Venezuela jails 34 store managers on charges of price gouging 1357

Venezuela’s President Nicolas Maduro said on Thursday that 34 supermarket managers had been jailed on charges of hiding food and gouging prices, in the leftist government’s latest crackdown on businesses as the country struggles under a severe economic downturn.

“We had a group of supermarkets that hid the products from people and started to charge them whatever they wanted. There are 34 managers of big supermarkets behind bars for violating the law,” Maduro said, often angry during an hour-long televised broadcast on state television.

“I say one thing and the supermarkets come along and say another… What excuse do they have to not follow the rules?” said Maduro, urging Venezuelans to speak up if they see unfair prices to avoid “getting robbed.”

Last month, Maduro vowed an economic renewal for the oil-rich country, which is suffering from hyperinflation and shortages of basic goods, ordering a 60-fold salary hike and devaluing the currency by 96 percent.

His cash-strapped government said it would cover salaries for the first three months so that businesses would not increase prices despite the opposition-led congress estimating annual inflation at 200,000 percent.

Local media have reported that many of the arrested managers worked at Central Madeirense, a chain founded some 70 years ago by Portuguese immigrants. The company and Venezuela’s Information Ministry did not respond to requests for comment.

Some shop owners, doubtful that the government would ever cover the new wages, tried to balance the books by hiking prices and firing employees, adding to a mass exodus that has already seen over 2 million people flee the country of 30 million.

Economists say Maduro’s reforms do not tackle Venezuela’s root problems, namely currency controls and excessive money creation, and could in fact further destabilize its economy.

But Maduro struck an upbeat tone as he reviewed the measures, saying wage increases had been smooth and that authorities were no longer printing money unsustainably.

Maduro also said Venezuela would in October start using the petro, a cryptocurrency it launched this year, in international trade. A recent Reuters special report, however, showed that the petro is not a functional financial instrument, suggesting Caracas will struggle to get it accepted abroad.

A new system to pay for Venezuela’s gas will be extended nationwide on Monday, Maduro said. Venezuelans will be able to use a controversial state-issued “fatherland card” to fill their tanks, Maduro added, promising further details next week.

Maduro also blasted banks, giving them 48 hours to “free” the cash they were hoarding. Venezuela has struggled to print enough physical money, creating chronic cash shortages that Maduro has blamed on businesses and “mafias” operating in neighboring Colombia.

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Astreya Unveils New Wave of Enterprise AI Agents, turning Operational Signals into Real Insights and Rapid Action 582

Astreya, the world’s leading AI-First global IT managed services provider for Digital and IT infrastructure, is accelerating its mission to make AI and automation more accessible for businesses everywhere. By publishing ready-to-use AI agents across multiple marketplaces, including the ServiceNow Store, Astreya is helping organizations adopt AI faster and turn automation into measurable results. The initiative reflects the company’s broader commitment to improving efficiency, reducing manual workloads, and driving smarter operations across cloud, workplace, and IT environments.

Astreya recently served as a Prize Partner at A2HACKFEST 2K25 in Bengaluru, underscoring its commitment to investing in the next generation of AI innovation and talent. The company also participated in Google Cloud’s Agentic AI Day Hackathon, one of India’s largest developer events, where all four of its teams ranked among the top 700 submissions from over 9,100 entries and 57,000 participants.

Astreya’s “Soup Developers” team advanced to the Top 15 finalists, ranking among the top one percent of global submissions. Their concept, a modular ecosystem of 20 specialized AI agents, was designed to redefine financial planning by automating budgeting, cash-flow forecasting, market research, and investment strategy. The project stood out for its use of the Model Context Protocol (MCP), which allows agents to access real-time financial data, simulate complex market scenarios, and deliver personalized insights aligned to each user’s objectives.

Beyond the competition, Astreya has already released four production-ready AI solutions, powered by 21 specialized agents and advanced large language models on the ServiceNow Store. These agents empower IT teams to resolve issues faster, eliminate repetitive tasks, and increase productivity, freeing them to focus on higher-value, strategic initiatives that drive business growth.

