In a move that signals the next chapter in workplace modernization, JumpCloud Inc. has joined forces with Google Workspace to unveil the Work Transformation Set — an integrated, AI-driven solution designed to streamline enterprise productivity, security, and IT management under a single contract.

The offering merges Google Workspace’s AI-powered collaboration tools with JumpCloud’s identity, device, and access management platform, creating a unified ecosystem for modern enterprises seeking agility and security. Available exclusively through Google Workspace, the package consolidates pricing, support, and contracts — cutting complexity and cost while delivering enterprise-grade efficiency.

A Shift Away from Legacy IT

For decades, enterprises have been trapped by legacy IT systems that stifle innovation and increase operational risk. The Work Transformation Set represents a sharp turn away from that past. By combining AI-enabled productivity tools with Zero Trust security architecture, Google and JumpCloud are giving IT teams a roadmap for the AI era.

"Enterprise IT and security teams are at a crossroads," said Greg Keller, co-founder and CTO of JumpCloud. "The combination of JumpCloud and Google Workspace provides a clear path forward — leveraging Google’s AI to drive deeper security, productivity, and value."

The AI and Zero Trust Advantage

At its core, the Work Transformation Set is built for flexibility and future-proofing. The integration brings several key advantages:

• AI-Powered Productivity: Google Workspace with Gemini enhances everyday workflows, from automated content creation to smarter data analysis and seamless meeting management.

• Zero Trust Security: JumpCloud’s AI-driven Identity and Access Management (IAM) and Unified Endpoint Management (UEM) platforms deliver advanced biometric MFA and secure access across devices and operating systems.

• Simplified IT Operations: By merging licenses and support under one contract, enterprises can reduce Total Cost of Ownership (TCO) while streamlining procurement and compliance.

"Our customers need world-class AI, productivity, and collaboration — with best-in-class IT management," said Yulie Kwon Kim, VP of Product at Google Workspace. "Work Transformation Set delivers exactly that, helping businesses move beyond outdated technology and strengthen defense against evolving threats."

Real-World Impact: Fintech in Focus

Early adopters are already seeing results. Tamara, a fast-scaling fintech company, reports that the integrated solution has cut employee onboarding time by 70%, eliminated manual password resets, and ensured 100% device compliance.

"The seamless integration and powerful AI in Google Workspace, combined with JumpCloud’s unified management, have given us a secure, cloud-native foundation to scale at incredible speed," said Renjith Radhakrishnan, Head of IT Business Solutions at Tamara.

The Future of Enterprise Productivity

The Work Transformation Set marks a significant stride toward enterprise cloud maturity. In a landscape where hybrid work, security threats, and AI innovation converge, this collaboration reflects a growing industry shift: platforms that deliver holistic solutions rather than fragmented tools.

For businesses aiming to modernize their technology stack, the message is clear — the future of work isn’t about managing more tools; it’s about integrating smarter ones.

The Work Transformation Set from JumpCloud and Google Workspace is now available for enterprises looking to redefine productivity, security, and scalability in the AI-first era.

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Oracle Cloud Infrastructure (OCI) is doubling down on performance and efficiency. The company has announced the upcoming general availability of A4 compute shapes, powered by AmpereOne® M, the newest generation of Ampere-based processors. With this launch, Oracle becomes the first cloud provider to bring AmpereOne® M-based instances to market, further cementing its leadership in scalable, sustainable cloud infrastructure.

Slated for a November release across key regions—including Ashburn, Phoenix, Frankfurt, and London—the new A4 compute shapes promise a major leap in AI workload efficiency, price-performance, and energy savings.

Setting a New Standard for Cloud Compute

The A4 line builds on the success of OCI’s A1 and A2 compute shapes, which already serve more than 1,000 customers globally. With A4, Oracle is delivering up to 45% higher per-core performance on cloud-native workloads and 30% better price-performance compared to AMD EPYC-based OCI E6 shapes.

Available in both bare metal and virtual machine configurations, A4 instances feature 96 cores running at 3.6GHz, 100G networking, and 12-channel DDR5 memory bandwidth—making them ideal for AI inference, data analytics, and high-performance enterprise applications.

"Customers choose OCI for choice and flexibility," said Kiran Edara, VP of Compute at Oracle Cloud Infrastructure. "Our new Ampere A4 shape builds on what innovators like Uber and Oracle Red Bull Racing already achieve on OCI—delivering stronger price-performance and meaningful power savings."

