As AI starts to act on behalf of businesses, autonomous payment decisions need a clear, auditable chain of identity, intent and action. That’s what allows organisations to delegate with genuine confidence — and what will determine whether agentic commerce scales past pilots.”

Released under WAIC 2026’s theme, “Intelligent Partners, Co-creating the Future,” the white paper provides business leaders with practical guidance on adopting AI-driven payment capabilities, covering implementation approaches, governance considerations, and real-world enterprise applications.

By combining Sunrate’s expertise in global payments and treasury management with Mastercard’s trusted payment infrastructure and network capabilities, the collaboration reflects a shared commitment to accelerating the next generation of intelligent, secure, and autonomous B2B global payments.

Click here to check the white paper.

About Sunrate

Sunrate is a leading global payment and treasury management platform for businesses worldwide. Founded in 2016, Sunrate has enabled companies to operate and scale both locally and globally in 190+ countries and regions with its cutting-edge infrastructure, global network, and unified solutions.

Sunrate operates through offices across key markets, including Singapore, Kuala Lumpur, Jakarta, Hong Kong, Shanghai, and London. The company partners with the top global financial institutions, such as Citibank, Standard Chartered, Barclays, J.P. Morgan. Sunrate is also the principal member of Mastercard and Visa. To learn more about Sunrate, visit https://www.sunrate.com/.

About Mastercard

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. 

www.mastercard.com

SOURCE Sunrate

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BinBase Expands 2026 BIN Dataset with Instant Payout Intelligence for iGaming, Gambling, and Cross-Border Transfers

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BinBase updates its 2026 dataset with specialized Fast Funds, Visa Direct, and Mastercard MoneySend indicators to help iGaming operators and payout platforms execute seamless, instant card disbursements.

MIAMI, July 23, 2026 /PRNewswire-PRWeb/ — BinBase, a global provider of payment routing intelligence and card issuing data, has introduced specialized instant payout indicators as part of its upgraded 2026 BIN Database. Tailored for iGaming operators, online gambling platforms, crypto-to-fiat ramps, and payout aggregators, the updated dataset helps platform engineers streamline real-time card disbursements and Push-to-Card (P2C) transactions.

In high-velocity sectors such as online betting and gaming, instantaneous player payouts are a primary driver of customer retention. However, executing Push-to-Card transactions through protocols like Visa Direct and Mastercard MoneySend requires knowing whether the receiving card issuer supports Fast Funds for specific merchant category codes (MCCs). Attempting instant payouts on non-eligible cards leads to declined transactions, elevated processing fees, and poor user experiences.

The 2026 BinBase release solves this operational bottleneck by delivering dedicated attributes for real-time fund disbursements:

Fast Funds Eligibility: Granular indicators identifying domestic and cross-border Fast Funds support across global Visa and Mastercard ranges.Online Gambling Fast Funds (OG FF): Dedicated flags specifically identifying card ranges authorized to receive real-time gambling and betting payouts.Mastercard MoneySend & Visa Direct Indicators: Precise protocol compatibility markers (MS Ind & MT Ind) ensuring push transactions are routed only to eligible recipient cards.Direct Debit & Pull-Funds Support: Indicators for recurring collections and account-funding transactions.

“Player payouts in iGaming cannot wait for standard 2-to-3-day ACH settlements,” said a spokesperson for Damiko Inc. “By embedding our Fast Funds and Gambling FF flags into their payment engines, operators can instantly validate recipient cards before initiating a transfer, guaranteeing high success rates and instant liquidity for their users.”

Fintech engineers and payout architects can examine the full 29-field database schema and access a free 2026 sample dataset on GitHub.

To explore commercial licensing, bulk database downloads, or custom data feeds, visit BinBase at https://binbase.com.

About Damiko Inc

Damiko Inc is a US-based fintech data provider specializing in card issuer analytics, payment routing data, and global BIN database solutions. Operating through its flagship product, BinBase.com, the company supplies high-precision transaction intelligence to help merchants and payment facilitators worldwide optimize approval rates and mitigate processing fees.

Media Contact
Fedor Lavrikoff, BinBase, 1 7866133334, sales@binbase.com, www.binbase.com 

View original content:https://www.prweb.com/releases/binbase-expands-2026-bin-dataset-with-instant-payout-intelligence-for-igaming-gambling-and-cross-border-transfers-302829344.html

SOURCE BinBase

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Walnut Coding’s Young Coders Serve as ‘Instructors’ at Huawei Cloud Developer Training Camp

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Ages 8 and 15, students showcase AI-era project-building skills from concept to working application

BEIJING, July 23, 2026 /PRNewswire/ — Walnut Coding (the “Company”), a leading online platform for youth coding education, said two of its students – ages 8 and 15 – have joined the “instructor” lineup at Huawei Cloud Developer Training Camp, making them among the youngest “instructors” in the program’s history. The Company cites the pair as a prime example of how young learners can combine coding fundamentals with AI tools to turn ideas into working applications.

The two students, Bolin Du, 8, and Peiqi Gao, 15, built working applications using Huawei Cloud CodeArts, an AI coding assistant, then presented the projects to the training camp themselves – walking the audience through their design choices, technical builds, and debugging process.

