George Crump

June 11, 2025 by George Crump

Eliminating enterprise AI deployment barriers has become critical, as 70% of enterprise AI projects fail due to infrastructure complexity. However, organizations cannot afford to delay private AI adoption in today’s competitive landscape. As we detailed in our recent Blocks and Files analysis, traditional enterprise AI solutions create significant barriers that prevent broader adoption. These roadblocks—from infrastructure complexity to hardware lock-in—have limited private AI deployment to the largest corporations, which have the resources and expertise to overcome them.

VergeOS, with integrated VergeIQ, directly addresses every identified barrier through a fundamentally different approach: treating AI as a native infrastructure resource rather than a separate technology stack. By integrating generative AI capabilities directly into the unified data center operating system, VergeOS successfully eliminates the enterprise AI deployment barriers that have historically prevented mid-sized enterprises from deploying private AI.

Eliminate Enterprise AI Complexity Through True Integration

Traditional AI deployments require managing multiple software layers—such as containers, Kubernetes, orchestration platforms, and specialized AI frameworks—each adding complexity and requiring dedicated expertise. Unlike bolt-on AI solutions that create additional management overhead, VergeIQ operates as a native VergeOS service, eliminating the operational complexity of managing separate AI infrastructure.

The result is dramatic simplification: instead of requiring specialized AI infrastructure expertise, organizations can deploy and manage enterprise AI using existing IT skills and established operational procedures. This approach represents a fundamental advancement in eliminating enterprise AI deployment barriers through architectural convergence.

Built-In Capabilities Replace Separate Installations

Once VergeOS is installed, VergeIQ is immediately available as a native resource alongside virtualization (VergeHV), storage (VergeFS), and networking (VergeFabric). Organizations can deploy and utilize popular large language models like LLaMa, Qwen, Phi, and Gemma within minutes, without requiring additional software installations or complex configurations. This integration means IT teams manage AI workloads using the same unified interface they use for all infrastructure functions.

Eliminating Enterprise AI Deployment Barriers — Install from a Curated List of Models

VergeIQ includes comprehensive generative AI capabilities as part of the base VergeOS installation. Organizations don’t need to purchase, install, or integrate separate AI platforms, eliminating both the software licensing costs and integration complexity that plague traditional approaches.

Immediate and Practical Enterprise AI Value

Day one capabilities include document analysis of PDFs, spreadsheets, and text files; secure auditing and optimization of proprietary source code; automated infrastructure script generation; tailored enterprise content creation; and comprehensive infrastructure intelligence. All capabilities are available immediately upon deployment of VergeOS.

Additionally, VergeIQ enables experimentation without token-based pricing penalties. Organizations can set up secure, isolated virtual labs for testing and validation without requiring dedicated GPU resources, accelerating innovation while reducing operational risk.

This built-in approach ensures seamless compatibility and performance optimization, as VergeIQ is explicitly designed for the VergeOS environment rather than being bolted onto existing infrastructure.

Single Storage System Handles All Enterprise AI and Business Workloads

Traditional AI deployments create storage complexity by requiring separate, specialized storage systems for different workload types—high-performance storage for training, medium-performance for inference, and archival storage for long-term data retention. This specialization creates significant infrastructure duplication and operational overhead.

VergeFS, VergeOS’s integrated software-defined storage, provides unified storage that handles all AI workload requirements within a single system. The intelligent tiering capabilities automatically optimize data placement based on access patterns and performance requirements, eliminating the need for separate storage infrastructures.

Organizations can leverage their existing storage investments while accommodating AI requirements, dramatically reducing both capital expenses and operational complexity. VergeFS scales seamlessly from initial AI pilots to full production deployments without requiring architectural changes or additional storage systems.

Vendor-Neutral Hardware Approach Prevents Lock-In

VergeIQ provides complete vendor neutrality for compute hardware, supporting GPUs from multiple vendors or functioning on CPU-based systems. This flexibility ensures organizations aren’t locked into specific hardware vendors or dependent on GPU availability for AI functionality.

The platform features intelligent GPU orchestration that maximizes hardware efficiency across all vendors, while CPU-based AI capabilities ensure continued operation even when GPU resources are unavailable. Organizations can start with existing hardware and add GPU acceleration as needed, or change GPU vendors without architectural disruption.

This approach protects organizations against the rapid changes in AI hardware markets, allowing them to adopt new technologies as they emerge without being constrained by their initial infrastructure choices. Vendor neutrality is essential for eliminating enterprise AI deployment barriers that create long-term technological dependencies.

Enterprise AI Security Without Complexity

VergeOS includes comprehensive security features as part of its firmware-style operating environment. These built-in capabilities include network segmentation through VergeFabric, end-to-end data encryption, secure authentication systems, comprehensive audit logging, and role-based access controls.

For AI workloads, this means sensitive enterprise data remains secure within organizational boundaries without requiring additional security appliances or complex configurations. The integrated security model ensures that AI deployments meet regulatory compliance requirements while maintaining the operational simplicity that makes private AI practical for organizations of all sizes.

