To solve this challenge, the data company for trusted enterprise AI – Cloudera, released the Workflow Data Fabric Zero-Copy Connector for ServiceNow. In doing so, they enabled the extraction and transformation of the ServiceNow data in the Cloudera data fabric without extracting it first. In essence, Cloudera helped create a bridge between action data and insight data.

Real-Time Intelligence via Zero-Copy Architecture

Zero-Copy Connector is the key technology behind this press release that considers ServiceNow as a live component of the Cloudera Data Lakehouse. There is no creation of an additional copy of the data, but only a query of the data where it exists.

Main technical capabilities of the connector are:

Virtual Data Integration: Data scientists have an option to combine ServiceNow tables (for example, tickets and asset management information) with the historical data in Cloudera via SQL without data migration.

Metadata Management Across Multiple Platforms: Thanks to Cloudera SDX (Shared Data Experience) the consistent application of security and governance policy in an integrated manner for all types of data and according to GDPR, HIPPA, and other regulatory frameworks.

Also Read: PwC and OpenAI Partner to Build AI-Native Finance Function, Reshaping the Future of Fintech

Saving Cloud Costs: The elimination of large volumes of data transfer and duplication results in lower costs.

Near-Zero Latency: Analysts work with the most current operational data, allowing for “now-casting” rather than “forecasting” based on yesterday’s reports.

Impact on the Data Science Industry

This collaboration marks a significant transition in the Data Science sector, moving the needle from “Experimental AI” to “Operational AI.”

1. Accelerating the Lifecycle of Machine Learning (ML) For data scientists, 80% of the job is often described as “data janitoring”-the tedious process of cleaning and moving data. Zero-copy architecture removes a massive portion of this burden. By gaining instant access to ServiceNow’s rich operational datasets, data science teams can build, train, and deploy ML models much faster. Whether it’s predicting IT outages or identifying patterns in customer service friction, the time-to-insight is reduced from weeks to minutes.

2. The Rise of “Agentic” Data Science As the industry moves toward Agentic AI-where AI agents take autonomous actions-the need for real-time data is paramount. A data science model that predicts a supply chain disruption is only useful if it can trigger a workflow. By integrating Cloudera’s analytical power with ServiceNow’s workflow engine, the industry is creating a “closed-loop” system where data science doesn’t just inform a report; it powers a self-healing enterprise.

3. Enhanced Governance for AI Training Training AI models on “shadow data” or ungoverned extracts is a major risk for modern businesses. The Zero-Copy Connector ensures that the data used for training remains within the secure boundaries of the enterprise fabric. This allows data scientists to build more trustworthy models that are grounded in verified, governed, and high-fidelity operational data.

Effects on Businesses Operating in the Industry

The ramifications of the Cloudera announcement have much wider implications, serving as a framework for the “Intelligent Enterprise” in 2026:

Improved Operations through “Proactive Service”: Companies can shift from a reactionary support process to proactive service. Through the analysis of ServiceNow log files in real-time using Cloudera, organizations can detect when a particular server is about to fail or when customers complain about the same issue.

Data Democratization: It no longer requires you to be a data engineer to analyze complex workflows. By providing companies with a way to access ServiceNow data through SQL queries and Cloudera BI tools, firms can empower more individuals—from product managers to HR managers-to make informed data-driven decisions.

Resource Optimization: With ETL pipelines being phased out, IT and data engineering staff members can be reassigned to more value-added initiatives, such as developing AI agents and enhancing data quality.

Resilience in a Volatile Market: In a fluctuating economy, the ability to see the “health” of an organization’s workflows in real-time is a strategic moat. Companies that leverage this zero-copy integration will be more agile, responding to internal and external shocks with precision.

Conclusion

Cloudera’s introduction of the Zero-Copy Connector for ServiceNow marks a groundbreaking occasion in the “Data-to-Action” transformation. By removing the inefficiencies of data transfer, Cloudera does more than offer yet another tool-it changes the very nature of the contemporary data ecosystem itself. For the community of data science practitioners, this marks a freeing from the limitations of siloing data. For the business entity, it is nothing less than the building blocks of an autonomous company-a company driven by insights and action.