The move lands at a moment when AI coding tools are forcing a rethink across the education sector. Tools that can generate functioning code from a plain-language prompt have undercut the traditional argument for teaching children to program – that they need the skill to build things themselves. Walnut Coding’s answer is that the more valuable skill now is judgment – knowing what problem to solve, breaking it into parts, and determining whether an AI’s output actually works.

Gao built a travel-planning application that generates routes, itineraries, and recommendations based on user input, handling the project end to end, from requirements and design through coding and debugging. Du, the younger of the two, built an interactive calendar application, using HTML for page structure, CSS for visual design, and JavaScript for interactive features. Both students then took on an instructor’s role at the camp, presenting their project goals and technical implementation to the audience – a step Walnut Coding says separated the work from a typical classroom assignment.

These were not classroom exercises but working projects, built and presented inside a professional developer-training environment. The experience demanded more from both students than simply producing something functional – they needed to articulate their reasoning, defend technical choices, and refine the final result under scrutiny. Their participation signals a broader shift underway in what youth coding education can deliver.

AI is making code generation easier, but it is also redrawing which skills actually matter. A student who relies only on one-click generation may get a rough prototype quickly, but still struggle to spot logical flaws, judge whether the output is reliable, or turn an abstract idea into a product that actually works. Students with programming foundations, by contrast, are better positioned to define requirements, evaluate what the AI produces, correct its errors, and treat the technology as a tool rather than a shortcut to lean on.

“AI can help children generate code faster, but it cannot decide for them what problem they should solve, nor can it make the final judgment about whether the result is truly effective,” said Pengxuan Zeng, founder and CEO of Walnut Coding. “What these two students demonstrated is not just coding technique, but the ability to define needs, break down tasks, verify outcomes, and turn an idea into a working product. That is why we believe young people still need to learn programming in the AI era.”

Walnut Coding structures its courses around that thesis, pairing student-led project work with teaching-assistant guidance and AI-assisted support. According to the Company, this data is continuously fed back into its systems to refine the personalization of AI-assisted feedback — a closed-loop process linking teaching, practice, feedback, and curriculum development.

The Company frames the payoffs less around producing professional software engineers than around a broader form of literacy. As AI continues to reshape how tasks get done, the ability to understand the technology, structure problems clearly and collaborate effectively with intelligent tools may prove one of the most durable skills a young learner can develop.

Walnut Coding says it plans to keep expanding opportunities for students to build practical projects, partner with industry technology platforms such as Huawei Cloud, and develop the core capabilities needed to build with technology in the AI era.

View original content:https://www.prnewswire.com/news-releases/walnut-codings-young-coders-serve-as-instructors-at-huawei-cloud-developer-training-camp-302833884.html

SOURCE Walnut Coding

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MOREH Showcases High-Performance LLM Inference on AMD GPUs at AMD Advancing AI 2026

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SAN FRANCISCO, July 23, 2026 /PRNewswire/ — Moreh, an AI infrastructure software company, led by CEO Gangwon Jo, participated in AMD Advancing AI 2026, AMD’s flagship annual AI event held in San Francisco on July 22–23 (local time), where it demonstrated its distributed inference solution, the MoAI Inference Framework, running on AMD GPUs.

At the event, Moreh presented a live demonstration of the GLM-5.1 large language model (LLM) powered by the MoAI Inference Framework on a system equipped with 32 AMD Instinct™ MI300X GPUs across four nodes. Visitors experienced the chatbot firsthand, evaluating its response speed and service quality while observing performance across a range of real-world use cases.

Unlike conventional demonstrations that simply run an AI model, Moreh’s showcase displayed key inference service metrics in real time, including GPU utilization, Tokens Per Second (TPS), Time To First Token (TTFT), and Time Per Output Token (TPOT). This enabled attendees to directly verify both inference performance and GPU resource efficiency in a production-like service environment.

Global AI industry leaders and enterprise customers attending the event expressed strong interest in the system’s fast response times and stable performance. In particular, the live deployment of the computationally demanding GLM-5.1 model on AMD GPUs at production-grade service levels received positive feedback from visitors.

Moreh’s MoAI Inference Framework is widely recognized as the world’s first commercially deployed distributed inference solution built for the AMD ecosystem. Its distributed inference and heterogeneous computing technologies are designed to dramatically reduce AI service costs, enabling broader adoption of AI worldwide. The technology addresses one of the industry’s biggest challenges-the rapidly rising infrastructure and service costs caused by increasingly larger AI models-by delivering a more efficient inference infrastructure.

Moreh CEO Gangwon Jo stated, “This event provided an opportunity for global customers to verify firsthand that top-tier inference performance can be achieved on AMD GPU environments,” and added “We will continue advancing our AI infrastructure software so enterprises can operate AI services as efficiently as possible, regardless of the underlying GPU platform.”

Moreh develops its own AI infrastructure engine and has expanded its end-to-end AI capabilities through its foundation LLM subsidiary, Motif Technologies, covering both AI infrastructure and foundation models. The company is also strengthening its presence in the global AI market through strategic partnerships with leading technology companies, including AMD and Tenstorrent.

View original content to download multimedia:https://www.prnewswire.com/news-releases/moreh-showcases-high-performance-llm-inference-on-amd-gpus-at-amd-advancing-ai-2026-302833887.html

SOURCE Moreh

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