Enterprise AI Infrastructure
Trusted & Certified
NemoClaw enterprise deployment is the process of setting up NVIDIA’s NemoClaw framework on your own infrastructure, so your team can use advanced AI agents without relying on the cloud. Instead of sending sensitive data to third-party platforms, the system runs inside your environment, whether that is an RTX workstation, a DGX cluster, or a secure on-premise setup.
For healthcare, finance, legal, and other regulated sectors, a proper NemoClaw deployment goes beyond installation. It includes infrastructure planning, security hardening, access controls, model setup, and internal system integration so the platform is ready for real business use. At Ment Tech, we deliver NemoClaw enterprise setup with a focus on security, control, and long-term usability.
Updated Mar 2026
ISO 27001 · Certified
SOC 2 Type II · Compliant
Deloitte Fast 50 · Awarded
ERC-3643 · Compatible
KYC / AML · Integrated
MiCA-Ready · EU Compliant
VARA · UAE Licensed
OpenAI Partner · Certified
ISO 27001 · Certified
SOC 2 Type II · Compliant
Deloitte Fast 50 · Awarded
ERC-3643 · Compatible
KYC / AML · Integrated
MiCA-Ready · EU Compliant
VARA · UAE Licensed
OpenAI Partner · Certified
ROI & Value
Turn AI infrastructure into a long-term advantage. See how on-premise NemoClaw improves ROI through lower cloud costs, stronger data control, and reduced compliance risks.
Key Metrics
3-Year TCO vs Cloud AI
Compliance Risk Reduction
Inference Latency
Regulatory Exposure
Cloud AI Subscription Elimination
$300K–900K/year
Compliance Incident Avoidance
$1.9M–10M risk reduction
Data Egress Costs
$50K–200K/year
Productivity Gain
$500K–2M/year
Case Study
12-Hospital Regional Health System (8,000 staff)
Industry: Healthcare
The Challenge
The hospital network wanted to introduce AI, but its CISO had blocked all cloud AI tools because of HIPAA and patient data exposure concerns. That left more than 8,000 staff without access to AI support, while leadership still needed a secure solution that could work with Epic and keep PHI fully inside the organization’s infrastructure.
Our Solution
Ment Tech deployed NemoClaw on 4 DGX A100 nodes and configured a Llama 3.3 70B model for clinical documentation workflows. We connected the platform to Epic through an FHIR R4 MCP connector, added role-based access controls for clinical and administrative teams, and routed audit logs into the hospital’s existing SIEM for compliance visibility.
100% ↗ All PHI stays on hospital servers
Data Residency
$28,560 ↗ saved in the first year alone
Annual Savings
Full ↗ BAA not required — no external transfer
HIPAA Compliance
73% ↗ Clinical staff using AI daily within 60 days
Staff Adoption
$0 ↗ vs projected $280K/year cloud alternative
Cloud AI Cost
Comparison
Our Recommendation
When sensitive data is involved, there is little room for compromise. For organizations handling PHI, PII, financial or legal records, and classified data, on-premise AI is often the only model that truly meets security, compliance, and data sovereignty needs.
Let's Build Your AI Strategy Together
Let’s build your AI strategy together. Schedule a complimentary 30-minute call with our senior AI architects to discuss your infrastructure, compliance constraints, and deployment goals.
Ment Tech delivers NemoClaw enterprise deployment on your existing RTX or DGX infrastructure or helps you choose the right setup if new hardware is needed. The goal is not just to get NemoClaw installed, but to turn it into a secure, production-ready AI environment that fits your performance, compliance, and internal system requirements.
Hardware-Optimized Deployment
We configure NemoClaw deployment around your actual hardware, whether that is an RTX 4090 workstation, a multi-GPU server, or a DGX H100 cluster. From inference optimization to model tuning and throughput planning, the setup is built to run smoothly in real enterprise conditions.
Enterprise Security Posture
A proper, secure NemoClaw deployment needs more than infrastructure alone. We set up identity controls, RBAC, department-level isolation, audit logging, encrypted internal communication, and optional air-gap support so the environment is ready for enterprise security review.
On-Premise System Integration
Our NemoClaw deployment services include connecting the platform to the systems your teams already use, including EHRs, banking platforms, document management tools, and internal databases. That way, NemoClaw becomes part of real workflows instead of sitting as a standalone AI environment.
Custom Model Fine-Tuning
We also support NemoClaw enterprise setup with model tuning based on your domain data, whether that includes medical records, legal documents, or financial data. This helps the system deliver more relevant, reliable output for the work your teams actually do.
