Airwallex hits $6.2bn valuation
Airwallex has raised $300 million in a Series F funding round that values the payments firm at $6.2 billion.
0
Visa Ventures joined as a strategic investor, with Square Peg, DST Global, Lone Pine Capital, Blackbird, Airtree, and Salesforce Ventures also participating in the round, which includes $150 million in secondary share sales.
Founded in Australia in 2015, Airwallex provides bill payments for companies that operate globally, expense management and multi-currency debit cards for its 150,000 business clients.
The firm has been expanding fast, hitting $720 million in annualised revenue in March 2025, up 90% year-over-year.
Founded in Singapore, it has been pushing into the Americas and Emea, recently moving into a permanent US headquarters in San Francisco and opening offices in New York, Toronto and Paris.
The funding will be used to continue expanding its financial infrastructure into new markets including Japan, Korea, the UAE, and Latin America, and to accelerate go-to-market efforts in Europe, North America, and South East Asia.
Jack Zhang, CEO, Airwallex, says: 'Too many businesses are held back by legacy infrastructure that's slow, costly, and fragmented. At Airwallex, we're building a new foundation for the global economy - one that's fast, seamless, and built for scale."
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
-and-Elon-Musk.jpeg%3Fwidth%3D1200%26height%3D800%26crop%3D1200%3A800&w=3840&q=100)
The Independent
19 minutes ago
- The Independent
Republicans call for an end to Trump-Musk feud: ‘I hope it doesn't distract us'
As the Republican Party anticipates potential fallout from Donald Trump's public dispute with Elon Musk, prominent lawmakers and conservative voices are calling for reconciliation, wary of the repercussions of a sustained conflict. The animosity between the two figures could pose challenges for the Republican agenda, particularly concerning tax and border spending legislation championed by Trump but criticised by Musk. Representative Dan Newhouse, a Republican from Washington, expressed hope that the disagreement would not impede progress on critical tasks. Speaking on the matter, Newhouse said: "I hope it doesn't distract us from getting the job done that we need to. I think that it will boil over and they'll mend fences." As of Friday afternoon, Musk had refrained from further engagement, focusing instead on promoting his various companies on social media. Senator Ted Cruz, a Texas Republican, voiced optimism for a resolution, telling Fox News that, "I hope that both of them come back together because when the two of them are working together, we'll get a lot more done for America than when they're at cross purposes". Sen. Mike Lee, a Republican from Utah, sounded almost pained on social media as Trump and Musk volleyed insults at each other, sharing a photo composite of the two men and writing, "But … I really like both of them.' 'Who else really wants @elonmusk and @realDonaldTrump to reconcile?' Lee posted, later adding: 'Repost if you agree that the world is a better place with the Trump-Musk bromance fully intact.' So far, the feud between Trump and Musk is probably best described as a moving target, with plenty of opportunities for escalation or detente. One person familiar with the president's thinking said Musk wants to speak with Trump, but that the president doesn't want to do it – or at least do it on Friday. The person requested anonymity to disclose private matters. In a series of conversations with television anchors Friday morning, Trump showed no interest in burying the hatchet. Asked on ABC News about reports of a potential call between him and Musk, the president responded: 'You mean the man who has lost his mind?' Trump added in the ABC interview that he was 'not particularly' interested in talking to Musk at the moment. Still, others remained hopeful that it all would blow over. 'I grew up playing hockey and there wasn't a single day that we played hockey or basketball or football or baseball, whatever we were playing, where we didn't fight. And then we'd fight, then we'd become friends again,' Hannity said on his show Thursday night. Acknowledging that it 'got personal very quick,' Hannity nonetheless added that the rift was 'just a major policy difference.' House Speaker Mike Johnson projected confidence that the dispute would not affect prospects for the tax and border bill. 'Members are not shaken at all,' the Louisiana Republican said. 'We're going to pass this legislation on our deadline.' He added that he hopes Musk and Trump reconcile, saying 'I believe in redemption' and 'it's good for the party and the country if all that's worked out.' But he also had something of a warning for the billionaire entrepreneur. 'I'll tell you what, do not doubt and do not second-guess and don't ever challenge the president of the United States, Donald Trump,' Johnson said. "He is the leader of the party. He's the most consequential political figure of this generation and probably the modern era.'