Unlike traditional approaches that require layering security solutions on top of AI platforms, VergeOS provides enterprise-grade security as a fundamental platform characteristic.

Broader IT Problem Resolution

VergeOS, combined with VergeIQ, addresses multiple critical IT challenges simultaneously. For organizations evaluating VMware alternatives due to Broadcom’s pricing and licensing changes, VergeOS offers more than an alternative; it modernizes the entire infrastructure without requiring hardware replacement.

The same installation that replaces VMware infrastructure provides comprehensive generative AI capabilities, storage modernization through VergeFS, and advanced networking through VergeFabric. This unified approach maximizes organizational value while minimizing the complexity of managing multiple infrastructure solutions. Log in to our case studies library to learn how the transition has gone for our customers.

Alternatively, organizations can deploy VergeOS alongside existing VMware infrastructure to immediately gain AI capabilities, then transition away from VMware when timing aligns with their broader infrastructure strategy. This unified approach is central to eliminating enterprise AI deployment barriers while addressing broader requirements for infrastructure modernization.

Implementation Path for Enterprise AI Success

VergeOS with VergeIQ removes the traditional barriers that have prevented broader enterprise AI adoption. By treating AI as a native infrastructure resource, organizations gain immediate access to powerful generative AI capabilities without the complexity, cost, and operational overhead of traditional approaches.

The platform’s vendor-neutral approach, integrated security, unified storage, and immediate value delivery create a practical path for organizations to deploy private AI that meets enterprise requirements while remaining operationally manageable.

Organizations can start with pilot deployments using existing hardware, validate business value, and then scale confidently in their architectural choices, eliminating the typical enterprise AI risk of significant upfront investments with uncertain outcomes.

For organizations seeking to leverage the transformational potential of private AI without the traditional deployment barriers, VergeOS with VergeIQ provides a comprehensive solution that makes enterprise AI practical, secure, and immediately valuable.

See VergeIQ in Action: Live Demonstration Tomorrow

Ready to see how VergeOS with VergeIQ succeeds in eliminating enterprise AI deployment barriers in real-time? Join us tomorrow, Thursday, June 12th at 1:00 PM ET, for our world-premier VergeIQ webinar and demonstration.

Watch our product experts showcase how VergeIQ delivers enterprise-ready AI deployments in minutes, not months. You’ll see live demonstrations of curated Large Language Models, such as LLaMa, Falcon, and DeepSeek, running with near-bare-metal performance, GPU pooling and clustering capabilities, and disconnected, sovereign AI solutions.

This comprehensive demonstration will show how VergeIQ transforms private AI from a complex, resource-intensive challenge into a simple, immediate infrastructure capability.

Register now for tomorrow’s live demonstration and discover how VergeOS with VergeIQ can deliver immediate AI value within your existing infrastructure strategy.

Filed Under: AI Tagged With: AI, Enterprise AI

June 5, 2025 by George Crump

Using existing frameworks that enable the creation and use of AI agents—that’s the core benefit of VergeIQ’s OpenAI-compatible service. With this capability, VergeIQ, makes enterprise-grade generative AI secure, manageable, and easily accessible—not just for developers, but for anyone who uses familiar, off-the-shelf AI software tools such as VS Code, Continue, and Anything LLM.

Fully integrated within VergeOS—the comprehensive data center operating system and leading VMware alternative—VergeIQ delivers immediate, seamless access to powerful generative AI capabilities without additional setup. Once VergeOS is installed, VergeIQ is ready to go. Enterprises can quickly deploy secure, locally hosted large language models (LLMs), allocate GPU resources dynamically, and interact with sensitive internal data entirely within their own data centers. With VergeOS, AI is on-premises, private, and secure.

VergeIQ’s OpenAI-compatible service Enables Familiar Tools

By providing an OpenAI-compatible router or service, VergeIQ removes the typical hurdles to private AI adoption. Users can seamlessly migrate their workflows to VergeIQ. No new tools, retraining, or significant code changes are needed—simply point your existing applications to VergeIQ’s internal API endpoint and begin working.

For business analysts, content creators, support specialists, and IT teams, this means quickly integrating powerful generative AI into everyday workflows without any steep learning curves.

Developers already familiar with OpenAI’s libraries and documentation can start building applications on VergeIQ without having to learn a new interface or rewrite their code. The only change required is pointing applications to a new, internal API endpoint.

If you don’t use any of these tools, then don’t worry, VergeOS with VergeIQ includes everything you need to leverage AI to understand your data and create new content.

Complete On-Premises Security and Control

VergeIQ’s OpenAI-compatible service ensures your sensitive data never leaves your environment. Unlike cloud-based AI services that transmit data externally, VergeIQ operates entirely within your premises. This complete on-premises deployment capability allows enterprises to run fully disconnected—no internet or cloud connectivity required—ensuring absolute control, full regulatory compliance, and secure management of confidential data.

On-premises operations not only enhance privacy but also dramatically reduce latency, providing real-time responses and faster insights.

