Three Developments Worth Watching

1. DigitalOcean builds for self-improving AI agents: Managed memory, data services and feedback loops could simplify the development of autonomous applications.
2. NVIDIA and Cisco target AI infrastructure bottlenecks: High-density optical connectivity aims to support larger AI systems with greater efficiency.
3. HighByte and Databricks connect industrial data with AI: Governed, contextualized factory data could help manufacturers move from isolated experiments to operational use cases.

These developments matter because AI progress increasingly depends on what surrounds the model: reliable infrastructure, usable data and the ability to translate insights into action.

5 Technology News Stories

1. DigitalOcean Introduces Agent Learning and Data Services

DigitalOcean has introduced managed services for autonomous AI agents, combining persistent memory, vector data management and continuous feedback on its cloud infrastructure.

The move addresses a practical barrier to agent adoption: developers often need to assemble multiple services to maintain context and improve agent performance. Integrating these capabilities could reduce development complexity and make costs easier to manage, particularly for startups. However, self-improving systems still require evaluation, safeguards and human oversight. Easier deployment will matter most when agents perform reliably in real-world workflows.

2. NVIDIA and Cisco Collaborate on High-Density Optical Modules

NVIDIA and Cisco are developing a high-density, pluggable optical interface designed to connect increasingly large AI infrastructure and GPU clusters.

As AI workloads scale, networking bandwidth, power consumption and heat increasingly constrain data-center design. More efficient optical connectivity could help operators expand computing capacity without proportionally increasing networking overhead. A standardized approach may also simplify deployment across infrastructure ecosystems. The broader lesson is that AI scaling depends on more than faster processors. Connectivity and energy efficiency are becoming equally important considerations in infrastructure investment.

3. Xero Integrates Google Gemini for Financial Analytics

Xero is integrating its accounting intelligence with Google Gemini, allowing small businesses, advisors and bookkeepers to query financial data and generate reports through natural-language prompts in Google Workspace.

The integration could reduce the time small businesses spend switching between accounting dashboards, spreadsheets and documents to understand cash flow or investigate financial trends. It also brings AI closer to everyday decision-making instead of requiring users to learn separate analytics tools. The key test will be whether answers remain accurate, secure and useful enough to support financial decisions without replacing proper verification.

4. Atos and Fortinet Expand Their Global Cybersecurity Partnership

Atos and Fortinet are expanding their partnership into a globally coordinated cybersecurity model for hybrid and multicloud environments, combining security technology with consulting and managed services. The arrangement draws on Atos’s network of 17 security operations centers.

For multinational organizations, a more unified approach could reduce fragmented security policies, inconsistent regional contracts and visibility gaps across cloud environments. It also reflects demand for managed protection as security teams face complex threats and talent shortages. However, vendor consolidation only helps if organizations retain clear oversight, consistent service quality and measurable improvements in threat detection and response.

5. HighByte and Databricks Make Industrial Data More Accessible for AI

HighByte and Databricks are extending their integration to stream contextualized industrial data into the Databricks Data Intelligence Platform, supporting analytics, machine learning and agentic AI applications.

Manufacturers often hold valuable operational data across disconnected systems, making it difficult to use consistently in AI projects. Connecting industrial data with governed analytics infrastructure could reduce custom integration work and help teams apply insights to quality, productivity and maintenance. The challenge remains data quality and governance. AI cannot produce dependable operational decisions when underlying factory data is incomplete, inconsistent or poorly contextualized.

ITDigest Featured Article

Future of Digital Payments: How Fintech Disruption Is Reshaping the Global Financial Ecosystem

Digital payments are evolving through real-time transfers, digital wallets, embedded finance and AI-driven fraud detection. This article examines how these technologies are changing customer expectations, business cash flow and financial inclusion. It also explores persistent challenges, including cross-border friction, security risks, regulation and system integration. Its central argument is that faster payments create value only when businesses combine convenience with reliability, interoperability and customer trust.

ITDigest Weekly Observations

This week’s announcements point to a shift from isolated technology upgrades towards connected systems built for practical use. AI agents need reliable memory and governed data; AI infrastructure needs efficient networking; businesses need financial and operational insights they can act on; and cybersecurity must scale across increasingly complex environments.