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Cutting Out the Friction from the “Cab-to-Cash” Process

Historically, factoring has been characterized by paper-based documents and inefficient communications. With an advanced architectural design that places users at the forefront, the new Workflow AI for Factors solution streamlines the entire workflow, including document ingestion, processing, approval, and financing.

As a neutral technology provider, Transflo ensures that this increased efficiency does not come at the cost of data security or relationship integrity.

“Our goal was simple: remove complexity from factoring,” said Renee Krug, CEO of Transflo. “We’ve combined automation, intelligent workflows, and a clean user experience to create a platform that is faster, more accurate, and significantly easier to use. This is a meaningful step forward for our customers and the industry.”

Also Read: Operant AI Introduces Endpoint Protector to Address Enterprise AI Security Blind Spots

“Our customers value confidentiality and trust,” added Krug. “Because Transflo is a neutral technology partner, our customers can confidently run their operations on our platform, knowing their data is protected and their business relationships stay intact.”

A Smarter, Scalable Factoring Engine

Workflow AI for Factors introduces a suite of intelligent capabilities designed for high-velocity financial operations:

End-to-End Automation: Custom AI agents carry out document capturing and data extraction, leading to greatly decreased manual input.

User-friendly Interface: An intuitive UI enables employees to process high volumes of transactions with no need for extensive training.

Built-in Validation Engine: A powerful built-in engine verifies invoices’ data in real-time, thus minimizing the chances of fraud or mistakes happening during the process.

Quick Payment Approval: The automation of the validation process makes it possible for factors to make decisions regarding funding in record time.

Scalability for Enterprises: The system is capable of processing numerous transactions in compliance with the high-performance standards of the current transportation industry.

“This platform is about efficiency and confidence and speed of funding,” said Bill Vitti, President and Chief Revenue Officer of Transflo. “Customers can trust that transactions are verified, accurate, and processed quickly, without the delays and errors that have historically impacted the industry.”

Live Demonstrations at IFA 2026

The launch coincides with the International Factoring Association (IFA) 2026 Conference in Nashville. Attendees can visit the Transflo team at Booth #12 from May 6-8 to experience live walkthroughs of the Workflow AI platform and see how it is redefining speed and precision in freight factoring.

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Governing AI agents is critical, now more than ever, as enterprises accelerate their deployment of agentic technology across systems, teams, and tools at unprecedented speed. Realizing the full value of this investment requires a unified approach to governance, identity and permission management, and control that spans every platform across which AI agents operate. ServiceNow is working with partners like Microsoft to give enterprises the visibility to see AI agents, models, tools, and prompts in their environment, which gives them the control to govern them consistently and the interoperability to put them to work across the tools employees already use.

“ServiceNow and Microsoft are helping organizations maximize value from every AI investment,” said Jon Sigler, executive vice president and general manager, AI Platform at ServiceNow. “With this expanded integration, customers can securely apply governance across ServiceNow and Microsoft environments with integrated visibility and controls, while putting ServiceNow Autonomous Workforce to work across the Microsoft 365 environment. This is an example of what it means to put AI to work at enterprise scale, with the trust and interoperability that business transformation requires.”

Also Read: Wrike Connects Governed AI To Enterprise Workflows, Now Available On OpenAI GPT Store

“One of the most important things we can do for enterprises is bring intelligence and action together in a secure, connected way,” said Charles Lamanna, executive vice president, Copilot, Agents, and Platform at Microsoft. “That’s why we’re excited to collaborate with ServiceNow, bringing their AI expertise into Microsoft 365 to add workflow intelligence on top of that secure foundation. Together, we’re helping customers act on insights more quickly and drive meaningful outcomes across their business processes.”