AmpereOne M: Purpose-Built for AI and Cloud

Designed specifically for cloud and AI workloads, AmpereOne® M offers predictable performance and scalability without the overhead of legacy x86 architectures. It enables efficient compute performance across diverse workloads, from web services to machine learning inference.

"AmpereOne® M was designed from the ground up for cloud and AI," said Jeff Wittich, Chief Product Officer at Ampere. "Our collaboration with OCI gives customers access to the full potential of this latest processor."

With A4 shapes, enterprises can expect faster AI inferencing, reduced time-to-first-token, and higher tokens-per-second—key metrics for developers running small and mid-sized LLMs such as Llama 3.1 8B. OCI’s internal benchmarks suggest an 83% price-performance advantage compared to Nvidia A10-based systems, enabling cost-effective CPU-based AI deployment at scale.

AI Inference and Sustainability in Focus

As AI adoption surges, enterprises face the dual challenge of scaling compute while managing costs and carbon footprint. The A4’s energy-efficient design tackles both, providing a sustainable alternative to power-hungry GPU clusters.

Ampere’s AI Playground, featuring optimized software libraries and pre-built demos on GitHub, is helping developers get started with LLM deployment and inference-ready applications quickly—accelerating adoption across industries.

Early Adopters: Uber and Red Bull Racing

Leading enterprises are already on board. Uber, which operates much of its infrastructure on OCI’s Ampere-based compute, plans to expand its workloads to A4, citing up to 15% more performance and lower power consumption.

Oracle Red Bull Racing, another early adopter, is leveraging A4 instances in its London data center for race strategy simulations and AI workloads, expecting a 12% performance boost.

Internally, Oracle is migrating key services like Fusion Applications and Block Storage to A4, enhancing SaaS performance and resilience. The company is also deploying memory tagging—a security feature unique to Ampere processors—to strengthen exploit detection with minimal overhead.

The Broader Impact

The A4 rollout highlights Oracle’s commitment to open, efficient cloud computing and reflects Ampere’s growing momentum across the industry. As enterprises modernize for AI-driven workloads, A4 delivers the balance of performance, sustainability, and scalability that traditional systems struggle to match.

The message is clear: the future of cloud performance is efficient, AI-optimized, and Ampere-powered.

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Bloomreach, the agentic platform for personalization, has announced a strategic partnership with Databricks, the data and AI company behind the Data Intelligence Platform. The collaboration introduces a new native integration designed to give marketers direct, self-service access to enterprise data — without the usual bottlenecks of IT dependency or complex engineering workflows.

This integration marks a significant leap forward in bridging the gap between data management and marketing execution, enabling businesses to unify insights, streamline workflows, and drive personalization at unprecedented speed and scale.

Turning Enterprise Data into Marketing Action

For years, marketing teams have struggled with fragmented data systems that slow down execution and limit creativity. Bloomreach’s new Databricks integration changes that equation by eliminating data silos and allowing marketers to directly access their organization’s lakehouse architecture.

"Modern marketers need data and insights to be actionable within their marketer-friendly solutions," said Meera Murthy, General Manager and VP of Product at Bloomreach Engagement. "Our native integration with Databricks bridges the gap between data and activation. We're putting the power of enterprise-grade data directly into marketers' hands."

The integration delivers real-time synchronization of customer profiles, behavioral data, and product catalogs. This ensures that marketing campaigns are always powered by the most accurate, up-to-date information, fueling data-driven personalization across channels.

What the Integration Unlocks

The Bloomreach–Databricks partnership empowers marketers to build and deploy advanced, data-rich campaigns that were once reserved for technical teams. Among the key benefits:

• Enriched Customer Profiles – Import granular customer data, including purchase history, demographics, and loyalty information, for deeper segmentation and personalization.

• Real-Time Campaign Triggers – Activate campaigns automatically based on live event data or updated customer attributes, delivering timely, relevant experiences.

• Synchronized Product Catalogs – Maintain up-to-date product data across every channel, ensuring accuracy from ad to checkout.

• Advanced Loyalty Programs – Design personalized offers and communications based on loyalty tiers, reward balances, and engagement patterns.

The Broader Impact on Data-Driven Marketing

This partnership represents a pivotal step in modernizing marketing operations through AI and data democratization. By removing the barriers between data storage and marketing activation, Bloomreach and Databricks are making real-time personalization a scalable reality for enterprise brands.

The integration also reflects a growing industry trend: marketing platforms evolving into AI-native ecosystems, where data intelligence fuels automation, creative agility, and measurable performance.

With this collaboration, marketers can finally operate with the same agility as their data teams — turning insights into action in real time and redefining how personalization drives growth.