The common challenge is execution. Integrations can reduce friction, but they cannot compensate for weak data, poor governance or unclear business objectives. As these technologies mature, the next question is: Which organizations will turn these connected capabilities into measurable productivity gains, and which will remain stuck in implementation?

The post ITDigest Weekly Roundup: Self-Improving AI, Smarter Infrastructure and the Future of Digital Finance appeared first on ITDigest.

As the adoption of Microsoft Copilot and Generative AI workflow becomes increasingly popular among smaller and medium-size companies, MSPs find themselves on a fine line when it comes to providing productive work within the modern workplace environment without being exposed to extreme data leakage, shadow AI and credential risk. The new platform from Proofpoint bridges this gap with multi-tenant management, auto-risk scoring and live DLP in the AI-powered MS 365 workload for MSPs.

“Many organizations are currently considering which AI solutions to deploy. Just as important, however, is which data and communication channels these technologies will interact with. Overly broad permissions, unclear sharing settings or a lack of confidence among employees do not arise because of AI, but its use can amplify their impact. Organizations therefore need to build AI readiness on strong security foundations,” explains Daniel Hofmann, GM & EVP, Proofpoint MSP Platform.

Human-Centric Security Meets Multi-Tenant Automation.

Previously, SMBs have used either native, built-in cloud security tools or a series of disconnected point solutions with limited capability to catch sophisticated, human-fueled threats. Now, with the advent of generative AI copilots (like Microsoft Copilot), there’s added risk. AI copilots build a context from across an entire enterprise tenant, so poorly designed access controls and unreviewed user prompts can give away sensitive IP, HR, or financial information.

Also Read: Atos and Fortinet Establish Global Cybersecurity Partnership to Address Enterprise Security Challenges 

Proofpoint’s new MSP architecture addresses these operational pain points with a dedicated, partner first architecture:

Multi-Tenant AI Risk Visibility: offers managed service providers with a single console that enables them to view prompt activity, access to sensitive data, and risky behaviors of user all at once across all the managed Microsoft 365 tenants.

Automatic DLP Enforcement: Blocks sensitive data such as PII, financial data, and intellectual property from entering any unapproved external AI models or leaking via any internal AI queries within the enterprise.

MSP Workflow Simplification: Combines tenant health management, threat detection, and billing into one platform to lower cost-to-serve for service providers and expedite threat detection and remediation.

Strategic Impact on the Cybersecurity Industry

When you deploy specialized AI governance and threat protection over managed channel platforms, you usher in important structural realignments into the Cybersecurity & Managed Services areas:

1. The Transition from Perimeter Defense to “AI-Contextual” Data Governance.

Legacy cybersecurity efforts concentrated on perimeter protection and blocking malicious files from the outside. Generative AI tools work from the insidegiving users the ability to call upon AI assistance with legitimate prompts, and users having access to internal files. Proofpoint‘s release is the first clear sign of an industry movement toward AI-contextual protection where protection technology is constantly checking users’ identity, the intention behind their prompt, and the sensitivity of the data before responding.

2. Democratizing Enterprise-Grade AI Security for the SMB Segment.

In the past, advanced Data Loss Prevention (DLP) and identity threat detection solutions were accessible mainly to organizations with large enterprise budgets and dedicated Security Operations Center (SOC) teams. By providing AI-focused governance tools through an automated MSP platform, mid-market, and small businesses can now use tools like Microsoft 365 Copilot more securely. This approach enables SMBs to achieve enterprise-level risk management without the need for in-house cybersecurity engineers.

3. Resolving “Shadow AI” and Misconfiguration Vulnerabilities

The primary risk for organizations using Microsoft 365 Copilot is over sharing of data due to old file permissions. If users provide wide access to internal folders, Copilot indexes those files and brings confidential content to unintended internal users. Automatic risk scoring enables MSPs to discover and remediate overshared files before deploying Copilot.

Overall Effects on Businesses Operating in the IT & Cybersecurity Sector.