Behind-the-Scenes Intelligence, Effortless Use

Underneath the familiar OpenAI-compatible interface, VergeOS intelligently manages all AI operations, including GPU orchestration, automatic model loading, resource allocation, and infrastructure optimization. Administrators can rely on VergeOS to dynamically scale resources, minimize manual intervention, and maximize performance without the complexities typically associated with on-premises AI deployments.

The result is enterprise-grade AI that’s easy to manage for IT teams, providing cloud-like simplicity with the full security and control of local infrastructure.

VergeIQ’s OpenAI-Compatible Service Enables Predictable Costs and Unlimited Usage

Unlike public cloud AI models that impose ongoing per-token or subscription fees, VergeIQ delivers predictable, flat-rate costs as part of VergeOS. Organizations aren’t penalized as their AI adoption grows. Enterprises can scale their AI use internally without escalating expenses, ensuring sustainable growth, cost-effective operations, and predictable budgeting.

Local AI Infrastructure with Cloud Convenience

VergeIQ’s OpenAI-compatible service offers a best-of-both-worlds approach, combining the security and privacy of fully private, on-premises infrastructure with the simplicity and familiarity of cloud-based AI interfaces. VergeOS provides enterprises a trusted, secure, fully controlled AI environment that’s immediately accessible and easy to use.

With VergeIQ, organizations gain rapid, secure AI capabilities without sacrificing convenience, compatibility, or performance.

Examples of Tools Compatible with VergeIQ’s OpenAI-Compatible Service

Category	Tool	Description
Desktop Applications	LM Studio	Local AI model runner with OpenAI-compatible API.
	Ollama	CLI tool for local model deployment with built-in API server.
	GPT4All	Desktop application connecting to various local or remote backends.
	Jan	Open-source ChatGPT alternative with API integration.
	AnythingLLM	Application for document-based chat and AI model management.
Web Interfaces	Open WebUI	Web interface for managing OpenAI-compatible API models.
	ChatGPT Next Web	Self-hostable, open-source alternative to ChatGPT.
	LibreChat	Open-source ChatGPT alternative supporting multiple API providers.
	Chatbot UI	Minimalist web-based AI interface supporting various APIs.
Development Tools	Continue.dev	VS Code/JetBrains extension providing AI-powered coding assistance.
	Cursor	AI-powered code editor configurable with custom API endpoints.
	Aider	Command-line coding assistant leveraging AI.
	OpenAI SDKs (Python/Node.js)	Official libraries compatible with VergeIQ’s API endpoint.
Mobile Applications	Mela (iOS)	Mobile chat application supporting custom API endpoints.
	AI Chat (Android)	Android AI chat apps configurable with custom APIs.
Browser Extensions	ChatGPT Box	Browser extension allowing custom API endpoint configuration.
	WebChatGPT	Extension configurable to various API providers.
Command-Line Tools	llm (by Simon Willison)	CLI tool for interacting with AI models using custom endpoints.
	chatgpt-cli	CLI implementations supporting interaction via custom APIs.

Beyond AI: Infrastructure Observability with ioMetrics

The openness of VergeOS extends beyond its AI capabilities. VergeOS includes ioMetrics, a powerful observability and monitoring solution built directly into the platform. ioMetrics enables IT teams to collect real-time data on infrastructure performance, usage patterns, resource allocation, and more.

With ioMetrics, administrators can:

Monitor Infrastructure Performance: Track the performance and utilization of CPUs, GPUs, memory, storage, and networking resources within your data center.
Analyze Resource Trends: Identify trends and usage patterns to optimize resource allocation and predict future infrastructure needs.
Proactively Address Issues: Detect potential bottlenecks or performance issues before they impact users, reducing downtime and maintaining high availability.
Leverage Open Standards: Integrate seamlessly with industry-standard observability tools like Grafana, Prometheus, and other monitoring dashboards.

By combining ioMetrics with VergeIQ’s AI capabilities, organizations can take infrastructure management to another level—using AI-driven analytics and actionable insights to improve decision-making, operational efficiency, and service reliability.

Filed Under: AI Tagged With: AI, VergeIQ

June 4, 2025 by George Crump

Understanding the ROI of on-premises AI versus cloud AI costs is crucial for enterprises seeking to leverage artificial intelligence without incurring excessive expenses. Organizations that embrace AI quickly realize two truths: the technology can revolutionize their operations, and the public cloud’s AI capabilities can become prohibitively expensive as adoption grows.

Public cloud providers charge per token or query, causing costs to rise rapidly as AI usage expands, effectively penalizing success. In contrast, on-premises AI solutions like VergeOS, which integrates VergeIQ, treat AI as a resource rather than a separate workload. VergeIQ, integrated into VergeOS, offers a flat, one-time cost model, empowering enterprises to leverage AI without incurring unpredictable expenses.

The Hidden Cost of Public Cloud AI

Public cloud AI services initially appear attractive due to the theoretical ease of deployment and assumption of low entry costs. Yet, as organizational usage expands, the token-based pricing results in rapidly escalating expenses. As more departments, teams, and applications begin to utilize AI, costs rise dramatically, complicating budget forecasting and potentially forcing restrictions on usage, which undermines the core value of implementing AI solutions.