  • TicketLens (Newly Published) — A certified AI solutions that delivers unified, single-pane insights across incidents and linked records, enhancing root cause analysis and resolution efficiency in dynamic ticketing environments. It provides one-click summaries of incidents, child incidents, problems, and changes; monitors CI health and completeness; and correlates related records to uncover potential root causes, recommends remediation steps, and will soon evolve toward guided and automated resolution, bringing engineers closer to faster, more accurate fixes within the ServiceNow environment.
  • Astraix — A proactive IT assistant that can analyze an image of an issue to identify the problem, recommend dynamic knowledge articles, trigger automated actions, and predictively assign the incident to the right group.
  • Attachment Summarizer — Reads and extracts the key points from ticket attachments, then updates work notes and surfaces relevant knowledge so teams don’t waste hours sifting through files.
  • Intelligent Knowledge Builder & Optimizer — Automates the creation, deduplication, and quality checks of knowledge articles, ensuring knowledge bases remain current and trustworthy.

Each solution removes the friction from IT support, enabling agents to resolve issues faster, with greater precision, at a consistently higher standard.

As part of its early adoption initiative, Astreya is offering its Agentic AI solutions free of charge for the next 3–6 months, enabling customers to experience their full potential, accelerate automation outcomes, and share actionable feedback through the ServiceNow Store.

AI Automation Assessment: Bridging Vision and Velocity

Astreya has launched the AI Automation Readiness, Maturity & Coverage Assessment, a vendor-neutral framework that helps enterprises identify automation blind spots, evaluate their current state, and accelerate AIOps adoption. The program delivers a maturity and tool-gap analysis, AI readiness scores, benefit projections, and a clear roadmap for transformation.

To complement this, Astreya’s Enterprise AI Services team introduced RapidPulse, a free, five-minute self-assessment that measures readiness across five pillars—Strategy, Tools & Platform, Data & Infrastructure, Process, and People—and provides an instant snapshot of AI and automation maturity.

By revealing where automation delivers the most value, Astreya enables organizations to prioritize investments, strengthen operational resilience, and move confidently from manual workflows to intelligent, autonomous IT operations.

Romil Bahl, CEO, Astreya: Most enterprises are still experimenting with AI in isolated pilots. The problem is that those efforts rarely scale. They stay in the lab, disconnected from the systems that drive real work. That means missed efficiency gains, higher costs, and teams carrying more manual effort than they should. By pairing agent-native applications with structured assessments and deployment playbooks, we embed AI directly where it matters, making businesses faster, leaner, and more resilient. Our new ServiceNow AI agents are a clear example of that shift,” said Romil Bahl, CEO, Astreya.

Expanding the AI Ecosystem with a Databricks Marketplace Debut

Building on its growing momentum in AI and automation, Astreya has launched its first solution on the Databricks Marketplace: Data Trust and Stats Intelligence (DTSi), now available for users to explore at no cost. This milestone also includes recognition as a validated Databricks Data Partner, reinforcing the company’s continued investment in scalable, real-world AI and data innovation.

Powered by five Gemini-enabled AI agents, DTSi is designed to help teams turn complex, unstructured datasets into trusted, actionable intelligence. The solution applies more than 15 advanced analytical and statistical techniques, from anomaly detection and correlation mapping to predictive modeling and hypothesis testing, to surface insights that accelerate better decision-making.

This expansion into the Databricks ecosystem reflects the same guiding principle behind Astreya’s multi-platform AI strategy: make AI easier to adopt, integrate, and scale. By delivering marketplace-ready solutions that unify data intelligence, automation, and AI-driven analysis, the company is helping enterprises move from raw data to confident action with greater speed and clarity.

Hyderabad: A Strategic Launchpad in a Global Model

The Enterprise AI Innovation Center in Hyderabad serves as the nucleus for applied research, experimentation, and rapid development of enterprise-grade AI solutions.

The center focuses on turning ideas into deployable outcomes, from developing AI agents and automation accelerators to creating point solutions tailored for business and IT operations. It brings together data engineers, AI scientists, and automation architects to prototype, validate, and scale solutions that directly address real-world enterprise challenges.