The raise in Proofpoint’s scale raises the stakes for other managed service providers, security software vendors, and enterprise customers:

Higher Service Margins for MSPs: MSPs can leverage tenants security management via automation and conduct AI risk audits to provide high-margin “AI Readiness and Security” managed service tiers that generate ARR without additional admin FTEs.

Lack of AI Governance Will Hurt Un-Governed Cloud Security Bundles: customers of IT service providers for Standard, non-Governed Cloud Security Bundles that offer email filtering without DLP or AI governance will start leaving them in droves. Business leaders want MSPs that can secure their AI integrations.

Reducing legal and regulatory compliance liabilities Automated enforcement of DLP protection avoids compliance violations like GDPR HIPAA PCI-DSS and reduces the regulatory penalties faced by SMBs and their IT partners.

Conclusion

This Proofpoint platform expansion marks a critical evolution in channel-led cybersecurity. By providing the combination of human-centric threat protection with the automated, AI-based Microsoft 365 AI governance, the platform bridges the gap between software innovation at a fast rate and secure operational execution. To the cybersecurity industry at large, this launch is an indication that the future of enterprise protection is the safe, governed, and scalable adoption of AI for all businesses.

The post Proofpoint Introduces New Microsoft 365 Security Updates for MSPs and Businesses appeared first on ITDigest.

Also Read: NetSuite Unveils Free AI-First Financial Platform to Accelerate Startup Scale from Idea to IPO

“The AI industry keeps telling enterprises to buy a smarter model, but a model can’t reason its way to your definition of revenue,” said Chris Lynch, CEO of AtScale. “Enterprises need to define what an answer means, compute it correctly, and prove it holds up. AtScale for AI brings those capabilities together so accuracy becomes something businesses can measure, improve, and demand.”The platform aims to address a common challenge in enterprise AI: models may interpret metrics such as revenue differently unless organizations provide clear definitions and consistent calculation rules.

Read More: AtScale Launches AtScale for AI to Close the Enterprise AI Accuracy Gap

The post AtScale Unveils ‘AtScale for AI’ to Resolve Enterprise AI Business Logic and Accuracy Challenges appeared first on ITDigest.

Also Read: Zones and Thoughtworks Partner to Bridge the AI Execution Gap for Enterprise IT

Deutsche Telekom uses Xurrent’s incident response platform to help maintain service reliability during major live events and keep customer-facing services running smoothly.”Engineers have AI to help them write code, but when that code breaks, they are still left searching through logs, dashboards and past incidents to understand what happened,” said Brian Wenngatz, CEO of Xurrent. “The next step is bringing that same level of AI support to incident resolution, giving engineers the context they need to move faster while keeping their expertise and judgment at the center.”Xurrent includes its AI capabilities across the platform without additional charges for premium AI features.

Read More: Xurrent Extends Sera AI Into an AI SRE teammate to Help Engineering Teams Resolve Incidents Faster

The post Xurrent Unveils AI SRE Teammate to Accelerate Incident Investigation and Root Cause Analysis appeared first on ITDigest.

In leveraging Veeam Data Platform operational telemetry to feed into the Arctic Wolf Aurora® Superintelligence Platform and Aurora Agentic SOC, the collaboration enables enterprise IT and security teams to address the problem of operational blind spots in recovery infrastructure. This multi-domain view allows security analysts to detect, investigate, and mitigate new cyberattacks more quickly and accurately.

Connecting the Dots Between Cyber Defense and Data Recovery

Given the emergence of advanced usage of artificial intelligence by threat actors to perform quick and large-scale cyberattacks, enterprise backup and disaster recovery strategies are now primary targets for hackers. Hackers look to target the secondary infrastructure to cause disruption and get ransom payments. On the other hand, there are too many alerts and data that security analysts need to sift through to distinguish risks from everyday business activities. The problem is that when backup software is used in isolation from the main Security Operations Center (SOC) processes, security analysts do not have enough contextual information to assess suspicious activities and protect restore points.