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Yandex has unveiled a groundbreaking AI-powered solution capable of assessing brain development in infants — marking the world’s first neural network designed specifically for this purpose. Developed by Yandex B2B Tech, the Yandex School of Data Analysis, and St. Petersburg State Pediatric Medical University, the technology automates MRI analysis for babies under 12 months old, reducing evaluation time from several days to just minutes.

The system, freely available on GitHub, is designed for use by hospitals and research institutions worldwide. It holds the potential to transform how clinicians detect cerebral palsy (CP) and other central nervous system disorders, enabling faster diagnosis and more effective rehabilitation planning.

Tackling a Global Pediatric Challenge

Cerebral palsy remains one of the most prevalent causes of childhood disability, affecting roughly 2–3 in every 1,000 live births, according to the World Health Organization (WHO). Early diagnosis is crucial for improving patient outcomes, yet identifying CP in infants under one year has been a longstanding clinical challenge.

MRI scans offer valuable insights into an infant’s brain structure but are notoriously complex to interpret due to the low contrast between gray and white matter — critical tissues that govern cognitive and motor development. While scanning takes 20–40 minutes, image analysis often consumes hours or days of a radiologist’s time, particularly when tracking multiple scans for developmental monitoring.

AI Steps In: How the Neural Network Works

Yandex’s new AI model automates the segmentation and classification of brain tissues in MRI scans, achieving more than 90% accuracy in distinguishing gray and white matter. The tool drastically reduces turnaround time and improves the precision of developmental assessments.

The project was inspired in part by prior global research efforts, such as the 2019 MICCAI Grand Challenge, which focused on infant brain segmentation. However, Yandex researchers faced the same obstacle that stymied earlier attempts — a lack of annotated data.

To overcome this, the team collaborated closely with pediatric radiologists to create new segmentation masks and train the neural network using a combination of machine learning experiments and clinical validation. The result is a purpose-built model optimized for real-world medical use.

"Although many commercial radiology tools exist, none had tackled newborn MRI analysis," said Anna Lemyakina, Head of the Yandex Cloud Center for Technologies and Society. "By combining AI expertise with clinical knowledge, we’ve built a solution that helps radiologists diagnose faster and plan rehabilitation earlier."

Practical Benefits for Global Healthcare

Yandex’s open-source approach means any medical institution or research organization can deploy the tool without licensing restrictions. Its potential benefits include:

• Improved accuracy and objectivity: The model quantifies the ratio of gray-to-white matter, ensuring consistent and data-driven assessments.

• Faster diagnosis: Processing times are reduced from days to minutes, enabling timely intervention for at-risk infants.

• Higher clinical throughput: Automating MRI segmentation allows radiologists to dedicate more time to complex diagnoses and patient consultations.

• Support for junior specialists: The AI can assist less-experienced clinicians in interpreting infant brain scans, enhancing confidence and consistency.

Accelerating Early Detection and Research

By cutting analysis time and boosting diagnostic accuracy, Yandex’s innovation may play a key role in accelerating early cerebral palsy detection and improving global child healthcare outcomes. The solution also supports longitudinal research by standardizing brain development measurements across large datasets.

In an era where AI-driven medicine continues to evolve, Yandex’s open-source contribution underscores the transformative potential of AI in clinical diagnostics — not to replace human expertise, but to enhance precision, speed, and accessibility.

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TransPerfect, the world’s largest provider of language and AI solutions, is adding more hardware to its trophy shelf. The company took home two major honors at China’s Auto Digital Awards, held during the Auto Digitalization & Marketing Innovation Conference (ADMIC) in Shanghai — a marquee event spotlighting digital transformation across the global automotive ecosystem.

The company was recognized as both Annual Automotive Digital Marketing Service Provider and Annual Outstanding Overseas Marketing Services Provider, underscoring its growing influence in the intersection of AI, localization, and global marketing.

Driving Digital Transformation in Automotive Marketing

This year’s ADMIC conference ran under the theme “All-Digital Forward, Counter-Cycle Growth,” attracting global automotive leaders, marketers, and digital innovators eager to navigate a rapidly evolving landscape. The Auto Digital Awards, centered on “Intelligent Digitalization Driving Growth,” honored companies pushing the boundaries of marketing technology and operational innovation.

For TransPerfect, that meant showcasing how its language, data, and AI capabilities power international growth for automotive brands. From data collection and multilingual content creation to AI-enhanced marketing automation, the company’s end-to-end localization technology continues to help automakers scale globally while maintaining local relevance.