Beyond R&D, the center also serves as a client co-innovation space, where teams jointly explore use cases, assess AI readiness, and design adoption roadmaps that bridge experimentation and enterprise deployment.

“Our Hyderabad Innovation Center is a springboard for enterprise AI, where we validate agent-native ideas, run assessments to surface real value, and then harden solutions for production. Our Enterprise AI capability is global, but hubs like Hyderabad help us compress the cycle from prototype to deployment so clients see measurable outcomes faster,” explained Jothiganesh Nagarajan, COO, Astreya.

Looking ahead

Through strategic partnerships, agent-based innovation, and scaled engineering, Astreya remains focused on one core priority: turning AI into measurable enterprise value. The company continues to invest in multi-agent design, platform-native integration, and specialized engineering talent to help clients move beyond pilots and proofs of concept toward AI solutions that scale, deliver, and stick.

About Astreya

Astreya is a global IT managed services provider that powers enterprises by designing, deploying, and managing complex technology environments. We deliver end-to-end solutions across hybrid cloud, data centers, network infrastructure, and the digital workplace. Intelligent automation and AI run through everything we build to drive efficiency, accelerate service delivery, and clear barriers to growth for our customers.

Learn more at www.astreya.com

Nirmata Launches AI Platform Engineer to Automate Cloud-Native Infrastructure Governance and Management 590

AI-driven solution delivers enterprise Kubernetes management with automated policy-as-code for security, compliance, and governance

Nirmata, creator of Kyverno and leader in policy-as-code innovation, today announced the general availability of its AI Platform Engineering Assistant, an AI-powered solution that automates Kubernetes security, compliance, and workflow management across Kubernetes, Infrastructure as Code (IaC), and hybrid-cloud environments.

As organizations accelerate AI-assisted software development, platform teams must keep pace with increasingly complex infrastructure. Industry data shows a 30x acceleration in software creation and over $350 billion in AI infrastructure investment, yet nearly half of enterprises cite critical platform engineering skill gaps. Nirmata’s AI assistant empowers platform teams by automating the time-intensive tasks of Kubernetes policy management and securing infrastructure, enabling them to scale.

“Platform engineering has become both the bottleneck and the enabler of the AI future,” said Ritesh Patel, Vice President of Product at Nirmata. “Without scalable governance, innovation stalls under complexity and risk. With AI-powered governance, Nirmata transforms policy-as-code into a continuous, intelligent system that enforces compliance without slowing teams down.”

Built on the proven Kyverno policy-as-code engine—the CNCF-incubating project for Kubernetes, IaC, and cloud—the assistant uses a multi-agent architecture to automate policy authoring, detection, and remediation, creating a system for continuous Kubernetes governance and compliance that keeps humans in the loop while automating the most time-consuming tasks.

Key capabilities include:

  • Copilot interface: Conversational AI that turns hours-long investigation cycles into minutes. Engineers use natural language to instantly pull detailed insights, data, and reports about their infrastructure and generate enforcement actions.
  • Policy-as-Code Agent: Transforms natural language rules into validated Kyverno policy-as-code for Kubernetes and IaC, ensuring each rule aligns with security and compliance standards. This streamlines policy creation and eliminates common syntax errors while helping platform teams standardize governance across clusters and pipelines.
  • Remediation Agent: Detects misconfigurations and policy violations, then generates and validates secure fixes with human verification in the loop. This drastically reduces the time engineers spend diagnosing and correcting issues while ensuring every change remains compliant and secure.

Together, these agents deliver AI-powered Kubernetes security through a collaborative, intelligent system that continuously strengthens security, compliance, and operational trust while freeing engineers to focus on higher-value innovation. The AI Platform Engineering Assistant supports all common Kubernetes, Infrastructure-as-Code, and CI/CD systems, with native support for multi-cluster Kubernetes management and seamless integration with existing developer workflows.