The Financial Advantage of On-Premises AI

VergeOS combined with VergeIQ offers a fundamentally different financial model. After an initial investment in infrastructure, enterprises receive unlimited AI capabilities under their control, without ongoing per-token costs. This approach enables predictable budgeting and substantial long-term savings, encouraging broader adoption of AI throughout the organization without additional financial penalties.

The On-Premises AI TCO Benefits with VergeIQ

1. Predictable Budgeting and Cost Control

VergeIQ employs a straightforward flat-fee pricing model, eliminating unpredictable expenses associated with usage-based cloud services. Organizations can accurately forecast budgets, enabling consistent financial planning without surprises as AI utilization expands across departments.

2. Accelerated Enterprise Adoption

Without the constraint of per-token or per-query charges, enterprises can freely encourage widespread AI adoption throughout their organization. This empowers innovation, encourages experimentation, and maximizes the organizational benefits derived from AI without financial hesitation.

3. Enhanced Data Privacy and Compliance

Deploying AI on-premises with VergeIQ ensures sensitive data stays securely within your enterprise environment, eliminating the need to spend valuable time sanitizing or anonymizing datasets. This approach reduces operational costs associated with data preparation. It decreases risks and potential expenses related to the exposure or breach of proprietary data, ensuring full compliance with stringent privacy regulations.

4. The ROI of On-Premises AI Lowers TCO

Integrating AI directly within VergeOS eliminates third-party software costs, reduces infrastructure complexity, and minimizes ongoing operational expenses. The combination of simplified management, reduced external dependencies, and predictable costs results in a notably lower total cost of ownership compared to cloud-based alternatives.

5. On-Premises AI Improves Sustainability and Efficiency

VergeIQ leverages VergeOS’s efficient infrastructure management, optimizing hardware resource usage and decreasing power consumption. This aligns with corporate sustainability initiatives, helping enterprises meet environmental goals while reducing energy expenses associated with AI workloads.

Realize Immediate Business Value with On-Premises AI

VergeIQ allows secure analysis of proprietary data, internal process optimization, and infrastructure automation within your data center. Immediate operational improvements translate directly into measurable business value. The predictable flat-fee model ensures a rapid return on investment (ROI) and eliminates financial surprises associated with cloud-based AI.

The ROI of on-premises AI Means No Operational Overhead

Private or on-premises AI solutions carry a reputation for significant operational overhead due to their complexity and reliance on multiple third-party components. VergeIQ, however, transforms this narrative. Integrated directly within VergeOS, VergeIQ simplifies operations by providing vendor-neutral AI resources alongside built-in virtualization, storage, and networking. This unified approach makes AI capabilities instantly accessible upon installing VergeOS, removing the need for separate installations or complex third-party setups.

Additionally, VergeIQ’s built-in OpenAI-compatible API ensures compatibility with tools and platforms such as LangChain, AutoGPT, ChatGPT interfaces, and other OpenAI-compatible solutions. Enterprises can rapidly integrate existing applications and workflows without retraining teams or re-engineering software. As a result, organizations benefit from powerful, operationally streamlined AI capabilities that reduce complexity, minimize overhead, and accelerate ROI—all fully controlled within their own data centers.

Catch an exclusive preview of VergeIQ during our live webinar and demonstration on June 12 at 1:00pm ET. Register here.

Conclusion: Sustainable AI Investment with VergeIQ

Enterprises have clear choices in adopting AI: escalating public cloud costs or predictable, secure, and cost-effective on-premises AI with VergeOS and VergeIQ. By selecting on-premises AI, organizations gain financial sustainability, complete data control, and a lasting competitive advantage. Reducing costs is just one of the requirements for AI. To learn more, read “Enterprise AI: Key Requirements and Why It Matters.”

With VergeOS and VergeIQ, embracing AI becomes a strategic investment rather than an unpredictable expense, positioning your enterprise to leverage AI’s transformative potential without financial uncertainty.

Filed Under: AI

June 3, 2025 by George Crump

Delivers secure, private, easy-to-use AI that installs in minutes

Ann Arbor, MI — June 3, 2025 — VergeIO, the developer of VergeOS—the first software-defined platform to unify virtualization, storage, and networking—today announced VergeIQ, a fully integrated Enterprise AI infrastructure solution enabling enterprises and research institutions to securely, efficiently, and easily deploy and manage private AI environments.

VergeIQ is not a bolt-on or standalone AI stack. It is seamlessly integrated as a core component of VergeOS, enabling enterprises to rapidly deploy AI infrastructure and capabilities within their existing data centers in minutes, rather than months.

“With VergeIQ, we’re removing the complexity and hurdles enterprises face when adopting AI,” said Yan Ness, CEO of VergeIO. “Organizations want to leverage the power of AI for competitive advantage without losing control of their most sensitive data. VergeIQ provides exactly that—enterprise-ready AI fully integrated within VergeOS, entirely under your control.”

“AI has quickly become a strategic priority across every industry, but organizations encounter significant challenges around infrastructure complexity and data governance,” said Scott Sinclair, Practice Director of the Infrastructure, Cloud, and DevOps segment at Enterprise Strategy Group (ESG). “VergeIQ directly addresses these pain points by making private, secure AI deployment achievable for enterprises of all sizes. This innovation will help drive the next wave of enterprise AI adoption.”

