Innovation

💸 HBX Group, in collaboration with FinPay, launched its eWallet in Spain, designed for the travel industry with features like integrated financing and full transaction traceability. Available initially in Spain, the platform aims to digitize B2B payments and expand to OECD countries from June. This eWallet facilitates instant, cross-border transactions, aiming for efficiency, reduced costs, and operational scalability. HBX's Daniel Nordholm and FinPay's CEO Juan Antonio Soriano highlighted the move towards digitalization and sector-specific solutions.

📱 Fliggy, an online travel services platform, introduced 'AskMe', an AI travel assistant, developed with Alibaba Group, emulating professional travel consultants. 'AskMe' uses proprietary data and Alibaba's Qwen AI for personalised itineraries, operating 24/7. It features real-time, bookable itineraries, live pricing for flights, hotels, and attractions with budget-adjustment capabilities. Additionally, it supports voice commands and generates visually rich itineraries with interactive maps, also allowing for social media sharing.

🏠 At the Arabian Travel Market (ATM) 2025, running from 28 April to 1 May in Dubai, AI's role in advancing travel will be highlighted. AI and machine learning capture about two-thirds of global tech investment deals in travel since 2020. Danielle Curtis, ATM Exhibition Director, promises visionary speakers and innovative solutions in booking and data analysis. Cassie Kozyrkov, ex-Google AI expert, will discuss AI adoption in travel on the opening day.

📦 Accelya launches FLX ONE Cargo, a cloud-native platform, to enhance airline cargo operations with AI and machine learning on AWS Cloud. The platform aims for better capacity planning, overbooking strategies, cargo space utilization, and reduces costs. FLX ONE Cargo enables real-time operations, digital connectivity, and offers to settlement lifecycle support. Tim Reiz, the Chief Product & Technology Officer at Accelya, emphasizes the necessity for modern infrastructure in the air cargo industry. The API-first architecture of FLX ONE Cargo complies with IATA standards, including ONE Record.

💸 2025 Paytronix Loyalty Report shows loyalty check sizes rising across restaurant concepts and c-stores, yet flat sizes are also common. 50% of full-service restaurants (FSRs), 44% of quick-service restaurants (QSRs), and 31% of convenience stores (c-stores) reported over 10% year-over-year loyalty check size growth. However, 12–25% of brands experienced declines, and about a quarter of QSR and FSR brands saw little change. AI-enhanced data analytics, qualitative behavior feedback, and personalized marketing are recommended to boost loyalty spend and program efficiency.

🍴 The 2025 Paytronix Loyalty Report indicates that loyalty check sizes are increasing in restaurants and c-stores, yet 50% of FSRs, 44% of QSRs, and 31% of c-stores experienced over a 10% rise year-over-year. However, 12-25% of brands saw loyalty check declines, and about a quarter of QSR and FSR brands observed flat growth. AI-enhanced data analytics, qualitative behavior feedback, and personalization are recommended for driving loyalty spend and personalizing guest experiences. Rachel Peterson, a Paytronix loyalty strategist, emphasizes the importance of granular, targeted messaging for customer retention and visitation.

💾 PAR Technology Corp announced the launch of its POS Spring Release with enhancements in guest convenience, in-store resilience, and platform extensibility. The release features contactless payment options like Pay via SMS and QR code, flexibility in adding items to orders, geofencing integration for kitchen chits, tailored pricing on item modifiers, and improved tax support reflecting regional rules. Additionally, custom data management and a real-time Data Feed improve sync times and system tracking.

💾 PAR Technology Corp. introduced PAR POS Spring Release, enhancing guest convenience with secure contactless payments, including Pay via SMS and QR code, loyalty account payments, and flexible item additions to orders. Staff operations streamlined with Geofencing Integration for Kitchen Chits, customizable pricing on item modifiers, and improved tax support for regional and third-party delivery service taxes. Platform extensibility now features custom data management via API, and a Data Feed reducing item sync times to nearly instant. These innovations aim to balance stability and innovation for restaurant operators.

💰 The 2025 Paytronix Loyalty Report indicates that loyalty check sizes have grown in 50% of Full-Service Restaurants (FSRs), 44% of Quick-Service Restaurants (QSRs), and 31% of convenience stores (c-stores) by over 10% year-over-year. Yet, 12-25% of brands across these segments saw loyalty check size declines, with a quarter of QSR and FSR brands experiencing flat check sizes. The report highlights the importance of AI-enhanced data analytics, qualitative behavior feedback, and personalized marketing strategies for increasing loyalty spend and customer engagement. AI-powered personalization, smart upsells, and relevant offers are essential to turning loyalty program participation into revenue.

📰 LLMs.txt is a new web standard assisting AI models like ChatGPT in understanding website content. It's a Markdown file at the root of a site, enhancing AI search visibility and ensuring accurate information referencing. This tool complements traditional SEO elements such as robots.txt and sitemaps. It's easy to implement and drives more organic traffic by improving AI-generated citations. LLMs.txt works by giving a structured content version to AI, with large language models trained on vast data sets using deep learning and neural networks. AI readability optimization includes clear headings, structured tables, FAQ sections, simple language, internal linking, and optimized metadata. The file's creation involves defining objectives, mapping content, writing in Markdown, and uploading to the website's root directory. WordPress and Webflow platforms can add LLMs.txt through plugins or redirects. Best practices for LLMs.txt include concise descriptions and regular updates. While AI models don't automatically detect LLMs.txt files yet, they can be manually introduced to AI tools to improve content prioritization and visibility. Real-world examples like Anthropic and Cloudflare showcase the effectiveness of LLMs.txt in AI-first content optimization.