Unified control for a multi-agent enterprise

ServiceNow AI Control Tower already connects to Microsoft Foundry and Copilot Studio to discover AI assets, enforce governance policies, and drive consistent oversight. The new AI Control Tower integration with Microsoft Agent 365 expands these capabilities by extending visibility and governance insights across Microsoft Agent 365’s AI agent ecosystem. This gives IT and operations teams enhanced visibility into agent activity across ServiceNow and Microsoft ecosystems, regardless of where these agents were built or deployed.

Through the integration, ServiceNow AI Control Tower gives administrators the ability to review and approve ServiceNow AI specialists prior to submission to the Microsoft Agent 365 Marketplace, where Microsoft publishing and policy controls apply. This helps ensure that every ServiceNow AI specialist that interoperates with the Microsoft 365 environment has been vetted, permissioned, and authorized for deployment.

ServiceNow AI specialists come to work across Microsoft 365 applications

In the Microsoft Agent 365 Marketplace, a ServiceNow AI specialist will appear in the org chart as a digital employee with defined roles, permissions, and accountability.

This allows the AI specialists to be able to take actions such as drafting a Word document, responding to email messages in Outlook, or acting on an assigned comment in PowerPoint, subject to Microsoft 365 permissions, identify, and admin policy controls, while consumption is tracked across both ServiceNow’s and Microsoft’s metered usage models.

SOURCE: Businesswire

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CyborgDB is the end-to-end-encrypted vector database purpose-built for regulated industries, allowing organizations to build and scale high-performance AI systems without compromising security or compliance. Built for real-world AI, CyborgDB possesses sub-millisecond latency for searching hundreds of millions of vectors without exposing a single byte of plaintext.

Security organizations like OWASP have warned that vectors and embeddings represent a fast-emerging area of vulnerability, while Fortune Business Insights predicts that the vector database market will grow to nearly $18 billion by 2034. This partnership underscores a broader industry shift in focus from AI that works to AI that works securely in production.

Also Read: OPAQUE Acquires Abu Dhabi-Developed Cryptographic AI Technology

“AI adoption is accelerating, but security has lagged behind,” said Nico Dupont, Founder and CEO of Cyborg. “This partnership with Austin AI shows that secure, production-ready AI infrastructure is not just possible – it’s already being deployed.”

Austin Artificial Intelligence is widely recognized as a leading consultancy, partnering with organizations to embed AI across strategy, operations, and decision-making. This partnership reduces the friction caused between AI moving into production and security being a productivity inhibitor, embracing secure AI as the industry standard.

“Our customers want to deploy AI on sensitive data without introducing new risk,” said Robert Corwin, CEO of Austin Artificial Intelligence. “Partnering with Cyborg allows us to confidently bring end-to-end security into production AI systems, giving enterprises the confidence to move faster and scale AI safely.”

SOURCE: Businesswire

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“For decades, networking ran in the background. Today, it’s the central nervous system, determining how fast you can move, how much you spend, and whether your AI investments produce value,” said Kate Johnson, CEO of Lumen Technologies. “With Alkira, Lumen will pair the trusted network for AI with a cloud-native control plane, which will give customers a programmable network designed for the AI era. It’s what the market needs, and it’s what we’re building at Lumen.”

The Programmable Network Imperative

AI is reshaping how enterprises operate and how their networks must perform. More than half of internet traffic today is automated traffic generated by software systems rather than human users. Networks have to be big enough, fast enough, intelligent enough, and secure enough to keep up. Yet many enterprise networks remain static, manually configured, and fragmented across providers. Lumen is working to define a new category of enterprise networking: one built on world-class physical infrastructure, a programmable network, and a connected ecosystem of clouds, applications, and partners.