Geeky Gadgets
22 minutes ago
- Geeky Gadgets
Stop AI Hallucinations : Transform Your n8n Agent into a Precision Powerhouse
What if your AI agent could stop making things up? Imagine asking it for critical data or a precise task, only to receive a response riddled with inaccuracies or irrelevant details. These so-called 'hallucinations' are more than just a nuisance—they can derail workflows, undermine trust, and even lead to costly mistakes. But here's the good news: by fine-tuning your n8n AI agent settings, you can dramatically reduce these errors and unlock a level of performance that's both reliable and context-aware. From selecting the right chat model to configuring memory for seamless context retention, the right adjustments can transform your AI from unpredictable to indispensable. In this comprehensive guide, FuturMinds take you through the best practices and critical settings to optimize your n8n AI agents for accuracy and efficiency. Learn how to choose the perfect chat model for your needs, fine-tune parameters like sampling temperature and frequency penalties, and use tools like output parsers to ensure structured, reliable responses. Whether you're aiming for professional-grade results in technical workflows or simply want to minimize hallucinations in everyday tasks, this report will equip you with actionable insights to achieve your goals. Because when your AI agent performs at its best, so do you. n8n AI Agent Configuration Choosing the Right Chat Model The foundation of a reliable AI agent begins with selecting the most suitable chat model. Each model offers unique capabilities, and aligning your choice with your specific use case is crucial for optimal performance. Consider the following options: Advanced Reasoning: Models like Anthropic or OpenAI GPT-4 are designed for complex problem-solving and excel in tasks requiring nuanced understanding. Models like Anthropic or OpenAI GPT-4 are designed for complex problem-solving and excel in tasks requiring nuanced understanding. Cost Efficiency: Lightweight models such as Mistral are ideal for applications where budget constraints are a priority without compromising too much on functionality. Lightweight models such as Mistral are ideal for applications where budget constraints are a priority without compromising too much on functionality. Privacy Needs: Self-hosted options like Olama provide enhanced data control, making them suitable for sensitive or proprietary information. Self-hosted options like Olama provide enhanced data control, making them suitable for sensitive or proprietary information. Multimodal Tasks: For tasks involving both text and images, models like Google Gemini or OpenAI's multimodal models are highly effective. To improve efficiency, consider implementing dynamic model selection. This approach routes tasks to the most appropriate model based on the complexity and requirements of the task, making sure both cost-effectiveness and performance. Fine-Tuning AI Agent Parameters Fine-tuning parameters is a critical step in shaping your AI agent's behavior and output. Adjusting these settings can significantly enhance the agent's performance and reliability: Frequency Penalty: Increase this value to discourage repetitive responses, making sure more diverse and meaningful outputs. Increase this value to discourage repetitive responses, making sure more diverse and meaningful outputs. Sampling Temperature: Use lower values (e.g., 0.2) for factual and precise outputs, while higher values (e.g., 0.8) encourage creative and exploratory responses. Use lower values (e.g., 0.2) for factual and precise outputs, while higher values (e.g., 0.8) encourage creative and exploratory responses. Top P: Control the diversity of responses by limiting the probability distribution, which helps in generating more focused outputs. Control the diversity of responses by limiting the probability distribution, which helps in generating more focused outputs. Maximum Tokens: Set appropriate limits to balance response length and token usage, avoiding unnecessarily long or truncated outputs. For structured outputs such as JSON, combining a low sampling temperature with a well-defined system prompt ensures accuracy and consistency. This approach is particularly useful for technical applications requiring predictable and machine-readable results. Best n8n AI Agent Settings Explained Watch this video on YouTube. Stay informed about the latest in n8n AI agent configuration by exploring our other resources and articles. Configuring Memory for Context Retention Memory configuration plays a vital role in maintaining context during multi-turn conversations. Proper memory management ensures that responses remain coherent and relevant throughout the interaction. Key