Integrated Enterprise AI Infrastructure

VergeIQ is designed for enterprises needing secure AI capabilities, data privacy, and near-bare-metal performance. Customers can select and deploy various Large Language Models (LLMs)—such as LLaMa, Mistral, and Falcon—and immediately begin using them on their own data within VergeOS’ secure, tenant-aware infrastructure.

Unlike traditional AI stacks that rely on complex third-party infrastructure or GPU virtualization tools like NVIDIA vGPU, VergeIQ provides native GPU pooling and clustering, eliminating external licensing complexity. This native integration ensures dynamic, efficient GPU resource utilization across virtual data centers.

Key Highlights of VergeIQ

Private, Secure Deployment: Fully on-premises, air-gapped, or disconnected deployments ensuring total data sovereignty, compliance, and security.
Rapid LLM Deployment: Instantly deploy popular pre-trained LLMs, including LLaMa, Falcon, OpenAI, Claude, and Mistral, without complex setup or custom training.
OpenAI API Routing: A built-in OpenAI-compatible API router simplifies the integration and interaction of diverse large language models (LLMs) within your workflows.
Vendor-Agnostic GPU Support: Utilize any standard GPU hardware, avoiding vendor lock-in and enhancing flexibility in infrastructure decisions.
Dynamic GPU/CPU Orchestration: Automatically manage and optimize the loading and utilization of AI models across available GPU and CPU resources, maximizing infrastructure efficiency and scalability.
GPU Sharing and Clustering: Dynamic, intelligent pooling and sharing of GPU resources across clusters to ensure optimal usage, performance, and cost-efficiency.
Infrastructure Intelligence: Directly query IT infrastructure to extract actionable insights and simplify operational decision-making rapidly.

VergeIQ will be available as a seamless upgrade of VergeOS to all existing customers, providing full enterprise AI capabilities immediately upon upgrade.

To learn more about VergeIQ and see it in action, register for our upcoming webinar on June 12th at www.verge.io.

About VergeIO

VergeIO is the company behind VergeOS, the world’s first unified data center operating system. VergeOS simplifies and integrates virtualization, storage, and networking into a single, scalable software platform that spans from the edge to the core. With the addition of VergeIQ, VergeIO is redefining how enterprises build, deploy, and manage private and secure AI infrastructure.

To schedule a demonstration or join the VergeIQ Early Access program, visit www.verge.io.

Media Contact:
Judy Smith
JPR Communications
[email protected]
(818) 522-9673

Filed Under: Press Release

June 2, 2025 by George Crump

Organizations across every industry recognize the transformational potential of generative AI. However, deploying these powerful capabilities on-premises has historically been complex, costly, and difficult to manage. Until now. Introducing VergeIQ—an integrated generative AI capability built directly into VergeOS, the unified data center operating system.

With VergeIQ, generative AI becomes another powerful infrastructure resource, seamlessly integrated alongside virtualization, storage, and networking within VergeOS. Once VergeOS is installed, your enterprise immediately gains access to VergeIQ—no additional software, no complicated setups, and no dedicated AI infrastructure required. VergeIQ is built-in, turnkey, and available to IT to help with infrastructure tasks and the organization at large to gain AI insights into proprietary data.

Why On-Premises and Secure AI Matters

Deploying AI completely on-premises is fundamental to achieving genuinely private or sovereign AI capabilities. Hosting AI within your own data center infrastructure ensures full control over sensitive or proprietary information, eliminating the risks associated with external or cloud-based providers. By keeping data entirely within organizational boundaries, enterprises can confidently meet stringent regulatory requirements and compliance standards. An on-premises approach prevents data exposure during transmission and storage in external environments, making it the most reliable way to ensure true data privacy, security, and sovereignty.

How VergeIQ Makes Enterprise AI Practical

Traditional enterprise AI deployments typically require standalone environments, expensive hardware stacks, and deep technical expertise. By introducing VergeIQ, we are breaking down these barriers by embedding AI as a resource natively within the VergeOS platform. This unified approach simplifies deployment, reduces costs, enhances performance, and eliminates the complexity typically associated with generative AI infrastructure.

As a result, enterprises can immediately and privately begin leveraging powerful generative AI models, such as LLaMa, Qwen, Phi, Gemma, within minutes after installing VergeOS. VergeIQ’s design allows you to securely and privately interact with your sensitive documents, proprietary code, and confidential internal datasets, without ever sending your information outside your infrastructure.

Enterprise AI with Day 1 Value

Rapid Analysis and Insights from Internal Documents

From day one, your users will be able to securely upload a wide range of common document types, including PDFs, documents, spreadsheets, text files, HTML pages, and more. VergeIQ quickly processes these documents and generates secure, context-rich summaries, actionable insights, and content tailored to your organization’s information within your own infrastructure. No data leaves your control.

