The grocery industry has endorsed the Ensuring Fee-Free Benefit Transactions (EBT) Act, a bipartisan piece of legislation introduced by Rep. Shontel Brown, D-Ohio, vice ranking member of the House Agriculture Committee, and Rep. Tony Wied, R-Wis., House Agriculture Committee member and onetime small-business owner and retailer. The act would permanently prohibit additional fees from being imposed on retailers for Supplemental Nutrition Assistance Program (SNAP) electronic benefit transfer (EBT) transactions. “Independent grocers are on the front lines of the fight against food insecurity, investing heavily in technology and training to ensure SNAP works for families who rely on it,” said Stephanie Johnson, group VP for government relations at Washington, D.C.-based NGA. “The EBT Act is a necessary and commonsense solution to protect community-based retailers from new swipe fees that could compromise their ability to provide SNAP benefits and threaten food access in low-income areas.” The EBT Act would make permanent a provision in the 2018 Farm Bill that prohibits states and state contractors from levying processing and other related fees from a state’s side of a SNAP EBT transaction on SNAP-authorized retailers. While a permanent ban on interchange or swipe fees in SNAP already exists, the EBT Act applies the same permanent ban on state-side transaction fees. SNAP-authorized retailers must pay for their side of the costs associated with SNAP EBT transactions, but processing or other related fees outside of retailers’ control have never before been imposed on SNAP-authorized retailers. With the transition to chip cards and mobile payments, grocers are incurring considerable software and hardware costs, and many operators worry that EBT processors may begin charging fees for SNAP transactions, similar to the fees imposed on non-SNAP debit and credit card purchases. Such fees would be a hardship for independent grocers, many of whom operate on razor-thin margins of 1.4%, according to NGA. “Grocers already absorb significant upfront and ongoing costs to participate in SNAP, from purchasing EBT-compliant point-of-sale systems to training staff and ensuring program compliance,” added Johnson. “Adding processing fees would punish retailers for serving vulnerable populations.”
DoorDash launches all-day drone delivery in Dallas-Fort Worth, ordering food from dozens of local and national restaurants
Following a successful pilot, DoorDash and Flytrex have launched drone delivery service in the Dallas-Fort Worth Metroplex. Customers in parts of Little Elm and Frisco, Texas, can now order food from dozens of local and national restaurants, between 8:00 a.m. and 9:30 p.m., with delivery by Flytrex’s autonomous drone fleet. The launch marks Flytrex’s first third-party app integration, allowing customers to place orders directly through the DoorDash app. Eligible customers can choose drone delivery when checking out, with orders prepared at restaurants and flown to their homes. The service currently reaches more than 30,000 households and 100,000-plus residents, with additional sites in the area launching in the near future. According to DoorDash, it now offers the region’s most expansive drone operating hours and the highest payload capacity. Flytrex drones can carry as much as 6.6 pounds — the largest amount in the area — and next-generation models will boost capacity to 8.8 pounds. To accommodate the deliveries, neighborhoods have established drop-off points at public and communal locations throughout the coverage area. Flytrex has additionally implemented advanced drone traffic control technology, enabling various drone operators to serve overlapping communities while safely managing flight paths via automated systems, a move that broadens suburban coverage.
Walmart’s AI architecture rejects horizontal platforms for targeted stakeholder solutions, each group receives purpose-built tools that address specific operational frictions
Walmart continues to make strides in cracking the code on deploying agentic AI at enterprise scale. One of the retailer’s primary objectives is to consistently maintain and strengthen customer confidence among its 255 million weekly shoppers. Walmart’s AI architecture rejects horizontal platforms for targeted stakeholder solutions. Each group receives purpose-built tools that address specific operational frictions. Customers engage Sparky for natural language shopping. Field associates get inventory and workflow optimization tools. Merchants access decision-support systems for category management. Sellers receive business integration capabilities. The segmentation acknowledges the fundamental need of each team in Walmart to have purpose-built tools for their specific jobs. Store associates managing inventory need different tools from merchants analyzing regional trends. Generic platforms fail because they ignore operational reality. Walmart’s specificity drives adoption through relevance, not mandate. Walmart’s Trend to Product system quantifies the operational value of AI. The platform synthesizes social media signals, customer behavior and regional patterns to slash product development from months to weeks. The system creates products in response to real-time demand rather than historical data. The months-to-weeks compression transforms Walmart’s retail economics. Inventory turns accelerate. Markdown exposure shrinks. Capital efficiency multiplies. The company maintains price leadership while matching any competitor’s speed-to-market capabilities. Every high-velocity category can benefit from using AI to shrink time-to-market and deliver quantifiable gains. Walmart’s approach to agent orchestration draws directly from its hard-won experience with distributed systems. The company uses Model Context Protocol (MCP) to standardize how agents interact with existing services. Walmart leverages decades of employee knowledge, making it a core component of its growing AI capabilities. The company systematically captures category expertise from thousands of merchants, creating a competitive advantage no digital-first retailer can match. The strategic advantage compounds. Walmart’s 2.2 million associates represent proprietary intelligence that algorithms cannot synthesize independently. Their framework applies across industries. Financial services organizations balancing customer needs with regulatory requirements, healthcare systems coordinating patient care across providers, manufacturers managing complex supply chains are all facing similar multi-stakeholder challenges. Walmart’s approach provides a tested methodology for addressing this complexity.