recommendations include: Context Window Length: Adjust this setting to retain essential information while staying within token limits, making sure the agent can reference prior exchanges effectively. Adjust this setting to retain essential information while staying within token limits, making sure the agent can reference prior exchanges effectively. Robust Memory Nodes: For production environments, use reliable options like PostgreSQL chat memory via Supabase to handle extended interactions without risking data loss or crashes. Avoid using simple memory nodes in production, as they may not provide the stability and scalability required for complex or long-running conversations. Enhancing Functionality with Tool Integration Integrating tools expands your AI agent's capabilities by allowing it to perform specific actions via APIs. This functionality is particularly useful for automating tasks and improving efficiency. Examples include: Email Management: Integrate Gmail to send, organize, and manage emails directly through the AI agent. Integrate Gmail to send, organize, and manage emails directly through the AI agent. Custom APIs: Add domain-specific tools for specialized tasks, such as retrieving financial data, generating reports, or managing inventory. To minimize hallucinations, clearly define the parameters and scope of each tool. This ensures the agent understands its limitations and uses the tools appropriately within the defined context. Optimizing System Prompts A well-crafted system prompt is essential for defining the AI agent's role, goals, and behavior. Effective prompts should include the following elements: Domain Knowledge: Specify the agent's expertise and focus areas to ensure it provides relevant and accurate responses. Specify the agent's expertise and focus areas to ensure it provides relevant and accurate responses. Formatting Rules: Provide clear instructions for structured outputs, such as JSON, tables, or bullet points, to maintain consistency. Provide clear instructions for structured outputs, such as JSON, tables, or bullet points, to maintain consistency. Safety Instructions: Include guidelines to prevent inappropriate, harmful, or biased responses, making sure ethical and responsible AI usage. Using templates for system prompts can streamline the configuration process and reduce errors, especially when deploying multiple agents across different use cases. Using Output Parsers Output parsers are invaluable for enforcing structured and predictable responses. They are particularly useful in applications requiring machine-readable outputs, such as data pipelines and automated workflows. Common types include: Structured Output Parser: Ensures responses adhere to predefined formats, such as JSON or XML, for seamless integration with other systems. Ensures responses adhere to predefined formats, such as JSON or XML, for seamless integration with other systems. Item List Output Parser: Generates clear and organized lists with specified separators, improving readability and usability. Generates clear and organized lists with specified separators, improving readability and usability. Autofixing Output Parser: Automatically corrects improperly formatted outputs, reducing the need for manual intervention. Incorporating these tools enhances the reliability and usability of your AI agent, particularly in technical and data-driven environments. Additional Settings for Enhanced Performance Fine-tuning additional settings can further improve your AI agent's reliability and adaptability. Consider the following adjustments: Iteration Limits: Set a maximum number of iterations for tool usage loops to prevent infinite cycles and optimize resource usage. Set a maximum number of iterations for tool usage loops to prevent infinite cycles and optimize resource usage. Intermediate Steps: Enable this feature to debug and audit the agent's decision-making process, providing greater transparency and control. Enable this feature to debug and audit the agent's decision-making process, providing greater transparency and control. Multimodal Configuration: Ensure the agent can handle binary image inputs for tasks involving visual data, expanding its range of applications. These settings provide greater control over the agent's behavior, making it more versatile and effective in handling diverse scenarios. Best Practices for Continuous Improvement Building and maintaining a high-performing AI agent requires ongoing monitoring, testing, and refinement. Follow these best practices to ensure optimal performance: Regularly review and adjust settings to enhance response quality, reduce token usage, and address emerging requirements. Test the agent in real-world scenarios to identify potential issues and implement necessary improvements. Align tools, configurations, and prompts with your specific use case and objectives to maximize the agent's utility and effectiveness. Consistent evaluation and optimization are essential for making sure your AI agent remains reliable, efficient, and aligned with your goals. Media Credit: FuturMinds Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