Also Read: Essen Health Care Launches RADIN Health All-In-One RIS and PACS Cloud Platform

Alkira to Accelerate Lumen’s Digital Platform Development

Alkira will accelerate Lumen’s vision of a programmable network with a single control plane that orchestrates connectivity beyond Lumen’s network across data centers, multiple clouds, partner ecosystems, and on-prem environments. Combined with Lumen’s core assets, this is expected to deliver strategic value across multiple fronts:

• Platform acceleration: Once acquired and integrated, the Alkira product will unify Lumen’s on-net and off-net services, cloud on-ramps, and Multi-Cloud Gateway into a single programmable platform, advancing Lumen’s roadmap by several years and substantially completing Lumen’s digital architecture.
• Expanded addressable market: Lumen’s Network-as-a-Service (NaaS) business today is concentrated in premises-to-cloud (north-south) connectivity. Alkira is positioned to accelerate Lumen’s move into cloud-to-cloud and data center-interconnect (east-west) connectivity — the fastest growing segment of enterprise networking. Lumen estimates Alkira’s global footprint and cloud-native capabilities will bring its total addressable market to approximately $70 billion.
• International reach: Lumen owns the fiber where ownership compounds value, the dense U.S. backbone closest to its customers. Alkira’s carrier-agnostic design will extend Lumen’s programmable network internationally over local infrastructure, broadening Lumen’s footprint without the capital intensity of building fiber in every geography.
• Deeper partner integration: Alkira’s API‑driven marketplace presence will help strengthen integration across Lumen’s connected ecosystem of clouds, data centers, and technology partners and will fast-track the selling and provisioning of Lumen Validated Designs.
• World-class talent: The proposed acquisition will add deep cloud-native control plane, cloud networking, and software-at-scale expertise to accelerate the delivery of consumption-based networking and software-defined cloud interconnects.

Today, Alkira serves enterprise customers across financial services, technology, retail, healthcare, and manufacturing sectors globally. Upon closing the transaction, Lumen plans to begin offering Alkira’s core east-west connectivity services to its enterprise base, with deeper platform integration to follow.

SOURCE: Businesswire

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As enterprises increasingly migrate to distributed cloud environments, traditional DDoS mitigation has struggled to keep pace with cloud and distributed infrastructure adoption. Standard ISP solutions often resort to dropping all traffic and taking the service offline to protect the network, while external third-party providers force a “security detour” that reroutes traffic through public infrastructure, introducing significant latency and complexity.

Megaport DDoS Protection removes these challenges by integrating fabric-native protection directly into the Megaport network, closing the gap between basic ISP tools and complex enterprise-grade security solutions. By keeping protection inline with the private network path, traffic stays on its intended route without being diverted, maintaining peak performance even while under attack.

Also Read: Fathom Secures Strategic Investment From CVS Health Ventures to Accelerate Enterprise-Wide Autonomous Coding

“Network resilience is now a core infrastructure requirement, not an optional extra,” said Michael Reid, CEO at Megaport. “Moving DDoS protection inside the network layer rather than treating it as a bolt-on service eliminates the traditional trade-offs between security, performance, and cost. It takes users less than a minute to deploy Megaport Internet, and its native DDoS protection works to keep digital services available and high-performing regardless of external threats.”

Key features and benefits of Megaport DDoS Protection include:

• Fabric-Native Mitigation: Unlike external providers, Megaport filters traffic within its own network, eliminating the need for traffic redirection to external scrubbing centers, reducing latency, and maintaining control.
• Rapid Deployment: The capability is fully self-service and can be easily added via the Megaport Portal in under 60 seconds. Users get smarter protection almost instantly thereafter.
• Targeted Protection: Mitigation occurs at the host/IP level. Only malicious traffic is filtered while the rest of the network continues to operate normally.
• Simplified Pricing: Costs are aligned to connection capacity rather than the size or frequency of attacks, removing the unpredictability of attack-based cost models that are often associated with legacy providers.
• Operational Simplicity: Pre-configured protection profiles reduce the need for manual tuning while still distinguishing between legitimate traffic surges and attack patterns.

The service is designed for environments where downtime has immediate financial and brand impact, whether they are handling high-traffic or highly critical processes. Megaport DDoS Protection offers both passive and active mitigation modes, specifically focusing on Layer 3 and Layer 4 attacks.

The launch of DDoS Protection is part of Megaport’s evolution toward owning the full connectivity experience for its customers, providing a platform where performance and protection are managed together as core components of network infrastructure.