The Global Auto Industry’s Digital Reckoning

As the automotive industry braces for tighter margins, sustainability pressures, and shifting consumer expectations, global brands—especially emerging Chinese automakers—are relying heavily on digital marketing to expand internationally. AI-driven personalization and automated localization are quickly becoming non-negotiable tools in this competitive race.

“We’re proud to help our automotive clients deploy digital strategies to expand globally—and we are honored by this recognition,” said Phil Shawe, President and Co-CEO of TransPerfect.

With China emerging as both a manufacturing hub and an innovation powerhouse in connected and electric vehicles, TransPerfect’s dual awards highlight its strategic role in bridging East and West through AI, data, and language intelligence.

The message from Shanghai was clear: in the automotive world, digital fluency and global storytelling are now as critical as horsepower.

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Optimizely, the leading digital experience platform (DXP) provider, is expanding its AI marketing capabilities. The company announced that Optimizely Opal, its agent orchestration platform, now integrates with Google Cloud’s Gemini Enterprise, a unified AI agent platform for discovering, creating, and running intelligent agents.

This integration addresses two persistent challenges for marketers: fragmented customer data and difficulty in delivering personalized campaigns at scale. By combining Opal with Gemini Enterprise, marketing teams can analyze enterprise-wide data, generate actionable insights, and even automate campaign execution.

Unleashing Agent-to-Agent Marketing Intelligence

Opal’s Agent2Agent (A2A) capabilities allow AI agents to collaborate seamlessly across systems. Marketers can now design workflows where agents gather, analyze, and act on customer data in real time. This approach eliminates manual data handling and accelerates campaign execution.

Powered by Google’s Gemini models, Opal delivers advanced reasoning over text and visual data. The integration enables sophisticated analysis of large datasets from multiple sources, offering insights that drive smarter and faster marketing decisions.

"We're entering an era where marketing teams need orchestrated intelligence that adapts, learns, and executes across workflows," said Jessica Dannemann, Chief Partner Officer at Optimizely. "Opal in the Google Cloud Marketplace makes AI marketing capabilities accessible and scalable for businesses."

Breaking Down Data Silos

Gemini Enterprise provides a network of third-party agents and integrations that unify data from dozens of enterprise systems. By connecting Opal to this ecosystem, marketers gain a holistic view of customers, enabling campaigns informed by complete, accurate, and real-time data.

This integration simplifies workflows, allowing teams to automate complex tasks such as industry research, content personalization, and performance monitoring. Agents operate continuously, providing insights overnight and ensuring marketers start their day with actionable intelligence.

Agent2Agent Interoperability Architecture

The A2A architecture enables real-time collaboration between AI systems. Agents can interact, share insights, and coordinate actions, removing the need for manual intervention. The architecture is host-agnostic, supporting diverse agent types and deployment models, which ensures flexibility for enterprise environments.

This innovation transforms Opal from a data analyzer into a fully orchestrated AI marketing assistant, capable of managing campaigns from insight generation to execution.

Driving Smarter, Faster Marketing

The integration empowers marketing teams to:

• Automate campaign execution: Agents can trigger personalized campaigns based on customer behavior and data insights.

• Enhance personalization at scale: Real-time analysis across multiple systems improves targeting and relevance.

• Accelerate decision-making: Continuous agent collaboration provides ready-to-use insights each morning.

• Unify marketing data: Eliminate silos and ensure consistency across global enterprise systems.

"Bringing Optimizely's agent to Google Cloud provides customers powerful new tools to advance digital transformation," said Dai Vu, Managing Director, Marketplace & ISV GTM Programs at Google Cloud. "The integration helps marketers break down data silos and innovate faster."

The Bigger Picture

With Opal’s July debut in the Google Cloud Marketplace, this deepened integration signals a growing trend: AI-driven orchestration is becoming central to marketing operations. Enterprises that adopt these agent-to-agent systems can not only optimize workflows but also create more intelligent, adaptive, and personalized campaigns.

By combining Optimizely’s AI expertise with Gemini Enterprise’s unified data capabilities, the partnership enables marketing teams to operate at a scale and speed previously unattainable, transforming data into actionable insights and measurable results.

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DoubleVerify (DV), the leading ad verification and media quality platform, today announced the expansion of its post-bid brand suitability measurement to Meta Threads feed. This move allows global advertisers to monitor content and context around their ads with AI-powered precision, ensuring campaigns maintain brand safety while reaching engaged audiences.