For healthcare, finance, legal, and other regulated sectors, the challenge is not whether teams want AI. It is that most cloud AI tools create real concerns around data control, compliance, and internal security. That is why many organizations need AI that runs inside their own environment.
Data Residency Compliance
Many organizations cannot send patient records, financial data, legal files, or internal documents to external AI platforms. They need tighter control over where data stays, how it is processed, and who can access it.
Air-Gap Requirements
Some environments require AI systems to run without internet connectivity at all. In those cases, cloud AI is not just a compliance risk. It is not a workable deployment option.
Cloud AI Cost at Enterprise Scale
Cloud AI costs can rise quickly once usage expands across teams and departments. For larger deployments, on-premises infrastructure often becomes a more practical long-term option.
GPU Hardware Already Owned
Many enterprises already have NVIDIA hardware in place for AI or data workloads. What they often lack is the expertise to turn that infrastructure into a secure and usable AI environment.
Complex Enterprise Integration
Running AI is only part of the challenge. Connecting it to EHRs, banking systems, document platforms, and internal databases requires careful integration work that most teams cannot handle through a basic setup alone.
Multi-Tenant Enterprise Access
Enterprise AI needs more than shared access. Teams usually require SSO, role-based permissions, department-level isolation, and audit visibility before the system is ready for wider internal use.
Relying on cloud AI can increase compliance risk, while blocking AI entirely slows teams down. For many enterprises, the bigger risk is failing to deploy AI in a way the business can actually use.
Built for organizations that need more than a basic install, our NemoClaw enterprise deployment covers the infrastructure, security, integration, and operational layers required to run AI reliably inside regulated environments.
Hardware Readiness and Performance Planning
We assess your existing hardware, model fit, runtime compatibility, and performance requirements so the deployment is built around what your environment can support in real use.
NemoClaw Stack Deployment
We deploy the full NemoClaw stack inside your environment and configure the core runtime, orchestration flow, model serving layer, and supporting services needed for a stable setup.
On-Premise Model Deployment
We deploy and tune the right open models for your use case so the system performs well for internal workflows such as research, summarization, or document-heavy tasks.
Enterprise Security and Access Control
A proper, secure NemoClaw deployment needs strong internal controls. We configure SSO, role-based permissions, encrypted communication, audit logging, and optional isolation settings for safer enterprise use.
Internal System Connectivity
Our NemoClaw deployment services include connecting the platform to the systems your teams already use, including EHRs, banking tools, document platforms, and internal databases.
Private RAG Knowledge Setup
We build on-premises knowledge bases from your internal documents so agents can retrieve approved information without sending sensitive content outside your environment.
Monitoring and Operational Visibility
We set up logging, performance tracking, latency monitoring, and alerting so your team has a clear view of how the platform is performing over time.
Department-Level Agent Isolation
Different teams need different access. We configure department-level separation so each group can use NemoClaw with the right permissions, tools, and data boundaries.
Compliance Documentation Support
We also help prepare the documentation needed for internal reviews, security checks, and compliance sign-off, making NemoClaw enterprise setup easier to approve and move forward.
See Our AI Solutions in Action
Get a personalized live demo built around your infrastructure, workflow, and compliance requirements. You will speak directly with the engineers who understand how the platform is deployed in production.
Technical Architecture
A fully on-premise, air-gap-capable AI agent stack built on NVIDIA hardware.
Air-gap-capable deployment with no required internet connectivity after setup
FIPS 140-2 compliant cryptographic modules for data at rest and in transit
Active Directory integration with department-level RBAC enforcement
Full audit trail of AI interactions with timestamping and response traceability
NVIDIA Confidential Computing support on H100 for model protection
Network micro-segmentation and isolated VLAN deployment
Signed container images from NVIDIA NGC registry for supply chain integrity
A deployment-ready enterprise stack built for secure on-premise AI.
AI Frameworks & Libraries (12)
ML Infrastructure & Cloud (10)
Foundation LLM Models (8)
Business Integrations
Our process is built to take NemoClaw from infrastructure planning to a production-ready setup in a clear, structured way. For most enterprise environments, the full deployment is completed in 10 to 15 business days.
We begin with a detailed review of your hardware, network environment, security requirements, integration needs, and compliance considerations. This helps us plan the right deployment approach before any installation begins.
Once the environment is validated, we deploy the NemoClaw stack, configure the core runtime, and install the model setup best suited to your use case. At this stage, the focus is on getting the platform stable, responsive, and ready for internal use.
Next, we secure the environment for real enterprise use. That includes access controls, role-based permissions, encrypted internal communication, audit logging, and the security settings needed for internal review and approval.