Availability

The Nirmata AI Platform Engineering Assistant is now available to enterprise customers. Live demonstrations will be featured at KubeCon + CloudNativeCon North America 2025 and KyvernoCon.
To learn more or request a demo, visit nirmata.com.

About Nirmata

Nirmata is the creator of Kyverno, the CNCF policy engine for Kubernetes security and governance. With 2.5B+ downloads, Nirmata’s AI-powered policy-as-code solutions help enterprises automate Kubernetes compliance, prevent misconfigurations, and deliver enterprise Kubernetes management at scale across regulated industries. For more information, visit www.nirmata.com.

Loyalty Juggernaut Launches GRAVTY Agentic AI Compass: The World’s First Autonomous Loyalty Intelligence Suite 411

Empowering enterprises to run loyalty like a performance engine—transforming insight into impact and speed into strategic advantage through accountable Agentic AI.

Loyalty Juggernaut, Inc. (LJI), a global leader in enterprise loyalty-tech innovation, today announced the launch of GRAVTY Agentic AI Compass, the first-ever multi-agent intelligence suite engineered to transform how loyalty programs are run by augmenting human analysts with always-on, decision-ready intelligence.

Built on Amazon Bedrock and powered by GRAVTY’s patented data fabric, Compass marks a new era in loyalty operations. It enables brands to go beyond static dashboards, delivering proactive, explainable, and actionable insights at machine scale.

A 24×7 Loyalty Analyst—Powered by Agentic AI

Compass operates as a collective of specialized AI agents that function like a team of expert analysts. Each agent serves a distinct purpose—from program performance and strategic recommendations to sentiment analysis, anomaly detection, benchmarking, and offer testing. Working in harmony, they deliver proactive guidance, predictive insights, and prescriptive actions across engagement, economics, and experience—enabling loyalty teams to shift from manual analysis to strategic action.

“Loyalty leaders don’t need more dashboards—they need defensible decisions they can act on in real time,” said Dave Andreadakis, Chief Commercial Officer at Loyalty Juggernaut. “Compass closes the gap between ‘we think’ and ‘we took action.'”

Compass performs parallel investigations, blending quantitative KPIs with qualitative sentiment signals. It simulates outcomes before execution, de-risking decisions and ensuring every recommendation is explainable, auditable, and aligned with enterprise governance.

“GRAVTY Compass redefines how enterprises manage loyalty—by augmenting teams with autonomous intelligence that learns, reasons, and acts in real time,” said Kalpak Shah, Co-Founder and CTO at Loyalty Juggernaut. “It replaces static reporting with dynamic, agent-driven insight—empowering loyalty teams to move from observation to optimized action with unprecedented speed and confidence.”

AWS Endorses the Launch of GRAVTY Compass

“AWS is excited to support the launch of GRAVTY Compass, a groundbreaking multi-agent AI system for loyalty management. Built on the secure and scalable foundation of Amazon Bedrock, Loyalty Juggernaut’s specialized agents, from sentiment analysis to program benchmarking—are redefining how loyalty programs are managed. GRAVTY Compass delivers a truly intelligent Loyalty Analyst that transforms the day-to-day experience of loyalty teams by automating routine analysis, surfacing real-time opportunities, and providing on-demand, context-aware recommendations across engagement, economics, and experience,” said Jordan Alsop, Head of Commercial Data & AI at AWS.

About Loyalty Juggernaut, Inc. (LJI)

Loyalty Juggernaut, Inc. (LJI) is the company behind GRAVTY, a patented, AI-first loyalty platform that powers next-generation programs and ecosystems for global enterprises. With deployments across some of the world’s most iconic brands in airlines, hospitality, retail, CPG, BFSI, and telecom, LJI continues to redefine loyalty through Agentic AI, first-party data innovation, and real-time decisioning. Its clients include WestJet, Viva Aerobus, VietJet, Global Hotel Alliance, FEMSA, Majid Al Futtaim, Emirates and Deutsche Telekom.

www.lji.io

Drivetrain Launches First MCP Server For Finance, Connecting AI To Real Data 1182

By adapting Anthropic’s Model Context Protocol to finance, teams can ask complex business questions and get instant, intelligent answers grounded with actual company data.