Use Enterprise AI to Securely Explore Proprietary Source Code

For software development teams, VergeIQ is invaluable. It lets you instantly audit, analyze, and optimize your proprietary software codebases, without ever sending sensitive intellectual property off-premises. Developers can quickly identify potential issues, create clear documentation, and accelerate software delivery, all securely within the VergeOS environment.

Accelerate Infrastructure Automation

VergeIQ simplifies infrastructure automation, enabling IT teams to rapidly generate accurate scripts, infrastructure-as-code (IaC) definitions, and workflows. Instead of relying solely on manual scripting, you can securely query VergeIQ to generate automation code tailored to your environment, significantly accelerating infrastructure management across your entire data center.

Use Enterprise AI to Generate Tailored Enterprise Content

VergeIQ empowers business and marketing teams by quickly generating internal documentation, knowledge-base articles, HR policies, or customer communications from your secure, private data sources. Enterprises can confidently produce content that is not only accurate and relevant but also fully compliant with their governance requirements.

Infrastructure Intelligence

And of course, VergeIQ supports querying your IT infrastructure itself. By leveraging the power of VergeIQ, infrastructure teams can obtain immediate operational insights, analyze workloads, predict capacity requirements, and simplify day-to-day operational decision-making. All infrastructure data remains secure, private, and fully accessible within your data center.

Why VergeIQ Makes Sense for Enterprise AI

Hardware Abstraction without Compromise

VergeIQ incorporates intelligent GPU orchestration, vendor-agnostic GPU support, dynamic resource pooling, and highly optimized storage performance. This ensures maximum hardware efficiency, near-bare-metal performance, and lower power consumption. By leveraging VergeOS’s unified architecture, organizations can reach their sustainability goals while enhancing productivity and reducing costs.

Ready to see VergeIQ in action? Register for our world-premier webinar on June 12th.

OpenAI Ready

VergeIQ includes a built-in API router compatible with OpenAI, delivering a smooth and familiar experience for developers. Existing code, scripts, and integrations written for OpenAI APIs can work unchanged, except that your AI models run locally on your infrastructure. This means reduced latency, increased security, and complete data sovereignty, all without the complexity typically associated with private AI deployments.

Use Enterprise AI and gain Operational Simplicity

No Additional Installation Required

A defining characteristic of VergeIQ is its total integration within VergeOS. VergeOS is already recognized as a leading alternative to VMware, helping enterprises simplify their infrastructure and reduce costs. With VergeIQ, the same installation that handles virtualization, storage (VergeFS), and networking (VergeFabric) also provides comprehensive generative AI capabilities—no additional installations, complicated AI stacks, or specialized training needed.

VMware Exit Today, AI Tomorrow—One Platform, Two Major Wins

For many of our customers, transitioning away from VMware to a simpler, cost-effective infrastructure is the top priority. VergeOS is a leading VMware alternative, designed specifically to streamline this process. Introducing VergeIQ shouldn’t change that priority; it should accelerate it, as it is already included with the VergeOS deployment you’ll use as your VMware alternative. Once you’ve completed your migration away from VMware, you’ll immediately have access to a complete generative AI platform, right within your own data center.

But if you’re not ready to exit VMware just yet, you don’t have to wait. You can deploy VergeOS alongside your existing VMware infrastructure right now, instantly gaining access to VergeIQ’s generative AI capabilities. Begin benefiting from VergeIQ immediately, then transition from VMware to VergeOS when the timing works best for your organization.

VergeIQ is ready to deliver value from day one—not only helping you leverage AI to streamline infrastructure management but also supporting a wide range of additional enterprise use cases, as we’ll explore in detail below.

Availability Timeline

VergeIQ will begin preview demonstrations throughout June 2025. The Early Access Program is scheduled to open in July 2025, with General Availability set for August 2025. Existing VergeOS customers will seamlessly upgrade to receive VergeIQ capabilities as a part of their current infrastructure.

Conclusion: Transform Your Organization with Enterprise AI Today

Introducing VergeIQ as an integrated resource of VergeOS means that private generative AI is no longer a future aspiration—it’s a present-day reality. It meets all the requirements of Enterprise AI, allowing organizations to deploy, securely manage, and immediately benefit from generative AI models directly within their own data centers. VergeIQ provides the control, simplicity, and security enterprises demand, paired with the powerful generative AI capabilities that organizations increasingly require.

Ready to see VergeIQ in action? Register for our world-premier webinar on June 12th.

Filed Under: AI

May 27, 2025 by George Crump

The hidden costs of HCI often prevent IT professionals, who are looking to exit VMware, from seriously considering the architecture as a viable alternative. Hyperconverged Infrastructure (HCI) vendors capitalize on this scenario, positioning their solutions as streamlined platforms that seamlessly unify virtualization, compute, storage, and networking. However, this initial promise of simplified infrastructure management frequently masks significant hidden costs and complexities.

Initially intended to unify infrastructure components, traditional HCI has failed to deliver true integration. Compute, storage, and networking resources remain operationally separate, requiring distinct layers in the form of virtual machines (VMs) communicating with the hypervisor. Commonly deployed solutions utilize separate VMs for storage management (e.g., Nutanix’s CVM or VMware’s vSAN), distinct networking stacks (Nutanix Flow, VMware NSX), and individual management VMs (Nutanix Prism, VMware vCenter). True operational simplification remains elusive; what began as convergence is merely the virtualization of legacy three-tier architectures.