Sam’s Club AI-enables omnichannel ad measurement for brand partners using deterministic data from the Sam’s Club closed-loop ecosystem
Sam’s Club is releasing a solution called Omni-Impact, an AI-based tool for Sam’s Club Member Access Platform (MAP) retail media network to track ad performance. Omni‑Impact uses deterministic data from the Sam’s Club closed-loop ecosystem to let advertisers see what is driving incremental sales across all MAP on-site and off-site channels and over time. It also offers a 12-month longitudinal view of campaign performance across MAP channels. To help ensure consistency, Omni‑Impact applies a single, unified methodology across all MAP ad solutions. As a result, participating brands can use standardized metrics to compare performance across tactics. Omni‑Impact also simulates media mix strategies and delivers predictive budget guidance tailored to each advertiser’s historical performance and category dynamics. Omni‑Impact surfaces performance trends across a wide range of audience segments, such as age, household size or membership tiers. The retailer also recently began using first-party data to create personalized experiences through an offering called MAP’s Omni Experiences. This offering combines digital performance tactics like search and display with immersive experiences in and around media activations via channel, including online and in-store. These experiences can promote large-scale seasonal events, such as back-to-school, as well as smaller brand-led localized events.
Treasure Data has released its MCP Server that allows AI assistants like Claude, GitHub Copilot Chat, and Windsurf to interact directly with intelligent CDP
Treasure Data, the Intelligent Customer Data Platform (CDP) built for enterprise scale and powered by AI, has released its MCP Server, a new open-source connector that allows AI assistants like Claude, GitHub Copilot Chat, and Windsurf to interact directly with your Treasure Data environment. Powered by the open Model Context Protocol (MCP), this solution gives data teams a new superpower: the ability to explore and analyze customer data in an easy and effective way, using plain language and a conversation window. With the Treasure Data MCP Server, teams can query parent segments and segments, explore tables, and analyze data using natural language, making data insights more accessible than ever. The MCP Server acts as a local bridge between your LLM-enabled tools and the Treasure Data platform. Once configured, it allows AI agents to securely interact with your CDP through structured tool calls. Instead of spending an hour writing multi-step SQL and debugging joins, the AI does it for you, writing, refining, and executing the query directly within Treasure Data. The MCP Server handles the permissions, safely limits results, and ensures your API keys and environment variables are managed securely. For most enterprises, the biggest barrier to using AI effectively isn’t the model, it’s the data. If an LLM can’t access high-quality, governed data, it can’t generate useful insights. The Treasure Data MCP Server removes that barrier. The AI accesses the CDP directly, securely and intelligently, so teams can finally start having productive conversations with their customer data.
Chronosphere redefines cloud-native observability with Logs 2.0 and real-time data control, unifiying observability by tightly integrating telemetry log management with metrics and traces
By helping organizations control and optimize their telemetry data, Chronosphere makes observability scalable, actionable and cost-effective with its platform’s open-source foundation being key to empowering enterprises in today’s distributed, data-intensive environments, according to Martin Mao, co-founder and chief executive officer of Chronosphere. Chronosphere Logs 2.0 represents a major leap in unified observability by tightly integrating log management with metrics and traces in one cohesive platform. Designed for cloud-native observability, this upgraded solution helps engineering teams shift from reactive troubleshooting to proactive, data-driven performance management, according to Mao. “It’s a brand new launch of a brand new product for us. It is end-to-end log management capability, you can imagine our ability to ingest and store logs natively into the product, and use logs along with the other data sources like metrics and traces. On top of that, we’re also providing a set of capabilities to control log data and log data growth, and that is fairly unique in the market. I would say, manage the data volume growth in logs, as well as cost, while also having a great performance and experience at the same time.” Ballooning telemetry data is a top inhibitor of observability effectiveness because it overwhelms systems and teams with excessive, often low-value data, making it harder to extract meaningful insights in real time. Chronosphere tackles this by offering data control, cost optimization and intelligent signal prioritization — purpose-built for the demands of cloud-native environments, according to Mao.