To solve this disconnection, Veeam operational and security events stream natively into the Aurora Superintelligence Platform. The system correlates these telemetry feeds alongside more than 10 trillion weekly security signals collected across Arctic Wolf’s global customer base. The platform monitors crucial recovery activities including malware signatures within backup sets, anomalous user access patterns, unauthorized restore attempts, failed backup jobs, and administrative privilege changes enabling automated threat detection and deeper infrastructure oversight.

Also Read: Pricefx Partners With Databricks to Bring AI-Powered Pricing Intelligence to Enterprise Data

For mutual customers, the joint deployment enhances Veeam’s native immutable backup storage and data integrity checks with continuous threat monitoring, expert forensic investigation, and deep security context managed through Arctic Wolf.

Unfiltered Industry Statements and Executive Perspectives

“Organizations depend on their recovery environments to maintain business continuity when an incident happens, making visibility into those systems critical for cyber resilience,” said Dan Schiappa, President, Technology and Services at Arctic Wolf. “In the age of AI, security teams don’t need more alerts. They need context to understand what matters and how to respond. By bringing Veeam backup intelligence into the Aurora Superintelligence Platform, we’re helping customers gain a more complete view of their environment, accelerate investigations, and strengthen the resilience outcomes that matter most to their business.”

“Data and AI trust requires security and resilience to operate as one connected discipline,” said Michelle Graff, Senior Vice President for Global Partners and Channel at Veeam. “By bringing Veeam signals into Arctic Wolf’s security operations platform, we are giving organizations greater visibility into threats affecting their critical data and recovery environments. This partnership helps customers strengthen the trusted, secure, and resilient data foundation they need to maintain business continuity and safely accelerate AI at scale.”

Improving Connected Cyber Resilience and Future Integration Strategies

The collaboration builds on the joint effort of both vendors to ensure that organizations are able to reach end-to-end operational resilience via coordinated security and data protection processes. Going forward, Arctic Wolf and Veeam intend to improve their technical coordination around the areas of exposure management, threat detection, and automated recovery execution to allow enterprises to invest in better security.

The post Arctic Wolf and Veeam Form Strategic Alliance to Integrate Backup Intelligence directly into Security Operations Architecture appeared first on ITDigest.

“Organizations need the flexibility to pursue new AI opportunities while improving the economics of their overall infrastructure,” said Kurt Daniel, CEO of Virtuozzo. “With updated NVIDIA support and a smaller deployment footprint, Virtuozzo helps them bring GPU-powered services to more customers and locations. Our focus is on making cloud and AI easier to deliver, more efficient to operate, and profitable to grow.”

V/IS version 8.0 supports NVIDIA R595 and vGPU v20, enabling dedicated and shared GPU resources on the same host. Providers can run AI alongside traditional workloads while helping customers control data location and access.

Also Read: HighByte and Databricks Partner to Make Industrial Data More Accessible for AI Applications

This release introduces a lite deployment option for environments needing only one or two servers. Compute, management, and storage run together using local disks instead of shared storage, reducing infrastructure investment for smaller customers, branch offices, and factory locations.

Providers and channel partners can use the new option to offer:

• Dedicated customer nodes for workloads requiring separate hardware
• Managed infrastructure on customer premises for applications and data that need to remain local
• Deployments for smaller businesses sized for current needs, with an expansion path as demand grows

Each independent deployment includes its own admin panel, monitoring, and alerting. Configurable system reservations help reduce the resources allocated to system services, leaving more capacity for customer workloads.

Lite deployments use standard V/IS licensing, with per-core and per-TB logical storage pricing. A one-server configuration can deliver approximately 53% lower total cost of ownership than VMware.

Nodes with local storage can be added under common cluster management as customers need more capacity. When customers require automatic VM failover, providers can introduce a storage network and shared V/Storage across at least three nodes to form a standard high-availability cluster.

Additional improvements in the release include generally available migration from VMware vSphere 8 without VDDK, a new onboarding wizard, a RHEL 10 operating system, faster object storage, and greater control over API access.

SOURCE: Globenewswire

The post Virtuozzo Updates Infrastructure System to Support Flexible Deployment and NVIDIA Integration appeared first on ITDigest.