SOURCE: Businesswire

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The formation of the Advisory Board reflects Ibex’s strategic expansion into biopharma and its commitment to partnering with industry leaders to advance AI-driven biomarker development and precision diagnostics. As oncology rapidly evolves toward antibody-drug conjugates (ADCs) and other targeted therapies, the need for precise, reproducible biomarker quantification and scoring has become increasingly critical. The Board will provide strategic and scientific guidance as the company expands its Biopharma Services offering to support partners across the full lifecycle, from early biomarker and AI-powered companion diagnostics (CDx) development through clinical validation and global deployment via Ibex’s established clinical market.

“The complexity of cancer biology today requires more than just research prototypes; it demands practical, rigorous tools that can transition seamlessly from the lab to the clinic,” said Joseph Mossel, Co-Founder and President of Ibex Medical Analytics. “We are grateful to have Dr. Tarantino and Dr. March join us. Their deep expertise ensures Ibex remains grounded in the practical needs of pharmaceutical development. By leveraging our established clinical network, we are able to reduce risk in clinical development and expand market reach for our partners, moving beyond early-stage AI concepts toward reliable, clinical-grade deployment.”

Also Read: IonQ Launches Commercial InSAR Capability, Enabling Automated, Millimeter-Scale Earth Monitoring

Ruth March, PhD, OBE, FMedSci, FRSB, joins the board following a transformative tenure as Senior Vice President of Precision Medicine and Biosamples at AstraZeneca. Dr. March is a pioneer in the field, having led the approval of more than 70 companion diagnostics for six launched drugs across major global markets. Her career is marked by industry firsts, including the world’s first approval of circulating tumor DNA (ctDNA) to guide therapy and the development of digital pathology biomarkers as companion diagnostics. An expert in population genomics, she also initiated AstraZeneca’s genomics initiatives, utilizing machine learning to analyze millions of genomes. Her contributions to the life sciences were recognized with an OBE for her leadership during the COVID-19 pandemic.

“In my role at AstraZeneca, I saw firsthand the transformative potential of AI to accelerate diagnostics and advance precision medicine,” said Dr. March. “I worked with Ibex for many years and now feel privileged to continue to support them in an advisory role. Their technology has the potential to deliver precise, reproducible biomarker quantification and scoring, combined with a proven global clinical footprint that enables rapid translation from development to real-world use.”

Paolo Tarantino, MD, PhD, is a distinguished breast medical oncologist and clinical researcher. He currently serves as a Research and Clinical Fellow at the Dana-Farber Cancer Institute and Harvard Medical School. Dr. Tarantino’s work is at the forefront of the ADC revolution, specifically focusing on mechanisms of action and the development of novel predictive biomarkers to increase treatment precision. A prolific academic, he has published over 100 scientific articles and is a key contributor to numerous clinical trials and preclinical investigations aimed at optimizing outcomes for breast cancer patients.

Ibex’s expanded Biopharma Services offering builds on a proven pharma partnership model, exemplified by the development of Ibex Breast HER2, which progressed from algorithm development through clinical validation, regulatory certification, and real-world deployment using Ibex’s end-to-end capabilities. By combining robust quantification and customizable scoring approaches with a regulatory-grade platform and global clinical deployment footprint, Ibex enables pharmaceutical partners to develop, validate, and scale AI-driven diagnostics with confidence, from early development through commercialization.

SOURCE: Businesswire

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“Diversified has strong fundamentals, an exciting growth agenda and a leadership team with the ambition and urgency to match,” said Tripathi. “This is exactly the kind of opportunity I look for: a well-run business with the scale, talent and commitment to keep raising the bar, a long-term vision for market leadership and a clear understanding that technology can drive meaningful enterprise value.”

At Diversified, Tripathi will lead the company’s enterprise technology strategy, overseeing global IT across applications, cybersecurity, data and analytics, digital innovation, infrastructure and business systems. His role will include strengthening the digital and data foundation needed to support AI enablement, improve operational efficiency, and ensure technology serves as a true driver of commercial value and long-term competitive advantage. Tripathi, who officially joined the company yesterday, reports to CEO Paul Lidsky and serves on Diversified’s executive leadership team.