Today, Drivetrain (Drivetrain.ai), announces the launch of the industry’s first Model Context Protocol (MCP) server designed specifically for finance, fundamentally transforming how CFOs and finance teams access and analyze business data. Now, financial professionals can have conversations in natural language with their company data through artificial intelligence (AI) assistants, like Claude.

Drivetrain MCP connects AI directly to companies’ actual financial data, unlocking a far higher order of analysis and decision-making. The breakthrough is powered by MCP, a specification developed by Anthropic that standardizes how AI agents and applications can securely exchange data and actions.

The Drivetrain MCP server allows large language models (LLMs) to access your business metrics while maintaining enterprise-grade security. Finance leaders can ask questions like “Why did our gross margin drop last quarter?” and receive in-depth analysis that investigates, hypothesizes, and provides explanations, just like an experienced analyst would, but instantly.

“Developers have Cursor. Sales has Clay. Finance, the most data-rich function, has lacked its AI layer, until now”, said Alok Goel, CEO and co-founder of Drivetrain. “Drivetrain MCP is the open standard that connects any model to any workflow, transforming finance into the intelligence center of business. This isn’t just infrastructure; it’s the start of finance’s AI era.”

The technology moves finance teams beyond simple “if this, then that” automation to truly autonomous AI. Ask Claude, “How does our revenue growth rate compare to competitors?” and it can automatically analyze growth data, search industry benchmarks on the internet, create an executive summary, and save it to Notion or a Google Doc, all from one conversation that would typically require analysts hours switching between multiple tools.

Drivetrain MCP is now available to all Drivetrain customers and can be configured with Claude Desktop or any other MCP-compatible system in minutes. The system maintains existing user permissions, ensuring secure access to company data.

About Drivetrain

Drivetrain is an AI-native business planning platform that helps finance teams plan, forecast, and report with greater speed and accuracy. Trusted by companies in 17+ countries, the platform integrates with 800+ systems, including ERP, CRM, HRIS, and BI systems. Drivetrain is headquartered in the U.S. with global teams across Toronto, New York, and Bengaluru. Learn more at drivetrain.ai.

Telmai Brings Autonomous-Ready Data Observability for the Agentic AI Era 1842

Telmai’s new Data Reliability Agents deliver AI-ready data at the lake, validated in real-time, with autonomous detection, resolution, and natural language interfaces for agentic workflows.

Telmai, the AI-powered data observability platform, today announced its Agentic offerings to make enterprise data truly Autonomous-Ready. These new capabilities ensure agentic AI workflows can communicate, decide, and execute actions on real-time trusted data with minimal human oversight.

Agentic AI significantly changes the requirements for how organizations manage their data and thus their data quality (DQ). Because Agentic AI requires low-latency and real-time access to validated data, it’s imperative that data quality happens right at the source, not downstream, where most companies focus their DQ efforts today.
But validation alone isn’t enough. AI agents also need to understand whether data is truly fit for purpose in the context of their actions. This involves delivering contextual information about data health as metadata into catalogs and semantic layers that AI agents can access.

Only when trust and context are combined can AI agents operate responsibly and enterprises deploy them with real confidence.

Telmai has the unique ability to continuously validate, monitor, and enrich data with quality signals at the lake and can push that data quality metadata for consumption by agents. This creates the trusted foundation that autonomous AI products need to operate reliably and at scale.

With Telmai’s latest product launch, AI agents can continuously access reliable data and the critical data quality context needed to automate downstream workflows.

Real-Time, Continuous, Agentic AI-Ready Data

At the core of this update is the introduction of Telmai’s MCP-compliant server, which enables LLM-powered agents like Claude, Bedrock, or Vertex to query Telmai directly. Telmai continuously validates data, whether structured, semi-structured, or unstructured. Additionally, it generates comprehensive data quality metadata alongside the validated data, providing essential context on data health to ensure the data is reliable and AI-ready. Through the MCP layer, AI agents can access and retrieve validated data and metadata into their agentic workflows, eliminating the need for third-party transformations or complex workarounds.