We then connect NemoClaw to the internal systems your teams actually use, such as EHRs, document platforms, banking systems, or custom internal tools. This is where the deployment becomes practical for real workflows.
In the final phase, we run user acceptance testing, validate performance, review documentation, and prepare the environment for production rollout. This ensures the system is usable, secure, and ready for internal adoption.
Meet compliance requirements without slowing down AI adoption. NemoClaw regulatory compliance helps organizations deploy on-premises AI with stronger alignment to data privacy, security, and industry-specific governance needs.
European Union
United States
United Kingdom
Singapore
UAE
Canada
Australia
EU AI Act
Risk-based AI regulation — High-Risk AI system requirements
NIST AI RMF
NIST Artificial Intelligence Risk Management Framework
ISO/IEC 42001
International AI management system standard
GDPR Art. 22
Automated decision-making and profiling protections
SOC 2 Type II
Security, availability & confidentiality for AI systems
OWASP LLM Top 10
Security risks for large language model applications
CDEI AI Governance
UK Centre for Data Ethics & Innovation guidance
MAS AI Guidelines
Singapore MAS Fairness, Ethics, Accountability guidance
Protect sensitive AI operations with stronger control at every layer. NemoClaw enterprise security is designed to support on-premises deployments with tighter access control, data protection, auditability, and risk reduction
Trail of Bits
AI/ML security assessments
HiddenLayer
AI model security platform
Robust Intelligence
AI risk management
BishopFox
AI red teaming services
NCC Group
Enterprise AI security
Cure53
LLM API security testing
HIPAA Technical Safeguards
SOC 2 Type II
GDPR Article 32
FIPS 140-2
ISO 27001
Prompt injection detection and prevention
Output filtering and moderation
Role-based access control
PII detection and automatic redaction
Hallucination detection and confidence scoring
Rate limiting and abuse prevention
Audit logging for all AI interactions
Model versioning and rollback
Adversarial input detection
Data residency and sovereignty controls
End-to-end encryption for sensitive prompts
Human-in-the-loop escalation workflows
Enterprise-Grade Security
Bank-level encryption, hardened deployment standards, and enterprise monitoring built for regulated production environments.
256-bit AES Encryption
99.99% Uptime SLA
24/7 Monitoring
Professional NemoClaw deployment packages for organizations that need on-premise AI with full control over data, infrastructure, and compliance.
NemoClaw Workstation
A single-workstation deployment for small teams or departments running AI locally for focused internal use.
Departments piloting on-premise AI or smaller organizations with existing RTX hardware
NemoClaw Data Center
A multi-GPU or DGX deployment for mid-sized to large organizations that need secure, multi-user AI infrastructure.
Mid-to-large enterprises in healthcare, finance, legal, and other regulated sectors
NemoClaw Enterprise Platform
A full enterprise AI platform for organizations requiring large-scale deployment, custom models, and maximum sovereignty.
Large enterprises, government organizations, and defense environments
Included in Every Engagement
FAQ
NemoClaw enterprise deployment means setting up NVIDIA’s NemoClaw stack on your own infrastructure, so AI agents can run with stronger privacy, control, and operational oversight. It is designed for teams that want to use AI internally without depending fully on cloud-based environments.
OpenClaw gives you the core agent framework, while NemoClaw adds more structure around security, policy enforcement, and controlled execution. That makes it a better fit for organizations looking for a more governed deployment approach.
NVIDIA’s current documentation says NemoClaw is still in alpha preview, so it is better suited today for controlled pilots, internal testing, and phased enterprise rollout planning. For most organizations, that means validating the setup carefully before wider adoption.
NemoClaw adds policy-based guardrails, sandboxed execution, privacy controls, and more granular permissions around agent behavior. These controls are part of what makes a secure NemoClaw deployment better suited to sensitive internal use cases.
NVIDIA says NemoClaw can run across local, on-premises, and GPU-backed environments, including RTX and DGX systems. The right setup depends on your workload, performance needs, and internal infrastructure.
NemoClaw is built around stronger privacy and deployment control, which makes it relevant for restricted environments. In practice, air-gapped use depends on how the full stack is designed, secured, and maintained within your infrastructure.
The hardware depends on the model size, user load, and response speed you need. Smaller deployments may work on RTX-class systems, while heavier enterprise use cases usually need more powerful GPU infrastructure such as DGX environments.
Still have questions?
Can’t find the answer you’re looking for? Our team is here to help.
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Give your team access to secure on-premises AI while keeping sensitive data inside your own infrastructure. NemoClaw enterprise deployment helps regulated organizations move forward with AI in a way that is easier to govern, secure, and scale.