Also Read: Ondaro Appoints Ben Durham-Kilcullen as First Chief AI Officer

“As Diversified continues to scale globally, technology must be a core driver of operational excellence, customer experience and long-term growth,” said Lidsky. “Viral’s track record leading complex IT modernization programs, building global delivery models and using data and AI to improve business performance aligns directly with where we are headed as a company. I’m confident he will be a strong partner to our leadership team as we strengthen the digital foundation that supports our people, our clients and the future of our business.”

Before joining Diversified, Tripathi served as CIO of C1 (formerly ConvergeOne), leading enterprise IT transformation, including a cloud ERP program, establishing data analytics and scaling the company’s global IT capability center. Prior to that, he was CTO and then Global CIO at Ascendion (formerly Collabera), a technology engineering and talent solutions group. There he enabled revenue growth via technology modernization and data-driven insights, rapidly deploying core systems and embedding generative AI into core platforms to drive productivity.

Additionally, Tripathi spent more than seven years of his career at KPMG, where he advised Fortune 500 C-level leaders and private equity sponsors on IT strategy, M&A integration, digital transformation across the U.S. and Europe and large-scale operational transformation.

SORUCE: Businesswire

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The partnership focuses on embedding AI agents across core financial workflows, including planning, forecasting, procurement, payments, treasury, tax, and reporting. These AI systems are designed to automate repetitive processes, generate insights, and enhance decision-making while maintaining governance and control through human supervision.

Unlike traditional automation tools, the AI agents being developed through this collaboration are intended to operate dynamically across systems, learning and improving over time. The initiative is also grounded in real-world implementation, with early use cases being tested within OpenAI’s own finance operations before being scaled to enterprise clients.

At its core, the collaboration reflects a broader industry trend: the transition from experimental AI deployments to fully integrated, enterprise-wide systems. By combining PwC’s domain expertise in finance and consulting with OpenAI’s advanced AI capabilities, the initiative aims to redefine the “office of the CFO” into a more strategic, data-driven function capable of delivering predictive insights rather than just historical reporting.

What does this mean for the fintech industry?

The implications for the fintech sector are profound. Fintech companies, which already operate at the intersection of finance and technology, are likely to accelerate their adoption of agentic AI models to remain competitive. This development sets a new benchmark for operational efficiency, where AI is no longer a supporting tool but a core component of financial infrastructure.

First, the introduction of AI-native finance functions could significantly reduce operational costs by automating labor-intensive processes such as reconciliation, compliance checks, and financial reporting. This enables fintech firms to allocate resources toward innovation and customer-centric services rather than back-office functions.

Second, the ability of AI agents to continuously analyze large datasets in real time will enhance risk management and fraud detection capabilities. Financial institutions can move from reactive to proactive strategies, identifying anomalies and potential risks before they escalate. This aligns with broader industry efforts to strengthen governance and improve decision-making through AI-driven insights.

Third, the collaboration highlights a shift toward “agent ecosystems,” where multiple AI systems work together seamlessly across business functions. For fintech companies, this could lead to the development of more integrated platforms that combine payments, lending, compliance, and analytics into unified solutions, ultimately improving customer experiences and operational agility.

Also Read: Customers Bank and OpenAI Partner to Build an AI-Native Commercial Banking Model 

Beyond fintech, the impact on businesses across industries is equally significant. Organizations that adopt AI-native finance functions can expect faster financial close cycles, more accurate forecasting, and improved strategic planning. This transformation also redefines the role of finance professionals, shifting their focus from manual processing to higher-value activities such as analysis, strategy, and innovation.

However, the transition is not without challenges. Companies must address concerns related to data security, regulatory compliance, and ethical AI use. The emphasis on human oversight in the PwC-OpenAI model underscores the importance of maintaining accountability and transparency as AI systems become more autonomous.