From inbox to action, natively

Every day, AR teams spend hours reading customer emails, interpreting requests and manually recreating those actions in their AR systems. As email volumes grow, repetitive work limits the time finance specialists can spend on resolving disputes, engaging customers and accelerating collections. Quadient’s AR email agent removes this bottleneck. It triages emails and tickets, classifies payment commitments, invoice questions and disputes, and prepares the corresponding actions directly in the platform where AR teams already work. There is no separate tool and no copy-and-paste.

Also Read: Spectrum Instrumentation General-purpose digitizers get onboard averaging function

Automation with governance built in

Organizations decide how the agent operates, which actions are enabled, and where human reviewers step in. Every action remains visible and auditable.

“As cash becomes an increasingly strategic lever for business growth amid complexity, accounts receivable teams should be focused on improving cash flow, not recreating information from emails inside another system,” said Lilac Schoenbeck, Senior Vice President of Product for Quadient Digital. “The Quadient AR email agent combines the speed of AI with the confidence of human oversight, giving organizations the ability to automate repetitive work while maintaining complete visibility and control. This launch is an important milestone in our broader vision for bringing intelligent AI agents to finance operations.”

A connected, AI-native finance platform

The release of AR email agent marks the next milestone in Quadient’s broader expansion of agentic AI across AR, AP and CCM. Quadient plans to introduce additional purpose-built capabilities that address workflow challenges unique to each discipline while creating a more connected digital platform. The AR email agent is globally available for opt-in today for Quadient AR customers.

The post Quadient Expands Agentic AI to Accounts Receivable, Turning Customer Emails into Action appeared first on ITDigest.

By bringing together business development and customer engagement as well as service delivery and commercial arrangements on a global level, these companies fill a major gap in the process of enterprise risk management. This new architecture will integrate Fortinet’s cutting-edge technology solutions, such as Secure Networking, Unified SASE (Secure Access Service Edge), and Security Operations powered by AI with Atos’s global consultancy services, system integration, and managed security services (MSS). This partnership operates through 17 Security Operations Centers (SOCs) at Atos, where over 31 billion security events are processed each day.

“Elevating our long-standing partnership from a country-led model to a globally coordinated alliance builds on the strong complementarity between Atos’ expertise in digital transformation and managed security, and Fortinet’s leadership in cybersecurity innovation,” stated Thomas Desrues, SVP of International Channel Sales at Fortinet.

Behind the Scenes: Global Mesh Architecture & Unified Managed Defense

In the past, multinational corporations operating in multiple continents had localized IT security contracts, which gave rise to fragmented architectures and vendor sprawl. Multi-cloud infrastructure consisting of private data centers, AWS, Azure, and Google Cloud suffered from “visibility blind spots,” where security policies were not consistently enforced within the regional jurisdictions.

Also Read: Trellix Launches Wise for Private Cloud to Strengthen AI-Powered Security Operations

The enhanced global partnership between Atos and Fortinet solves all these operational challenges through the following four-tier delivery model:

Global Service Standardization: Aligns commercial and technical SLAs in different countries, thus ensuring that corporate clients receive identical governance regardless of their branch office or cloud location.

Integrated SASE and Secure Networking: Combines Fortinet’s FortiEDR and SASE technology with Atos’s managed network services, thus implementing Zero Trust architecture for hybrid and remote workers.

AI-Powered Threat Orchestration: Allows integration of Fortinet’s AI-powered security telemetry with 17 SOCs of Atos, thereby providing automatic threat detection and incident investigation at speed of cyber attacks.

Unified Sovereign Compliance: Allows global enterprises to implement local data residency and audit compliance with the new requirements such as NIS2, DORA, and GDPR.

Strategic Impact on the Cybersecurity and Managed Security Services Industry

Transitioning from localized agreements to a unified global managed security model introduces fundamental structural realignments across the Cybersecurity and Managed Security Services (MSSP) landscape:

1. The Increasing Transition to Managed Vendor Consolidation

In particular, Chief Information Security Officers at enterprises are shifting from managing over ten individual point security vendors. Coordinating a global unified framework in combination with a leading security hardware vendor (Fortinet) and a leading international systems integrator (Atos) speeds up the process. MSSPs with regionally fragmented partnerships find themselves competing against well-coordinated global teams.