Ensuring Brand Safety in Emerging Platforms

Meta Threads is a dynamic, conversation-driven platform offering advertisers a chance to connect with highly engaged communities. However, its fast-moving feed presents challenges for brand safety. DV’s expansion provides independent, third-party verification, giving brands the confidence that their ads appear beside suitable and contextually relevant content.

"As advertising evolves across platforms like Threads, independent verification is critical to building trust and driving performance," said Mark Zagorski, CEO of DoubleVerify. "This expansion ensures brands have transparency and actionable insights to maximize campaign impact."

AI-Powered Brand Suitability

DV leverages its proprietary Universal Content Intelligence™ engine to analyze content across video, image, audio, speech, and text. Key features include:

• Proprietary AI Technology: Classification algorithms verify suitability at scale by examining content directly above and below ads.

• Comprehensive Coverage: Brand suitability measurement now spans Threads, Instagram, Facebook, and Audience Network.

• Accurate Media Insights: Real-time analysis provides actionable insights through DV Pinnacle®, DV’s unified analytics platform.

The platform’s key frame extraction technology pinpoints the most relevant video moments, reducing computing power and environmental impact while improving classification accuracy.

Maximizing Campaign Effectiveness

Advertisers using DV on Threads gain a holistic view of media quality, which helps safeguard brand equity, maximize contextual relevance, and reduce wasted ad spend. This integration forms a part of DV’s Media AdVantage Platform, which combines media verification, ad performance optimization, and campaign outcomes measurement.

Threads campaigns can now be monitored for brand suitability globally, with fraud detection and viewability measurement expected to follow. This expansion underscores DV’s commitment to providing advertisers with independent tools to navigate fast-growing social platforms without compromising scale or performance.

Why This Matters

The addition of Threads feed to DV’s brand suitability coverage comes at a time when advertisers are increasingly adopting conversational and real-time social platforms. By offering AI-driven verification, DoubleVerify helps brands:

• Ensure ads appear in safe and relevant environments.

• Reduce wasted spend caused by poor ad placements.

• Gain actionable insights for campaign optimization.

• Maintain global media quality standards across multiple social platforms.

In short, brands can confidently engage audiences on Threads while protecting their reputation and optimizing return on ad spend.

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FiscalNote Holdings, Inc. (NYSE: NOTE), a leader in AI-driven policy and regulatory intelligence, has introduced Bill Comparison in its PolicyNote platform. This new feature allows users to instantly compare legislative texts, track changes across versions, and identify critical differences that shape policy outcomes.

Even minor amendments can alter funding priorities, regulatory intent, or entire policy directions. Traditionally, spotting these nuances required labor-intensive, line-by-line analysis. Bill Comparison automates this process, providing a clear, streamlined view of changes between bill versions.

Instant Legislative Insights

PolicyNote users can now:

• Compare versions in seconds: Highlight additions, deletions, and modifications across bills.

• Track policy evolution: Understand how language, priorities, and funding references change over time.

• Use built-in search: Locate specific terms or provisions across multiple documents simultaneously.

The interface includes a redline view, making differences easy to spot, and allows professionals to quickly generate actionable insights for stakeholder briefings, regulatory reviews, or strategy sessions.

AI-Enhanced Policy Analysis

Bill Comparison integrates seamlessly with PolicyNote’s other AI features, including Similar Bills and Related Bills, which identify language reuse, policy trends, and cross-jurisdictional patterns. Users can also leverage the AI Assistant to generate plain-language summaries of differences or ask targeted questions, such as:

• “Which provisions were added in the latest version?”

• “How has funding changed between bills?”

These capabilities save hours of manual review and help policy professionals make strategic decisions faster.

Driving Efficiency for Policy Professionals

"Policy professionals are constantly pressed to understand how legislation is changing, and what it means, in real time," said Josh Resnik, CEO & President of FiscalNote. "Bill Comparison gives immediate visibility into what’s been added, removed, or changed, accelerating decision-making and providing a critical edge."

The feature supports tracking at all levels of government, from state amendments to complex federal legislation, ensuring that policy teams never miss important insights.

Implications for Legislative Monitoring

With Bill Comparison, FiscalNote strengthens its position as a market-leading AI platform for policy intelligence. By combining trusted data, expert curation, and AI-powered analysis, users can monitor legislative progress more effectively, spot trends, and respond to changes with confidence.

This launch represents FiscalNote’s ongoing commitment to delivering high-impact, AI-driven tools that transform policy monitoring, legislative analysis, and decision-making workflows for government affairs, compliance, and strategic planning teams worldwide.

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