How VergeOS Solves the Convergence Problem

VergeOS achieves true convergence through its ultraconverged design. By integrating storage, networking, virtualization, and data services directly into a unified operating environment, VergeOS eliminates silos and redundant communication layers. This cohesive design simplifies operations, reducing complexity, administrative overhead, and resource inefficiency.

Dive deeper with our on-demand webinar: “Comparing HCI as VMware Alternatives.”

The Efficiency Problem

The hidden costs of HCI include its inability to deliver meaningful infrastructure efficiency. Despite sharing hardware, HCI components remain distinct entities, each consuming substantial resources. Dedicated storage VMs, management VMs, separate networking stacks, and additional abstraction layers cumulatively drain compute cycles and memory. Application VMs running within these infrastructures consequently suffer degraded performance and higher latency, forcing organizations to compensate with additional hardware investment rather than benefiting from the initially promised efficiency gains.

For instance, a typical I/O operation in an HCI environment begins at the hypervisor level, proceeds through a storage controller (virtualized as a separate VM), traverses network infrastructure, and finally reaches physical storage media. Each extra step consumes CPU resources, adds latency, and reduces performance efficiency. As workloads scale, the cumulative impact of these inefficiencies affects application responsiveness and resource utilization.

Some HCI vendors utilize data locality to mitigate some of these issues; however, this technology further complicates operations and negatively impacts performance during node or drive failure.

How VergeOS Solves the Efficiency Problem

VergeOS integrates all services, including storage and networking, directly into its operating system, eliminating performance overhead associated with separate management virtual machines or additional software layers. Its lightweight architecture ensures maximum resource efficiency, optimizing performance and dramatically reducing hardware requirements and infrastructure costs.

The High Cost of HCI Inefficiency

The hidden costs of HCI inefficiencies necessitate significant investment in higher-performance hardware to compensate for architectural shortcomings. IT must procure more powerful servers, increased core counts, expanded memory, and faster networking. Furthermore, licensing models that charge per CPU core or capacity exacerbate costs, forcing organizations into substantial capital expenditures. These license models compel customers to purchase less optimal hardware to contain software licensing costs.

How VergeOS Reduces the Cost of Inefficiency

With a streamlined architecture, VergeOS maximizes hardware resource utilization. Its efficient code base and integrated design enable organizations to achieve optimal performance using commodity or existing hardware, reducing initial capital expenditures and ongoing operational expenses. VergeIO licenses VergeOS per-server without penalties for using high-core-count or high-capacity servers.

The High Cost of HCI Data Availability

HCI solutions employ synchronous mirroring—continuous real-time data duplication across nodes—to protect against hardware failures. Vendors commonly refer to redundancy levels as Replication Factor (RF) or Fault Tolerance Level (“failures to tolerate” or FTT). Nutanix refers to protection from one node failure as Replication Factor 2 (RF2), meaning two copies of data are maintained. VMware terms this configuration Failures to Tolerate of 1 (FTT=1).

To protect from two simultaneous node failures or multiple drive failures across nodes, Nutanix uses Replication Factor 3 (RF3)—three data copies—while VMware uses FTT=2. This triple redundancy greatly increases storage capacity and resource requirements. RF3 requires at least five nodes, becoming prohibitively expensive for smaller deployments. In larger environments, limiting resiliency to two node failures is insufficient, as risk increases with node count.

These requirements force prioritizing specific workloads for enhanced protection (RF3), relegating others to standard availability (RF2). Limited redundancy beyond RF3 leads organizations to increase the cluster count per site, resulting in cluster sprawl, which in turn causes additional administrative complexity, higher costs, and uneven availability guarantees.

To maintain performance during node failures, Nutanix and VMware require reserving a portion of resources on each server equal to the capacity of one full node. In a four-server environment, 25% of each server’s resources are reserved for failover, which substantially reduces the available capacity during regular production operations.

How VergeOS Delivers Cost-Effective Data Availability

VergeOS leverages ioGuardian, a deduplicated third-copy data protection method. This efficiently safeguards against multiple simultaneous hardware failures without excessive storage overhead or node count requirements of traditional RF3 implementations. ioGuardian provides robust availability at an economical cost, without requiring workload prioritization, delivering superior resilience at a lower price and complexity.

No reservation of server resources is required. If a node fails, VergeIO’s ioOptimize technology intelligently and automatically reallocates affected VMs to other nodes based on each VM’s resource demands and available server capacities.

The High Cost of HCI Data Protection

The Practice of Snapshotting

Snapshotting commonly provides additional recovery points beyond the capabilities of backup software. However, snapshot-intensive environments impose severe performance penalties, resulting in increased storage I/O and network resource demands. Frequent snapshots or long-term snapshot retention require complex metadata management, demanding more powerful servers, additional memory, and faster storage media. This results in escalated hardware and licensing costs, especially in per-core or per-capacity licensing models common to HCI.