The Sun
27 minutes ago
- The Sun
Huge fashion retailer with over 250 UK stores ‘drawing up radical rescue plan' with shops and jobs at risk
A HUGE fashion retailer with over 250 UK stores is reportedly drawing up a radical rescue plan which could see shops and jobs axed. The high street giant - which is being forced to restructure due to tough trading standards - employs around 5,500 people and was founded in London in 1948. 2 2 The chain's owners have brought in advisers from PricewaterhouseCoopers (PwC) to come up with money-saving solutions, reports Sky News. The proposals are expected to be finalised in a matter of weeks, though sources have reportedly claimed no decisions have been green lit on the retailer's future. Accounts for River Island Clothing Co for the year ending December 30 2023 showed the firm made a £33.2 million pre-tax loss. Then the turnover during the following 12 months fell by more than 19% to £578.1 million. The firm's latest accounts at Companies House, warned of growing financial and operational risks. "The market for retailing of fashion clothing is fast changing with customer preferences for more diverse, convenient and speedier shopping journeys and with increasing competition especially in the digital space," it said. "The key business risks for the group are the pressures of a highly competitive and changing retail environment combined with increased economic uncertainty. "A number of geopolitical events have resulted in continuing supply chain disruption as well as energy, labour and food price increases, driving inflation and interest rates higher and resulting in weaker disposable income and lower consumer confidence." In January, River Island hired consulting firm, AlixPartners, to undertake work on cost reductions and profit improvement. It's understood PwC has now taken over. Why are so many pubs and bars closing? In recent months, a number of River Island stores have been closing, including in Corby and Chesterfield. Originally named Lewis Separates and then Chelsea Girl, the chain was founded by Bernard Lewis in 1948 and became influential during the 1960s fashion scene, including the iconic mini-dress trend. It was re-branded as River Island in 1988 and throughout the next two decades expanded to become a leading high street force in the UK. It now has a presence in over 125 worldwide markets, in stores and online. Why are retailers closing shops? EMPTY shops have become an eyesore on many British high streets and are often symbolic of a town centre's decline. The Sun's business editor Ashley Armstrong explains why so many retailers are shutting their doors. In many cases, retailers are shutting stores because they are no longer the money-makers they once were because of the rise of online shopping. Falling store sales and rising staff costs have made it even more expensive for shops to stay open. The British Retail Consortium has predicted that the Treasury's hike to employer NICs from April 2025, will cost the retail sector £2.3billion. At the same time, the minimum wage will rise to £12.21 an hour from April, and the minimum wage for people aged 18-20 will rise to £10 an hour, an increase of £1.40. In some cases, retailers are shutting a store and reopening a new shop at the other end of a high street to reflect how a town has changed. The problem is that when a big shop closes, footfall falls across the local high street, which puts more shops at risk of closing. Retail parks are increasingly popular with shoppers, who want to be able to get easy, free parking at a time when local councils have hiked parking charges in towns. Many retailers including Next and Marks & Spencer have been shutting stores on the high street and taking bigger stores in better-performing retail parks instead. In some cases, stores have been shut when a retailer goes bust, as in the case of Carpetright, Debenhams, Dorothy Perkins, Paperchase, Ted Baker, The Body Shop, Topshop and Wilko to name a few. What's increasingly common is when a chain goes bust a rival retailer or private equity firm snaps up the intellectual property rights so they can own the brand and sell it online. They may go on to open a handful of stores if there is customer demand, but there are rarely ever as many stores or in the same places. The Centre for Retail Research (CRR) has warned that around 17,350 retail sites are expected to shut down this year.