2. Overcoming the Global Scarcity of Skilled Cybersecurity Personnel with AI and Global Reach

Cybersecurity continues experiencing a chronic global shortage of skilled security analysts who have threat hunting expertise. Enterprise IT departments face problems recruiting, retaining, and scheduling shifts of highly trained personnel. Global centralization of managed defenses through Atos’ network of 17 SOCs combined with Fortinet’s innovative security operations allows enterprises to outsource threat analysis at the Level-1 and Level-2 levels. As a result, the CISO of an enterprise can deal with strategic issues of managing risks.

3. Creating Uniform Policies for Zero Trust Networks in Multi-Cloud Environment

As organizations move workloads to hybrid and multi-cloud infrastructures, implementation of Zero Trust Network Access policies becomes extremely complex. Integration of SASE technology of Fortinet into the managed solution of Atos results in a blueprinted deployable structure

Overall Impact on Companies Running Business in IT & Cybersecurity Industry

Global partnership between Atos and Fortinet lays down definitive operational standards for enterprise buyers, cloud service providers, and channel partners:

Reduced Costly Procurement: Global enterprises are able to conduct IT procurement through one integrated contractual agreement and will not have to sign individual region-specific agreements with regionally-based resellers.

Greater Competition for Regional IT Service Providers: IT service companies that do not have globally-aligned SOC capabilities or internationally-standardized delivery processes will lose out on deals from multinational companies as a result of such globally-aligned alliances.

Greater Emphasis on Outcome-Based Security Managed Services: The business outcome of the cybersecurity solution will be measured based on MTTD and MTTR, and not only on buying the licenses.

Conclusion

Atos and Fortinet’s global partnering approach becomes a landmark event in terms of enterprise security architecture development. With the help of innovative AI solutions developed by Fortinet and global coverage provided by Atos, the partnership resolves the problem that has been bothering multi-cloud security in terms of management. For the entire industry of cybersecurity, the news demonstrates the following – protecting modern global enterprises requires connecting technical innovation with global standardization.

The post Atos and Fortinet Establish Global Cybersecurity Partnership to Address Enterprise Security Challenges appeared first on ITDigest.

Also Read: FIS Integrates Agentic AI Across Financial Intelligence Network to Help CFOs Forecast Cash Flow and Mitigate Market Risks

The workflow examines customer-specific requirements, reviews orders, and recommends next steps, while employees continue to make the final decisions. “Customers are challenged with figuring out how AI can make a difference in their business,” said Jeff Cobb, SVP, Integrated Solutions, Zones. “They may have pilots underway, but don’t always have the strategy, infrastructure, skills or resources to take the next step. Through our partnership with Thoughtworks, we’re helping customers identify the right opportunities and then giving them the technology and expertise to turn those opportunities into results that matter to their organization.”

Read More: Zones Expands AI Services with Thoughtworks Partnership to Help Customers Turn AI Into Business Results

The post Zones and Thoughtworks Partner to Bridge the AI Execution Gap for Enterprise IT appeared first on ITDigest.

Also Read: Manulife Unveils Unified Enterprise AI Platform to Accelerate Global Operational Efficiency and Innovation

With no implementation needed, eligible startups can connect bank accounts, create invoices, and start viewing financial information in less than ten minutes. As companies grow and their financial requirements become more complex, QuickStart provides a path to NetSuite’s broader enterprise resource planning platform without requiring them to start over. “As a technology founder, I know from experience that building a company shouldn’t mean becoming a finance expert,” said Evan Goldberg, founder and executive vice president, Oracle NetSuite. “QuickStart is designed to handle more of the routine financial work, surface what actually needs a founder’s judgment, and provide a financial foundation that can grow with the business, making NetSuite the first and last business system they will ever need.”

Read More: NetSuite Introduces Free AI-First Financial Platform That Helps Startups Go From Idea to IPO

The post NetSuite Unveils Free AI-First Financial Platform to Accelerate Startup Scale from Idea to IPO appeared first on ITDigest.