In the long term, this collaboration may serve as a blueprint for how enterprises integrate AI into critical business functions. As AI adoption continues to scale, companies that successfully combine technology with governance and human expertise are likely to capture a disproportionate share of the value generated by AI.

Ultimately, the PwC and OpenAI partnership represents more than just a technological advancement it signals a fundamental shift in how financial operations are designed and executed. For the fintech industry and beyond, the message is clear: the future of finance will be AI-native, adaptive, and deeply integrated into the fabric of enterprise decision-making.

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With AI adoption accelerating across departments such as HR, finance, engineering, and customer operations, enterprises are increasingly relying on AI assistants, coding agents, and MCP-connected tools to handle sensitive data and automate workflows. However, this rapid adoption has introduced new vulnerabilities, particularly from “shadow AI” tools unsanctioned or poorly governed applications that operate outside traditional security visibility.

Unlike legacy security solutions such as endpoint detection and response (EDR), CASBs, and network monitoring tools, which focus on processes and traffic, modern AI systems operate within encrypted environments and semantic layers that remain largely invisible to conventional defenses. This creates a significant security gap, especially as AI agents gain the ability to reason, act, and interact autonomously within enterprise systems.

“Security leaders are waking up to the reality that their AI exposure doesn’t live in one place it lives everywhere their employees and agents do,” said Vrajesh Bhavsar, CEO and Co-Founder of Operant AI. “The endpoint is where AI actually meets the workforce. It’s been the largest blind spot in the enterprise security stack and it’s the gap we built the Operant Endpoint Protector to close.”

Addressing the Rise of Shadow AI and Agentic Risks

The emergence of AI-powered coding environments and agent-based workflows has significantly improved productivity but also introduced new threat vectors. These include prompt injection attacks, data leakage, unauthorized access to sensitive systems, and real-time execution risks within AI-driven processes. MCP, which acts as the connective layer enabling AI agents to interact with tools and services, further expands the attack surface by allowing actions across trusted and encrypted channels.

Operant Endpoint Protector is designed to counter these risks by providing continuous visibility and control over AI interactions. The solution enables enterprises to monitor every AI prompt, MCP server, plugin, and agent activity in real time ensuring that even previously hidden or unmanaged AI tools are brought under governance.

Also Read: Malwarebytes Integrates Real-Time Scam Detection into Claude AI Conversations 

Core Capabilities for Enterprise-Grade AI Security

The platform delivers a comprehensive set of features tailored to the complexities of modern AI environments:

• Enterprise AI & MCP Registry: A centralized inventory that maps all sanctioned and shadow AI tools, MCP servers, and integrations, offering visibility into usage patterns and risk profiles.
• Real-Time Detection and Agent Monitoring: Continuous tracking aligned with emerging AI security frameworks to identify threats such as prompt injections, identity anomalies, and data exfiltration attempts within encrypted channels.
• Inline Data Protection: Enforcement of policies for sensitive data such as PII, PCI, and PHI, including automatic redaction of confidential information during AI interactions.
• Access and Execution Governance: Role-based access controls and runtime guardrails that ensure AI agents operate strictly within authorized boundaries.
• Endpoint-Native Code Protection: Built-in defenses against code injection and malicious execution attempts, with controls such as rate limiting and token management.

These capabilities are supported by a compliance-focused architecture that includes audit logging and data sovereignty controls, making the solution suitable for highly regulated industries such as financial services, healthcare, and government sectors.

Built for Scale, Privacy, and Enterprise Deployment

Operant Endpoint Protector is delivered as a native application compatible with macOS, Windows, and Linux, enabling seamless deployment across enterprise environments via standard device management workflows. It integrates with identity providers (IdPs) to align AI governance with existing access management frameworks, ensuring consistent enforcement of security policies across users, roles, and AI interactions.

Additionally, the platform supports private deployment models, including hybrid and private-SaaS configurations, allowing organizations to maintain full control over sensitive data and AI activity logs. This is particularly critical for enterprises operating under strict data residency and compliance requirements.

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