“In the era of model commoditization, true competitive advantage will emerge from trustworthy, dynamic, and contextually aware data,” said Sanjeev Mohan, industry analyst and principal at SanjMo. “Telmai’s latest release is a big step in this process. It offers continuous validation and contextual metadata that enable AI agents to act responsibly, while reducing the operational debt that has long hindered enterprise adoption.”

Natural Language AI Assistants & Decentralized Data Trust

Building on this foundation, Telmai is introducing a suite of AI assistants called Data Reliability Agents accessible through natural language interfaces, enabling both technical and non-technical users to interact directly with the platform. This decentralization means that ownership of data reliability no longer sits solely with engineering, accelerating time to value by making platform management and critical data quality insights accessible and actionable to all relevant stakeholders.

Autonomous Detection and Remediation

Telmai’s Data Reliability Agents enable autonomous detection and resolution of data anomalies. These intelligent agents continuously monitor data pipelines for irregularities and provide clear, plain-language explanations of root causes. Identifying and resolving complex data quality issues that once required deep technical expertise are now easily understood and addressed by both technical and business teams. Beyond detection, the Data Reliability Agents provide actionable recommendations and assist in generating data quality rules tailored to newly identified anomalies.

Furthermore, these Data Reliability Agents augment existing automated workflows, such as ticket creation and alert triggers, to help data teams proactively adapt and drive continuous improvement in their data quality processes.

This comprehensive approach closes the loop from detection through triage and remediation, ensuring that data being fed into the downstream processes is not only trustworthy but consistently ready for autonomous consumption and decision-making.

“As AI agents take the reins of decision-making, we believe autonomy should never come at the cost of reliability,” said Mona Rakibe, Co-founder & CEO of Telmai. “With these updates, Telmai is laying the groundwork for true intelligent automation and allowing enterprise data teams to shift their focus to driving measurable business value via Agentic AI.”

About Telmai

Telmai is a data observability platform company that enables enterprise data owners to monitor and detect real-time data issues. The platform leverages AI to monitor all data passing through the data pipeline before entering the data warehouse, protecting downstream systems and analytics used for decision-making. Telmai’s open architecture supports anomaly detection closest to data sources and works over complex data types with native support for nested and multi-valued attributes.

GAIM.FUN Secures Seed Funding to Revolutionize Virtual World Creation with AI 1888

GAIM.FUN, an innovative AI-powered platform transforming how virtual worlds and games are built, today announced the successful completion of its Seed funding round. This round attracted a distinguished group of investors specializing in AI, gaming, and Web3, including Griffin Gaming Partners, Bitkraft Ventures, Benchmark, 1Up Ventures, Playground Global, Norwest Venture Partners, and Hiro Capital, signaling strong market confidence in GAIM.FUN’s pioneering vision.

GAIM.FUN empowers creators by enabling them to turn a single sentence into a fully explorable, interactive 3D environment within minutes. Its cutting-edge AI engine generates modular, editable assets seamlessly integrated with physics properties, dynamic narratives, and intelligent NPC behaviors. Compatible with Unity and Unreal engines, GAIM.FUN dramatically accelerates development pipelines for indie developers, small studios, educators, and UGC creators alike.

The platform’s unique approach combines generative world models with a user-friendly editor, eliminating traditional barriers in 3D content production. With GAIM.FUN, users can automatically generate branching storylines, intelligent quest logic, and deeply simulated environments—all customizable to fit any creative vision.

Proceeds from the seed round will propel further AI advancements, expand the engineering and creative teams, and amplify global marketing to grow a vibrant user ecosystem. GAIM.FUN is positioned to lead the future of immersive virtual experience creation.

About GAIM.FUN

Founded to empower creators through AI, GAIM.FUN turns natural language prompts into dynamic, interactive 3D worlds ready for game engines. The platform’s modular assets, integrated physics, and adaptive narratives enable rapid prototyping and production, making it a hub for modern digital storytelling.