OPSWAT and SentinelOne’s AI/ML malware detection identifies threats that bypass traditional defenses such as polymorphic malware
OPSWAT and SentinelOne® announced their OEM partnership with the integration of SentinelOne’s industry-leading AI-powered detection capabilities into OPSWAT’s Metascan™ Multiscanning technology. This collaboration elevates malware detection across platforms, empowering enterprises to combat modern cyber threats with even greater precision and speed. With SentinelOne’s AI/ML detection capabilities now part of OPSWAT’s Metascan Multiscanning, joint customers benefit from: Enhanced detection accuracy through industry-leading AI capabilities; Cross-platform functionality, supporting both Windows and Linux deployments; Stronger ransomware and zero-day threat defense with autonomous, cloud-independent operation. Integrating SentinelOne’s AI detections strengthens Metascan’s multilayered defense, giving our customers faster, smarter protection against today’s most sophisticated threats. The inclusion of SentinelOne’s AI/ML detections in Metascan Multiscanning provides unmatched malware detection through simultaneous scanning with over 30 leading anti-malware engines, utilizing signature, heuristic, and machine learning techniques to achieve over 99% detection accuracy. The integration of SentinelOne’s AI/ML detections further amplifies this capability by identifying threats that bypass traditional defenses such as polymorphic malware.
Verax Protect safeguards companies against rising AI risks, peventing AI tools from exposing information to users that they are not authorized to access and enforcing organizational policies on AI
Verax AI has launched Verax Protect, a cutting-edge solution – suitable even for companies in highly regulated industries – aims to help large enterprises uncover and mitigate Generative AI risks, including unintended leaks of sensitive data. Key capabilities of Verax Protect: Prevent sensitive data from leaking into third-party AI tools: AI tools encourage users to input as much data as possible into them in order to maximise their productivity benefits. This often leads to proprietary and sensitive data being shared with unvetted third-party providers. Prevent AI tools from exposing information to users that they are not authorized to access: The increasing use of AI tools to generate internal reports and summarize sensitive company documents opens the door to oversharing data, raising the risk of other employees seeing information they’re not meant to access. Enforce organizational policies on AI: In contrast to the currently popular —but largely ineffective—methods of ensuring employee compliance with AI policies, such as training sessions and reminder pop-up banners, Verax Protect enables automatic enforcement of corporate AI policies, preventing both accidental and deliberate violations. Comply with security and data protection certifications. Many compliance certifications, such as those dealing with GDPR in Europe or sector-specific laws in the U.S. like HIPAA for healthcare or GLBA for financial services require evidence of an effort to safeguard sensitive and private data. Gen AI adoption makes such efforts more difficult to implement and even harder to demonstrate. Verax Protect helps to prove that sensitive and private data is safeguarded even when AI is used.
F5 introduces post-quantum cryptography tools for application security providing unified visibility into all encrypted traffic, apps and APIs
Application security firm F5 announced a series of post-quantum cryptography (PQC) solutions, designed to safeguard sensitive data and maintain performance across hybrid, multicloud and legacy environments at a time when classical encryption methods are becoming increasingly vulnerable. The company argues that, given the change ahead, that a poorly managed transition can cause outages and disrupt operations, especially across hybrid, multicloud and legacy systems. Without the right approach, organizations risk costly downtime, slower applications, compliance issues and frustrated users. The platform-based approach, which offers PQC support for both server-side and client-side encryption, protects organizations’ apps, APIs and data while optimizing performance. F5’s PQC capabilities offers a range of benefits, including trusted post-quantum encryption that utilizes the National Institute of Standards and Technology-standardized algorithms to secure customer data, intellectual property and critical assets without impacting system performance. The platform delivers end-to-end security, from client-side encryption to backend protection, and does so by combining high-availability application delivery with threat intelligence, firewall functions and secure access controls. The PQC offering provides unified visibility into all encrypted traffic, apps and APIs to enhance security oversight and support artificial intelligence, automation and telemetry initiatives. It also simplifies regulatory compliance by helping organizations meet evolving data protection standards as they adopt post-quantum cryptographic protocols.
Serrala launches cloud-based Cash Application solution to revolutionize receivables matching- a smarter way to match payments and remittances, cutting days of work down to minutes
Serrala raises the bar for Accounts Receivable (AR) with the launch of its new Cash Application capabilities, now part of the Alevate AR cloud solution. Designed to eliminate the headaches of manual cash allocation, this fully ERP agnostic, AI powered solution gives finance teams a faster and smarter way to match payments and remittances, cutting days of work down to minutes. With this launch, Serrala offers a complete cloud-native AR solution for the realities of today’s finance teams: automation at scale, seamless integration with any ERP system, and real-time visibility into receivables. Early adopters are already seeing measurable impact: up to 85% straight-through processing rates, a 90% reduction in manual processing and up to 75% faster cash application cycle times. Companies also report up to 40% fewer full-time resources needed to manage cash allocation tasks, freeing teams to focus on becoming more strategic. Nils Strachanowski, VP Product Order to Cash at Serrala said, “Alevate AR, with its advanced cash application capabilities, removes ERP limitations and delivers full transparency and intelligent automation across the entire receivables process regardless of platform. This marks a significant leap toward fully connected, data-driven finance operations. The solution also streamlines deduction handling, reduces error rates and misapplied payments, and delivers real-time KPI dashboards for metrics like DSO and working capital, putting actionable insights directly in the hands of decision makers.