Snapshot chains or numerous simultaneous snapshots greatly increase complexity, hindering disaster recovery processes. Restoring across heterogeneous hardware or hypervisor environments becomes challenging, restricting operational flexibility.

How VergeOS Simplifies Data Protection

VergeOS utilizes ioClone technology, integrated with its global inline deduplication, to create space-efficient, independent snapshots with minimal metadata overhead. ioClone’s architecture supports near-continuous snapshot execution and indefinite retention without performance degradation, enabling rapid and efficient data protection without the need for costly hardware upgrades or complex snapshot management. The combination of ioGuardian and ioClone also reduces the organization’s dependency on backup, lowering the costs of backup software licensing and backup hardware infrastructure.

The High Cost of HCI Inflexibility

The hidden costs of HCI architectures imposing strict hardware compatibility and homogeneity requirements are significant. Expanding storage or compute resources mandates identical hardware, limiting flexibility and increasing long-term infrastructure costs. Adding nodes of different brands, generations, or capabilities creates additional clusters, which fragment management and reduce efficiency.

How VergeOS Enhances Infrastructure Flexibility

VergeOS supports heterogeneous hardware environments, enabling organizations to integrate diverse hardware configurations into unified, scalable clusters seamlessly. This flexibility reduces costs, simplifies expansion, and maximizes investment longevity, enabling adaptive infrastructure growth without imposed constraints on homogeneity.

overcome the hidden costs of HCI inflexibility

An Example of The Hidden Costs of HCI vs. VergeOS

Consider a three-node infrastructure using traditional Hyperconverged Infrastructure (HCI), where the organization’s goal is to maintain continuous data availability even after two simultaneous node failures. Traditional HCI solutions, such as Nutanix or VMware vSAN, require at least five nodes configured with Replication Factor 3 (RF3), or a Fault Tolerance Level of 2 (FTT=2), ensuring continuous availability despite two node failures. In addition, these solutions require maintaining sufficient free storage capacity at all times to accommodate a complete rebuild in the event of node failures, thereby reserving capacity equivalent to an entire node, which further reduces usable storage space.

Because the customer wants to leverage their existing hardware—a heterogeneous mix of Dell and HPE servers—traditional HCI platforms present immediate compatibility and cost challenges. Traditional HCI requires uniform hardware for seamless operation, which adds complexity and cost.

Cost Analysis for Traditional HCI

Achieving protection from two simultaneous node failures requires:

Minimum Node Count: 5 nodes (uniform hardware required).
Replication Method: RF3 or FTT=2 (three synchronous copies of all data).
Usable Capacity: Reduced to approximately 33% due to triple mirroring overhead.
Reserved Free Capacity: Additional storage space equal to one node’s full storage capacity, always kept available to allow immediate rebuilds after failures.

In this scenario, the customer faces:

The necessity of purchasing additional uniform hardware due to vendor compatibility guidelines.
Higher software licensing costs, typically calculated per CPU core.
Significant reserved resources on each node (compute and storage) are allocated exclusively for node failure scenarios.

This dramatically increases capital and operational expenses, requiring significant investment in new hardware and licenses, thereby negating the anticipated HCI savings.

Cost Analysis with VergeOS

In the same scenario, VergeOS offers substantial advantages:

Minimum Node Count: 3 nodes (uses existing Dell and HPE hardware).
Replication Method: Integrated distributed mirroring combined with VergeOS’s independent, deduplicated third data copy via ioGuardian, which can be installed on any available standby server.
Usable Capacity: Approximately 50% (due to two-way mirroring), augmented by ioGuardian’s deduplication efficiency.
Reserved Free Capacity: Minimal additional storage capacity needed due to ioGuardian’s efficient data protection strategy, reducing rebuild space requirements compared to traditional RF3 architectures.

With VergeOS, you benefit from:

No need for uniform hardware, allowing immediate use of existing Dell and HPE servers.
Reduced licensing and hardware costs, as no additional nodes or extensive resource reservations are required.
Enhanced data availability beyond traditional two-node failure protection without extensive reserved storage, reducing overhead and complexity.

Summary of Cost Benefits

Traditional HCI requires two additional nodes (totaling five) and mandates uniform hardware, increasing both capital and operational expenses, compounded by large reserved capacity requirements for rebuilding data. VergeOS provides superior resilience, operational continuity, and cost efficiency by leveraging existing heterogeneous hardware and substantially reducing the need for reserved rebuild capacity.

Conclusion

While hyperconverged infrastructure initially promises simplicity, efficiency, and cost savings, underlying architectural limitations quickly surface as substantial hidden costs. Challenges such as insufficient convergence, operational inefficiencies, costly availability and protection schemes, and restrictive infrastructure flexibility erode promised benefits. Organizations should carefully assess these hidden costs when evaluating HCI solutions, prioritizing converged, integrated infrastructures like VergeOS that fundamentally address these critical challenges, enabling efficient, cost-effective, and future-ready IT environments.

Filed Under: HCI Tagged With: Alternative, HCI, Hyperconverged, UCI, VMware